Drawn to scale the “crust’ we inhabit would be invisibly thin, our entire planet is a giant radioactive ball of magma that has been burning for over 3.5 billion years.

174 petawatts of solar radiation hit the Earth daily

I addressed the irrational belief that fuel-efficient cars are somehow environmentally friendly in my last article, in this one I would like to examine other “alternative” forms of transportation and energy.  To begin with, let’s try to establish a rational foundation for examining these issues.  There are only three usable sources of energy available to us on this planet.  Solar, nuclear (geothermal energy is nuclear) and gravitational (tidal).  It’s easy to lose sight of this fact because energy can be stored and transported in many different forms BUT there are only THREE sources of it available to us.  The first societal delusion that is widely and irrationally held is that energy is in short supply and can be consumed.  The Sun blasts us with about 174 petawatts of energy per day… which will almost ALL be wasted regardless of what we do.  The planet Earth which is 99.99% MAGMA heated by nuclear decay will radiate roughly 44 terawatts of heat into the atmosphere per day… which will also almost all be wasted regardless of what we do and finally gravitational tidal forces between the Earth, Sun and Moon radiate roughly 3 terawatts of energy per day.  To better put this in perspective, imagine that we live on a paper thin layer of insulation (the Earth’s crust) that shields us from being broiled in an 18inch deep pot of 6000 degree hot magma under a paper thin atmosphere that shields us from being broiled by 174 petawatts of solar radiation.  Without the Earth’s thick, cloudy, polluted atmosphere to protect us, we wouldn’t last a day exposed to ordinary solar activity.  None of this energy is “renewable”, almost all of it will be “wasted” and it will never be in short supply to us.  In other words, we can’t “consume”, “waste” or otherwise “run out” of energy.  It is INFINITELY abundant to us.  All economic arguments that derive from one of these assumptions are FALSE.  This energy will be radiated by the Earth regardless of how human beings harness it.  No human activity adds or subtracts any energy from this equation.

The next absurd premise that underlies many eco-logical arguments is that we are somehow consuming resources on Earth as though the materials we harvest from the Earth’s crust are destroyed when we make stuff out of them and when we throw them away they are ejected into outer space never to return.  Obviously none of this is true.  Once again, all human activity is confined to a paper thin layer of the Earth’s crust… the rest of the planet is made out of metals, rare-Earth elements, nuclear materials and resources beyond any human hope of consumption, as with energy we will never “run-out” of these materials.

The forces that actually govern the cost and availability of energy and resources to us is the RATE at which we can harvest, store and transport energy in forms usable to human activity.  What is “limited” to us is the RATE and EFFECIENCY with which we can harvest the boundless volumes of energy that are wasted every day.  In this respect our RATE of energy generation is NOT limited by availability or technology but by the RATE at which we can remove the waste products of energy use from our ecosystem.  Waste products resulting from organic energy metabolism is called manure when we produce it internally or “pollution” when we produce it externally.  Oddly we all understand that producing manure is a natural and harmless byproduct of life that is naturally and beneficially recycled by the environment but for some reason we tend to believe that “pollution” is a toxic destructive force that permanently harms it.

In the context of analyzing energy usage economically, it is important to recognize that we do not consume energy, nor is there ever a shortage of supply.  There are only efficiency constraints on the rate at which we can collect, store, transport and dispose of the waste products associated with harvesting the INFINITE energy available to us.  This observation is also a very valuable analytic tool because it immediately informs us that the costs associated with the value of all physical goods and services are tightly bound to the costs of the energy sources associated with their creation, storage, distribution and disposal.  In this respect a car is no different from a type of battery or solar panel in economic terms.  It requires a certain amount of energy to make, store, transport and dispose of.  A cars monetary value is, in an indirect sense, a measure of how much economic energy it can help us collect.

In the same sense a solar panel or a windmill is not a “source” of energy.  They are machines made out of matter that required energy to make them that transform solar energy from an actual energy source into a usable form for human consumption.  Unlike a car who’s energy value to us is very abstract a solar panel or a windmill is very simple to analyze because directly producing electricity is its only job.  At this stage I am tempted to do a brilliant and detailed mathematical analysis of how much energy it takes to mine, manufacture, transport, maintain and dispose of these devices, however that would be boring and a lot of work and the conclusion we would reach would be the same one we arrive at by simply asking… if these devices are efficient sources of energy… why don’t we make them using the energy they supply?  Are wind mills and solar panels made from energy produced by windmill and solar energy farms?  Why not?  Clearly if they were the most efficient sources of energy, that would be the cheapest way to produce them… right?

A common counter-argument might be… we know they’re not efficient BUT they pollute less!  Really?  How could it be LESS polluting to use fossil fuels to mine and manufacture solar panels and windmills which are then used to generate electricity… rather than to burn the same fuel DIRECTLY for electricity without the apparently redundant intermediate step of making a solar panel or windmill?  Do you think that the solar panel or windmill generates MORE power than was required for its creation?  If that were true then we would have an infinite energy supply as a chain reaction of windmill and solar panel farms would explode around the world to make more windmills and solar panels at greater cost efficiency than burning fossil fuels!  The fact that wind farms and solar farms don’t reproduce like errant bacteria colonies tells us exactly what we will find when we add up the energy costs associated with mining the materials necessary to making a solar panel, add up the energy cost associated with MELTING GLASS to form a solar panel, the cost of the real-estate it has to occupy to gather light, the maintenance cost over time and the disposal cost.  We will find that a solar panel or wind mill consumes more energy than it ever generates… hence the reason they COST more to adopt than using the conventional fossil fuels that supplied the original energy necessary to making them, directly.

So why is it that we IMAGINE that consuming fossil fuels to make LESS efficient energy sources is LESS polluting or wasteful?  Where does this societal mass-delusion come from?  Obviously people with an interest in selling solar panels have an interest in having us believe that they are green and/or efficient by making arguments like the following;

http://www.care2.com/greenliving/do-solar-panels-use-more-energy-than-they-generate.html

So… they make the case that solar panels ARE net energy positive and cost saving IF you neglect to account for the cost of the real-estate they occupy, the cost of maintaining them and the cost of the government subsidies in the form of taxes dollars to support them and the costs government adds to the cost of fossil fuel alternatives through taxation and regulation?  Solar Panels have in fact become SO energy efficient that the entire US market for manufacturing solar panels utterly collapsed in recent years and almost all of the solar panels we purchase today are made in China using power generated by burning fossil fuels with no costly American restrictions on polluting that would otherwise make industrial manufacturing of solar panels “Too expensive”, or costly American pollution taxes on the use of fossil fuels to also inflate the cost of manufacturing them.   Thus, ironically, solar panels have indeed become more energy efficient in recent years by virtue of EXPORTING the pollution to China and thus circumventing the regulations and taxes imposed in the US that made them expensive.

More interestingly, why would they need to actively REFUTE the argument that solar panels and windmills are net energy consumers and net polluters if it’s not true?  Free market economics doesn’t need to be argued, it speaks for itself.  Why don’t we turn off the government subsidies for green energy and watch the wind farms and solar farms spring up like daisies across the countryside as a result of the FLOOD of eager investment dollars vying to make billions arbitraging the growing gap in cost between fossil fuel costs and solar or wind costs?  Unless there is no actual gap… You don’t need a bunch of PhD’s to research the subject when the market will do the work for you and the market “consensus” is that “green energy” sources are net consumers of energy and net polluters.  The only force improving their efficiency is exporting their pollution and associated tax costs to China, where, no matter how much we improve their efficiency and manufacturing cost… they are still not made with solar or wind power for some reason.

Interestingly China does have the largest solar energy production capacity in the world… why?  As I stated earlier, energy production is a rate problem NOT a supply problem.  China has more empty dessert waste land owned by the state than it has fossil fuel resources it can mine itself.  The Chinese government does not have to pay for land because it owns it all.  It has vastly lower transportation and maintenance costs for solar power than the US by virtue of making solar panels LOCALLY and China does not have to pay for solar power with debt, it can invest interest paid on our debt to their government to build solar farms, so the economics of solar power in China are radically different from the economics in the US.  Interestingly whatever those economics may actually be, China’s plan is to increase nuclear power production at 4 times the rate of solar power production by 2020, so even the brutally pragmatic Chinese with their vastly more efficient solar costs, don’t believe it is their most efficient source of energy.

“China is a large producer of polysilicon, for use in first generation solar cells around the world. A byproduct of the process is poisonous silicon tetrachloride, which is normally processed and recycled at a higher cost in the developed world, but often dumped by Chinese green startups.^{[citation needed]} With proper recycling the polysilicon would cost $84,500 per tonne, but the Chinese companies are making it at $21,000 to $56,000 a ton.^[14]“

“Zhejiang Jinko Solar Co., Ltd., founded in 2006 as a subsidiary of Hong Kong-invested JinkoSolar Holding Co, Ltd (NYSE Stock Code: JKS), produces solar panel photovoltaic cells and wafers. It employs more than 10,000 professionals in two factories in east China and has offshore offices and warehouse in the United States and Europe, according to the company website (www.jinkosolar.com). On Thursday, 15 September 2011, more than 500 people from Hongxiao Village protested over the large-scale death of fish in a nearby river. Angry protesters stormed the factory compound, overturned eight company vehicles, and destroyed the offices before police came to disperse the crowd. Protests continued on the two following nights with reports of scuffle, officials said. Chen Hongming, a deputy head of Haining’s environmental protection bureau, said the factory’s waste disposal had failed the pollution tests since April. The environmental watchdog has warned the factory but it had not effectively controlled the pollution, Chen added.^[15]“

The energy consumed by people WORKING to generate income is ALSO wasted when it is consumed as tax dollars. If these folks are taxed at 20% then they must work roughly 25% more (compound taxation) to feed their families and expend proportionate additional energy.

Finally there is a massive issue which is constantly overlooked or selectively avoided in all rational dialog about the economics of energy production and efficiency, which is the role the government plays when it manipulates energy markets through taxation, regulation, debt accumulation and incentives.  The same people who readily embrace the idea that driving less reduces fuel consumption don’t grasp that reducing driving through taxation of punitive regulation is also wasteful.  Doing work to generate income ALSO consumes energy and the portion of that productive work that is consumed by the government in the form of taxes is “WASTED” energy or productivity.  Raising the COST of transportation by taxing it doesn’t reduce overall energy consumption or pollution, it just shifts the wasted energy and pollution associated with that transportation into the government’s hands which in turn SPENDS those dollars on more energy consuming activities… like hiring bureaucrats to enforce regulations who also need cars to get to work.  So EVEN if you imagine that certain economic activities involving the consumption of fossil fuels are BAD for the environment, you would be STUPID to believe that taxing or regulating them had any impact on reducing the net consumption of energy or pollution.   The only ACTUAL way to REDUCE energy consumption and pollution is to have fewer people and to make them all poorer.  Any growth in economic activity will result in growth in energy consumption and “pollution”, the two are intimately linked.  Neither can “efficiency” be imposed on a market through any form of government intervention because government never has the power to reduce the cost of anything, it can only increase a cost through taxation or regulation.  Cost reduction is the exclusive domain of free market price competition.

So if all of these beliefs about energy economics and government are obviously flawed and foolish, why do we believe them?  Certainly some people are just ignorant, ideologues’ or profit from this misinformation but there is also a genuine rational reason to believe that these “alternative” forms of energy are somehow beneficial.  Governments have the power to print money and run debts which is a powerful way of hiding the real cost, wasted energy and pollution associated with these energy alternatives in the future where people in the present don’t experience it.  The use of debt to hide wasted energy and pollution in the future, combined with people’s inability to recognize taxation as a form of wasted energy and pollution results in many common economic misconceptions about energy efficiency.

For example, the common delusion that “public transportation” is more efficient than private or commercial transportation.   Public transportation achieves this “claim” through tremendous debt and the taxation of everybody NOT using the system to subsidize the “affordable” fairs for the people who do use it.  Increasingly the state and Federal government pays for public infrastructure with debt that is NEVER repaid which means that the amount of energy and pollution required to support them is effectively infinite.  It is actually impossible to make the case that ANY source of energy or transportation is “efficient” as long as it is paid for with debt that does not have to be paid off entirely within a specified timeframe.

Every American citizen owes roughly $50,000 in government debt and $1,000,000 in unfunded entitlement liabilities. Paying this debt would require the confiscation of 100% of all publicly traded assets in the United States. If 100% of the wealth of all US millionaires were confiscated the debt would be reduced to 4 trillion dollars and still be accumulating at a rate of roughly 1.2 trillion dollars a year.

From this point of view, the interest a government pays on any debt that does not contribute towards paying it off is wasted energy and a source of pollution in the form of energy consumed and wasted by the productivity of tax payers in order to make that debt payment.  Thus, anybody who is serious about their ecological concerns would advocate against the accumulation of government debt, or the use of taxation to create roads and transportation infrastructure (which also takes energy and pollutes)  Why tax people’s fuel consumption to punish them for driving when the same goal could be accomplished without wasted economic activity and pollution by simply not building roads in the first place?  Obviously I’m not an advocate of doing this, I’m just illustrating the absurdity of the economic and ecological premises so many of us seem to accept without question.

Ultimately any societal debt must be paid with interest in wasted economic activity or our society must eventually collapse as the Soviet Union did.

Finally, why do we care about “consuming” the Earth’s “non-renewable” energy resources?  If they are evil pollutants that we are in imminent danger of using up, then it would seem that the problem was about to solve itself right?  Well, it turns out that we are discovering NEW sources off “non-renewable” fossil fuels FASTER than we can consume them.  In which case, we don’t really know how non-renewable they are because we aren’t actually running out of them… so therefore we must JUST be upset about the pollution they create, right?  Except the “pollution” we are worried about is CO2 gas a natural byproduct of all organic metabolic activity on Earth and food for plants!  Setting aside the interesting argument as to whether or not pouring trace quantities of plant food into the atmosphere is “pollution” the prescription for “solving” this serious problem is to TAX it… again as though confiscating money from people who CONSUMED ENERGY earning it and SPENDING IT on additional economic activity would have any rational impact on reducing net consumption of energy or net pollution.  So we live in a strange world where we imagine that we are guilty of terrible energy waste and ecological devastation AND believe that the solution is to invest in accelerating it through taxation, debt accumulation and regulation.  Thus even if you accept that human activity is having a devastating impact on the environment and that precious limited energy resources are being consumed, every prescribed solution that we widely accept for these problems does nothing but AMPLIFY them IF they actually existed.

The post Eco-nomics appeared first on The Saint.

The experience also led me to coin the term “Quantum-Economics” to describe the world of frictionless online commerce which arose modifications I made to the traditional micro-economic supply and demand equations to account for the lack of costs, inventory and distribution friction associated with online media.  One of the reasons for calling my modified equations “Quantum-Economics” was the realization that in the absence of “classical” market forces, micro-economic modeling took on wave-like properties more akin to the math that describes quantum physics rather than the math of classical Newtonian physics.  The point of all of this is that my success with applying economic theory to saving my failing company gave me a deep and abiding fascination and appreciation for the subject which caused me to begin looking at many aspects of life in micro-economic terms.  The trouble with learning economics is that in the absence of hands-on experience it can seem remote, abstract and unintuitive.  In other words, it doesn’t appear to make “common sense”.  For me, it took applying and succeeding with it in the real-world for a light to go in my mind and for me to start seeing the economic forces at work in everything around me.

I’ve written many articles on the subject of “Quantum-Economics” and its power for designing online business models for this blog, but I would like to try to share my fascination with the power of economic analysis with others who may not have learned an “intuition” for it given it’s often seemingly abstract implications.  I read and truly enjoyed the book Freakanomics and would recommend it to everybody as a great starting point.  It’s one of those great books that makes a seemingly dull subject riveting and personal.  In the same vein, I would like to explore some economic subjects that are a little off the beaten path but which I find fascinating because of their counter-intuitive properties.  Because of my own strange interests in physics I tend to look for examples of “Quantum Economic” influences in the classical world… which really just means that I like to look for examples of real-world situations in which the absence of classical economic friction results in strange or interesting economic dynamics… more importantly, examples of situations in which people’s misguided economic “common-sense” results in irrational behavior.

Many years ago in the 1990’s I read a report on how the introduction of fat-free Olestra based potato chips had impacted potato chip sales which I recall to this day as having seeded my mind with the early ideas that would lead to developer Quantum-Economic models for online goods a few years later.  I can’t find the original study online today, but this article is a great reference on the subject.

http://business.highbeam.com/industry-reports/food/potato-chips-corn-chips-similar-snacks

Basically, what happened was that potato chip sales began declining precipitously in the 1990’s as a result of a “health-conscious” movement in America away from salty and fatty processed foods.  This resulted in the food industry introducing “healthier” potato chips with less salt and fat… which resulted in a massive increase in sales of these products and… more interestingly… an even more disproportionate increase in salt and fat consumption!  In other words, people seeking healthier food choices and food companies supplying them resulted in Americans eating MORE FAT AND SALT as a result.   This phenomena was, of course a great economic mystery to a lot of people, but good economic analysis illustrated exactly HOW this seemingly absurd phenomena came about.  Most interestingly to me, is that today I see the answer in “quantum-economic” terms.   Classical economics doesn’t seem to explain how this phenomena would occur because if people demand LESS salt and LESS fat than you would expect the supply and consumption of these goods to DROP not increase, right?  If I replace bags of potato chips on store shelves with the same quantity of product containing less salt and fat at the same price as the old product, assuming no other variables, such as taste, changed, I would expect to sell the same volume of product, make the same money but end up with people consuming LESS salt and fat, right?

Well, obviously, I’m going to say WRONG… but why?  Something else MUST have changed right?  I don’t think anybody would argue that the new products tasted BETTER or that suddenly stores started devoting twice as much shelf space to chips.  What changed?  This is where the strange economics begin to emerge.  Economic theory was really designed to describe how goods and services are exchanged for MONEY, but money isn’t the only currency that people trade-in, it’s just the currency that we tend to think about.   In this case video games and potato chips actually have a lot in common.  Neither product has any real productive or redeeming properties, yet we VALUE them for some reason.  Consuming them FEELS GOOD, which we are willing to pay CASH for.   In other words we subconsciously assign a price to our emotional state and price many products and services we buy NOT for their practical tangible economic value to us but for how they make us FEEL.  So, let’s enter the strange world of quantum economics and pretend that potato chips have ZERO cost associated with them.  They are TOTALLY FREE to everybody in any volume.  Would people consume more or less potato chips than they do now if they were free?  Well of course the answer is MORE and most people can intuitively understand why this would be the case.  But now the strange economics question… assuming all potato chips were free and I introduced new FREE potato chips containing LESS salt and LESS fat than the other free chips, would consumption increase even MORE?  Well… yes… they probably would… but why?

Feeling fat and unhealthy is a NEGATIVE feeling that we associate with eating potato chips.  This FEELING reduces the subconscious value we are willing to pay for potato chips.  Even when the chips are FREE we are paying this negative emotional price for consuming them which reduces consumption for potato chips JUST AS MUCH as increasing the  cash price of chips would accomplish.  Now we are dealing with a form of currency that DOES NOT conform to ordinary economic theory.  It can’t be taxed, it has no costs, inventory, requires no “energy” to manufacture or even rational basis for a price that can be assigned to it and yet it tangibly affects the collective demand and cash value of potato chips.  So what happened to market demand for potato chips with the introduction of lower salt and lower fat varieties?  The emotional cost of buying potato chips dropped precipitously and sales soared.  Pringles potato chip sales, for example, doubled with the introduction of fat-free Pringles.  Sales soared so much that the NET result was much greater consumption of salt and fat than before the “healthy” potato chip was introduced.

This wasn’t the ONLY reason chip sales soared however, another reason was that sales of smaller packages of chips sold in convenience stores at much higher margins also soared because people regarded buying and consuming chips in smaller units as another way to reduce their overall salt and fat consumption from potato chips, while still enjoying them thus increasing the margins and profits on potato chip sales.  So why are Americans Obese?  In addition to being lazy and sedentary, we are fat because of our poor understanding of economics in a relatively free-market economy.  Ironic, isn’t it?

Oatmeal sales is another fascinating example of this phenomena.  We all KNOW that oatmeal is good for our hearts right?  Everyone including the government tells us this is so… however, it’s not exactly true for two reasons.  First, studies found that the reduction in cholesterol associated with eating oatmeal for breakfast was ACTUALLY the result of eating oatmeal INSTEAD of bacon or pancakes.  The oatmeal had NO IMPACT on reducing cholesterol other than being a substitute for a different breakfast good that was higher in calories.  Second, it has been “discovered” that salt and cholesterol levels actually appear to have NO IMPACT on heart health or longevity (most people haven’t gotten that memo yet, even though it is rapidly becoming scientific “consensus”)

http://www.huffingtonpost.com/dr-jonny-bowden/cholesterol-health_b_2035487.html

This is a great example of a “positive” quantum-economic outcome.  People ate LESS “unhealthy” food because they IMAGINED that oatmeal was healthy which validated the belief that oatmeal was responsible for improved health outcomes which further enhanced the myth.  The net result was people eating lower calorie diets while buying more oatmeal.  In this case the people were assigning a higher value to feeling healthy about what they were eating than they were to eating foods that tasted better.

Classical economic thinking works well for describing trade in goods that have practical but NOT infinite value.  For example, survival has nearly infinite value to us, if somebody held a gun to our heads we might be willing to trade almost anything NOT to die, right?  How would you assign an economic price to NOT DYING?  The answer is, it’s worth almost anything you’ve got, which may vary wildly depending on your economic status in life.  Talking about supply and demand really doesn’t make much sense in this example because its meaning breaks down, however when we talk about something like food, which we all need a continuous supply of in order to NOT DIE, our understanding of economic theory begins to make sense.  When many producers work in competition with one another to meet a markets continuous incremental demand for NOT DYING, classical economics emerges.  However, when it comes to intangible needs like NOT BEING MISERABLE, classical economics begins to fail us because, like the need to NOT DIE, we place a nearly infinite value on NOT BEING MISERABLE as well BUT tangible goods and services don’t consistently satisfy this need and can’t be fully described using classical economic methods, YET we do unconsciously assign a price to them that is hidden in all of our purchasing behavior.

We all know the saying “Money can’t buy happiness” but what we really mean is “We don’t know how to value happiness with money” because the things that make us feel good are often intangible and don’t have physical costs associated with them that make classical economic pricing applicable to them.  When I first began to understand these ideas as they applied to selling games online I had a tremendous struggle getting the people around me to understand what I was talking about and why understanding it was important to our business.  I began looking for tangible real-world examples of the kinds of ideas I was trying to convey that would be easier for people to understand… and I found the examples I needed at the supermarket.

It was at the supermarket that I first came to understand and appreciate the concept of “portfolio-pricing”.  The importance of portfolio-pricing emerges from the realization that it is impossible to identify an individual buyer’s value for a good or service without altering it.  This is the quantum-economic analog to Heisenberg’s uncertainty principle, which simplistically observes that it is impossible to measure the location and velocity of a particle simultaneously because there is no way to measure one of the variables without altering the other.  We can, however, measure the average location and velocity of a group of particles to a high degree of precision.  For example the accuracy with which we can measure the location and speed of a thrown rock is very high.  The same is true of figuring out the emotional or irrational value people subconsciously assign to the products they purchase.  It’s impossible to figure this out for an individual person and an individual product because the value is highly relative and changeable, but it can be measured very accurately and captured for a large group of people across a portfolio of products.

Consider the toothpaste aisle in a supermarket.  The shelf-space the toothpaste occupies has a real tangible economic real-estate cost.  The toothpaste product itself is… well… paste… it costs nearly nothing to make and can be stored almost indefinitely.  I’m sure everyone visiting the toothpaste aisle at a supermarket has asked themselves the question… “Why does PASTE come in 50 brands and occupy half an aisle?”  Okay, maybe I’m the only one who thinks about pricing models while shopping but the point is, it does seem kind of odd doesn’t it?  If people really only valued toothpaste based on how effective it was at cleaning their teeth you would think there would be one row of the stuff in one size for .50 cents wouldn’t you?  Why would you buy a small tube of toothpaste if the stuff never goes bad and you know you’re going to be using it your entire life?  Might as well buy it in bulk right?  How do supermarkets justify filling whole rows with the stuff and charging nearly $7 for a small bottle of Hanna Montana tooth paste, or gel toothpaste with sparkly crap in it that you’re just going to spit out?

The answer is portfolio pricing.  The presence of a huge selection of toothpaste varieties increases the collective value of ALL of them in your perception.  Nobody goes to the grocery store SPECIFICALLY to buy just toothpaste, BUT if you happen to be at a supermarket for other purposes, you will almost certainly ALSO purchase your toothpaste there because they have the best selection of it and it’s not worth the investment in energy and time to make a special visit to the “Toothpaste warehouse” just to buy a commodity product.  Let’s enumerate just a few of the intangible “features” that the supermarket uses to sell us sodium bi-carbonate paste for seven bucks.

• Convenience
• Dentist approved
• No-mess bottle
• Family size
• Travel size
• Pretty packaging
• Trusted brand
• Flavor
• Tooth whitening
• Cute branding for kids
• Fresh breath
• Not needing to bend down to reach the cheaper stuff on the bottom shelf

All of these intangible properties of toothpaste have real-value to toothpaste buyers, however it’s impossible to match the optimal toothpaste “feature set” to every buyer, so instead the supermarket creates a “portfolio” of toothpaste features and calculates an optimal portfolio value for the family of products grouped together and presented to a large audience of buyers.  Each buyer SELF Maximizes the amount of money they pay for toothpaste by evaluating the entire portfolio of toothpaste “Features” and deciding which combination of features they value most, thereby justifying a $7 premium for what should otherwise be a .50 cent tube of paste.

I went to so far as to track down a supermarket manager and ask them about how they make decisions about their shelf space.  The manager informed me that they DON’T actually make those decisions, the vast majority of the aisle space is controlled and stocked by major food companies like Kraft and P&G who hire the best and brightest mathematical minds out of top universities to design optimal product portfolios.  These companies then PAY supermarkets rent to allow them to stock their shelves with their product portfolios.  This is a great benefit to the supermarket because of course they lack the extremely advanced math skills and enormous data required to compute the optimal product configurations for their stores to maximize revenue and profitability from a business that survives on only 2%-5% margins.

I realized, of course, that the same concepts applied to selling online games.  Having a portfolio of games that were carefully selected to represent a range of intangible entertainment features that people valued increased the perceived value of all of the games in the service and weirdly increased the amount of traffic AND the amount of money people would spend simultaneously.  Take an individual tube of toothpaste out on the street and ask people how much they are willing to pay for it and you might get offers of $1-$2, place the same tube on a shelf in a matrix of toothpaste products all priced from $2.50 – $8 and magically the same people will choose to pay $5 for some tube of paste.

Having introduced the idea of how to think about pricing intangible goods like “feelings”, it’s interesting to observe that a wide range of highly popular economic beliefs are the result of economic illusions that result when economic reality doesn’t conform to common-sense.  For example, here’s a really interesting and common example of an economic delusion widely held by almost everybody.  Are fuel efficient cars a good thing?  When you shop for a new car is fuel efficiency an important consideration in your choice of car?  Do you believe that the government forcing auto makers to produce fuel efficient cars reduces pollution emissions and reduces wasteful gas consumption?  Most people would nod approvingly at these statements as being obvious… right?  These beliefs are so deeply held and accepted that it’s almost impossible to question them… but let’s transform the question into a seemingly entirely different economic space… Is selling milk at half price a good thing?  If milk were sold for half price, would people drink MORE or LESS of it?  Do you think people will waste more or less milk if it is cheaper?  Does making milk cheaper reduce Peoples demand for milk?  Should the government subsidize milk prices to make it cheaper so people will consume less milk and waste less milk?

Give those questions a second to sink in before instinctively responding that it’s NOT THE SAME THING as making fuel efficient cars, because I’m going to show you that it’s actually EXACTLY the same thing in economic terms.  When I frame selling cheaper milk in the same terms as making transportation cheaper by virtue of needing less fuel to travel the same distance it all suddenly sounds absurd doesn’t it?  This discontinuity in beliefs stems from a classical economic illusion.  GAS is tangible and its price is subject to well understood classical economic forces, TRANSPORTATION however is intangible and subject to the strange pricing vagaries of quantum economics.  Some people buy gas purely for economic purposes such as transporting goods from where they are made to where they will be sold, however a great deal of transportation is purchased for intangible reasons that have little correlation to the price of gas.  Like low-fat potato chips… demand for “recreational” transportation goes UP when transportation is cheaper for any reason.  Making a car that consumes half the fuel of an ordinary car is equivalent to selling gas at half price to that car owner.  The amount of TRANSPORTATION that cars owner will consume at the lower price may not bear any rational correlation to the reduced cost if it is recreational in nature.  Just as people may consume four times as much milk as they did at half price, they may travel four times as much when gas costs them half as much.

There are a great many societal beliefs that people hold very dear that make no sense whatsoever in rational economic terms.  Consider markets for any products that have nearly infinite value to their customers.  These markets generally fall in two broad categories, the general market for NOT DYING and the general market for NOT FEELING MISERABLE.  The market for “criminal enterprises” like drugs, gambling, sex, etc.  can all be said to describe nearly infinite demand markets.  The people who NEED drugs, gambling or sex to NOT FEEL MISERABLE will pay everything they have got to get this need met.  Is there any amount of money or enforcement that can be spent that will prevent such markets from existing?  Probably not.  Weirdly, not only can these markets not be quashed by traditional enforcement means, criminal enforcement actually constitutes a government subsidy for these enterprises.

Our government PAYS farmers money to NOT grow crops and places high tariffs on the import of certain foodstuffs in the theory that protecting our agricultural base is strategically important to the country.  By preventing competition and paying farmers to produce less food we keep food prices higher for everybody and prevent our agricultural base from collapsing under competition from farmers in poorer countries that can produce the same foods much more cheaply.   Whether or not you agree that this is a good practice, we all understand that it achieves the DESIRED result of keeping farmers in business by RAISING and stabilizing the cost of food in the country while reducing competition through tariffs.  As with food subsidy’s, criminalizing demand for goods and services that also have nearly infinite value to their consumer’s results in an economically EQUIVALENT effect to subsidizing the criminal enterprise.  Penalizing and jailing drug dealers and outlawing classical retail distribution channels from selling drugs has the same economic impact as raising tariffs on food imports.  It reduces competition and therefore INCREASES the perceived value and potential margins for people who are willing to take the risk of getting caught.  Paying police officers and DEA agents to PREVENT the sales of drugs is analogous to paying farmers NOT to produce food.  The net result is a thriving, violent, and highly profitable market for drugs where one might not otherwise exist if it were not for the subsidies.  The cost of drugs has no impact on demand for them which is nearly infinite, so criminal enforcement simply increases the profitability of the business for its participants, just as a gas shortage increases the price of gas while its cost remains the same.

In my next installment on this subject, we’ll explore more of the absurdities of modern “Eco-nomic” theory such as why solar panels and windmills are net energy CONSUMERS and why electric cars and “energy efficient” bulbs consume MORE energy than their traditional counterparts.  I will preface this article by saying that I was born in Berkeley California in 1967 and was raised in a log cabin in Alaska for 16 years with no water, electricity or plumbing, so if you think you know anything about being “environmentally concerned” you haven’t met MY family.  Save your ignorant liberal outrage for somebody who doesn’t know any better. 

The post Strange Economics appeared first on The Saint.

Now that Ballmer is retiring from Microsoft everybody is piling on him for all manner of perceived failings as CEO.  Most recently for the toxic culture that the Microsoft review system is said to have engendered within the company.

http://www.slate.com/blogs/future_tense/2013/08/23/stack_ranking_steve_ballmer_s_employee_evaluation_system_and_microsoft_s.html

Now I hate to do this because ordinarily I take great glee in razzing Microsoft for its blunders but in this case, I have to take Ballmer’s side of the argument.  Criticizing Microsoft is fun, but having actually been CEO of several technology companies, I’ve got to  say I’ve developed some sympathy for Ballmer’s position over the years.   One of the biggest challenges I’ve always experienced making big technology is that you’re only as good as your tools and your tools are people.  When I have great people working for me… I become a great CEO.  When I have less-than-great people working for me… I’m a less-than-great CEO. Which very quickly makes you realize, as a technology company CEO,  your primary job is recruiting and retention.  I don’t think that a lot of people would dispute that Microsoft has managed to recruit and retain a lot of top notch talent over the years.  It’s always been one of Microsoft’s great strengths.

It’s also the case that unlike almost any other industry, software development can have a very extreme productivity curve.  There are engineers out there who can out code 5-20 ordinary skilled programmers.  There are one in a thousand engineers who can out-innovate nearly all ordinary skilled programmers.  If you wanted to design a compensation system that rewarded programmers in direct proportion to their contributions to a products success the contribution curve would generally show that 98% of your people were contributing between -1X to 3X units of productivity relative to their peers and the remaining 2% of employees where contributing 3-20 units.  In other words the top 2% of your team might be contributing 20%-40% of a successful products value.  In traditional organizations top performers were promoted to management in order to justify their higher compensation but in a technology company converting a great engineer into a bad manager is the last thing you want to do.  You need that engineer to stay exactly where he is in the organization but compensate him “fairly” for his productivity.  That means you need a review system that can pay one engineer 5X-20X what a peer sitting next to him in the same cube is earning.

On such a review scale the majority 99% of your employees are going to sit in a very tight cluster.  Most of them will never have the potential to be 10X contributors and a few are active productivity inhibitors that need to be removed from the organization if they remain that way.

Microsoft’s review system was designed very early on to try to capture these observations about engineering performance.  The fact that the Microsoft’s TRIES to pay exceptional people exceptionally is a great thing!  Most companies are content to pay all of their employees a flat market salary that sits somewhere near the market average for their position and experience + or – maybe 25%.  Microsoft “solves” this problem in a mathematically “obvious” way.  The company generates profits which, combined with market pricing for talent is used to set a “budget” for review time.  That budget is fixed.  It doesn’t matter how many super-talented geniuses worked on a product if the product didn’t perform exceptionally… the value of their productivity may still be low despite their best intentions and hard work.  That fixed “review” budget has to be distributed among those team members as closely as possible to each member’s contribution to the products success.  On a team of 100 people 2 of them may have written 20% of the used code and solved design or performance problems in an innovative way that nobody else could have discovered.  A few of the team members may have worked 80 hour weeks on code that all had to be thrown away in the end because it wasn’t used in the final product.  How do you distribute raises fairly?

Under the Microsoft review system the team’s manager would stack rank the team based on a large number of subjective variables.  The purpose of the stack rank is to force the manager to honestly assess the value of each team member to their organization.  A stack rank prevents a manager from being lazy by reviewing all of his team members to be equally valuable.  That stack rank is then used to distribute review scores and compensation along a bell curve proportionate to each team member’s position in the stack.  Since the manager has to deliver the reviews, he had better be prepared to defend them to his employees.   A few top performers get a lot, a few bottom performers get “the shaft”.  If you want a promotion at Microsoft, you need to review near the top of your stack several times.  If you review at the bottom of your stack several times you will be given a certain amount of time to find a new job in a different part of the organization… or be terminated.

This review system is the source of endless whining, chaffing and grieving at Microsoft.  Almost nobody likes it.  It doesn’t try to coddle emotionally fragile people and make them feel good about their mediocre contributions to their team.  There are no easy places to hide for the lazy and incompetent.  Managers are forced to be clear and accountable to their teams about each members relative value… which most people don’t want to hear if they are not #1.  Top performers, who should be happy, often feel guilty that they are making so much more than their less valued friends and team mates.  There is social pressure for them to commiserate with their less rewarded peers.  It is said that the system results in heavy internal politics and competition, that people on the same team are incentivized to back-stab one another, that managers will deliberately seed their teams with mediocre talent so they can pay their top people and close friends more generously and that Microsoft lost top talent because of it.  Etc.. etc..  Although all of this is true to some greater or lesser degree, I don’t believe that any of it is necessarily a BAD thing.  Here’s why…

How to “Prove” your review was “unfair”?
Quit and get a better job.

I know of very few people who have an accurate perception of their own value to an organization.  Do useless incompetent idiots KNOW they are useless incompetent idiots?  Isn’t one of the hallmarks of the most useless incompetent idiots, that they zealously believe they are top performers?  Do all exceptional people KNOW they are exceptional?  The Microsoft review system is a very clever economic structure for correctly valuing people over time regardless of their imagined value… which is almost always greater than their real value.  There is a simple way for anybody unhappy with their Microsoft review to PROVE that they are incorrectly valued.  They can quit and take a higher paying job at another company.  Anybody who remains at Microsoft after a dissatisfactory review and bitches endlessly about it, is just WRONG about their actual value… clearly nobody else in the market is willing to pay more to hire them.  Microsoft measures its churn rate to determine how FAIR its compensation system really is.  If Microsoft’s overall churn rate is too high then it can INCREASE its review budgets to bring it’s aggregate churn rate into a desired range.

Microsoft WANTS to churn out weak employees.  If a manager is deliberately seeding his team with weak employees in order to pay his top contributors MORE, then Microsoft’s system will force that manager to automatically churn them out, forcing the manager to spend more time recruiting WEAK talent from other internal groups.  Thus, there is even an economy and some job security for bottom performers.  If you believe that this is a widespread practice at Microsoft then imagine how unproductive you must be to not be able to find another job in the organization when you have been forced out of your current one as a result of constantly getting reviewed at the bottom of the stack?

Does the system really incentivize backstabbing within a team?  That would tend to assume that the team manager is UNAWARE of this incentive AND that the team is so small that backstabbing a few members has a chance of boosting an employee’s stack rank into the vaunted top 2% stratosphere… otherwise backstabbing, which takes time and effort, would not be a particularly advantageous activity unless the team manager actively rewarded it.  Since the overall size of the compensation budget is proportionate to the company’s actual performance, engaging in backstabbing would have the collective effect of reducing the size of everybody’s compensation by making the company less productive.

In short the underlying economic incentive ideas behind Microsoft’s review system are BRILLIANT and provide inherent resistance to fraud and gamesmanship.  That does not mean that such a brilliant system can’t be poorly administered or that people will LIKE being judged and compensated fairly.  If a manager rewards gamesmanship or tries to curry personal favor with disappointed employees by blaming the system for their review then the system will obviously be less effective.  If employees with an inaccurate view of their “worth” believe that getting an accurate assessment of their value to the organization is equivalent to being told they suck every review period then it would also cause an understandable morale problem… among the mediocre… which they can fix by improving their performance by accepting that they can do better or by proving the review wrong by quitting and taking a higher paying job elsewhere.  People who remain in the same job and remain disgruntled about their review are just proving that they have, apparently, been assessed accurately… Moreover, that being delusional about their real value and developing a poor attitude when challenged to perform better, are two areas they could improve on.

Now the California school of millennial management thought on this subject is that it is more important to make employees feel happy about their jobs and peer relationships than it is to treat them fairly.  We all know that happy employees are more productive don’t we?  Also because the market for engineers is so competitive, unhappy, less productive employees can always quit and get another job elsewhere, sometimes with a raise simply because there is such a scarcity of talent.  Better to try to keep everyone happy and forgo the whole systematic measurement of productivity and fair compensation for the sake of institutional peace?

Do useless incompetent idiots KNOW they are useless incompetent idiots?

Bill Gates and Steve Ballmer however would tell you that being surrounded by mediocre talent they have to carry and not being recognized for their contributions is precisely what guarantees that the top 2% performers will quit and go elsewhere.  Mediocre people can always be replaced.  The most valuable employees are hungry, aggressive and embrace the challenge of climbing to the top of a stack ranking rather than making excuses for their shortcomings and developing attitude problems when they don’t get their way.  People who consistently sit at the top of their stack ranking will eventually get promoted into a different stack (with higher standards) thus making room for their former peers to move up.  Bill and Steve would say that keeping the best and brightest people challenged was more important to retaining them than keeping everybody “happy”.

Of the many failings that Ballmer can be ascribed, Microsoft’s review system is hardly one of them.  I believe that he and Gates knew exactly what they were doing when they designed it and that it was responsible from a very early stage for cultivating a culture of excellence among Microsoft’s BEST performers and a culture of systematic and rationale productivity measurement.  I believe that Microsoft’s struggles under Ballmer are the result of too much success and complexity for anybody to manage at that scale, which is hardly an indictment of his tenure as CEO.

The post Steve Ballmer and the Microsoft Review appeared first on The Saint.

I am fortunate to be one of the few people alive to have had access to such a phenomenal body of gaming data and to be in possession of the mathematical acumen to be able to construct advanced models that appear to accurately describe the complete life-cycle of all known online game dynamics.  My motivation for undertaking this challenge was simple, it is extremely difficult to analyze the properties of online games because it is very hard to run properly controlled studies on a games behavior in the real world.  It is nearly impossible to model social virality in gaming while keeping cohorts or samples of audience completely isolated from one another.  I needed an accurate model to simulate game virality so that I could run virtual experiments on hypothetical games without needing to control a vast game publishing network, massive data warehouse’s and very sensitive experimental framework in order to gain insight into the fascinating and exotic monetization, consumption and marketing properties of online games.  I believe that the EUREKA formula is a significant mathematical achievement but because of its complexity and the difficulties associated with testing it, it may be a long time before it is widely recognized as a powerful tool for building successful online games.

For the purpose of this discussion, I’m going to use the EUREKA formula in a highly simplified way to try to illustrate why artificially driving traffic to a Free-To-Play game will often have very little positive impact on the games overall life-time revenue potential.

To begin with, let’s define the widely believed assumption that we are going to examine:

Proposition:  Buying or otherwise driving click traffic to a Free-To-Play game will generally increase its success.

Sounds obvious and reasonable doesn’t it?  It’s certainly understandable that most people in the industry strongly believe this proposition.  How would we go about testing this proposition scientifically in the real world?  Ideally we would take a sample of random online Free-To-Play games.  We would give them equal presentation to random audience samples and watch how they monetized with no marketing influence.  These would be our “control” tests.  Next we would buy an equal number of randomized traffic clicks to each game and measure their monetization over time in the presence of marketing promotion.  We would then compare each games life time revenue from organic traffic acquisition versus the same game with pushed traffic to see which game performed better monetarily and observe any other interesting differences about how the games behaved under different marketing conditions.  In practice, this experiment is very difficult to run because there is no simple way to get quality controlled audience samples that interact virally within the sample but not across samples at the same time.  This is a great example of a situation in which a good mathematical model can help us visualize what might happen if we could run this experiment with rigorous scientific controls.

To conduct this experiment we’re going to setup the EUREKA formula in a simplified way so as not to confuse the discussion with an elaborate explanation on the meaning and interactions between the many parameters that comprise the EUREKA formula.  A few simple assumptions can give us a clear NEW intuition for how Free-To-Play games actually behave without needing to rigorously tune the model parameters to capture all of the properties of an actual game.

The most current version of the EUREKA formula is publicly available on my Blog as a live Mathematica CDF file that anybody with the Mathematica web plugin can interact with.

http://www.alexstjohn.com/SVD4_1/SVD4_1.html

Here are the simple steps to reproduce this experiment from the live EUREKA model.

1)      Set the variable iExposed to 1.  My online EUREKA model defaults to a sample potential audience of 1000.  Setting iExposed to 1 means that of the entire available reachable online audience for a game (default 1000) only 1 person has initially been exposed to it.

2)      Under “Marketing Paramaters” set Susceptible–>Exposed to 1.  This is the number of clicks from the unexposed audience that you will buy for the game per day.  In this example the game starts with 1 exposed player and adds 1 per day for 1000 days.

*Note that the default model automatically sets the Exposed–>Engaged parameter to .1 which means that on average 10% of the Exposed  players will become paying Engaged players every day.

**Note that the default model automatically sets the Engaged–>Immune parameter to .01 which means that on average 1% of the Engaged paying players drops out of the game forever every day.

***$/DAU is automatically set to $1, again to give us a simplified relative view of how much revenue our hypothetical games will generate over time given different marketing and audience behavior parameters.

When we’re done the model should look like this;

The most important line on the graph is the red line.  It shows the active Engaged paying players in the game on any given day.  The blue line represents the unexposed players that have never heard of the game on any given day and the black line represents the players who have been exposed to the game and dropped out never to return.  When the “Immune” audience reaches 1000, the games life cycle is over.  Note that the game legend shows a figure for “Total Potential Revenue” of $58,753.  This is the games total revenue generation at $1/DAU over the 1000 day sample period.  Basically it is the area under the red curve times the $/DAU.

This graph represents a very simplified model of an online game.  The game has ZERO ability to market itself.  Players who play it have ZERO percent likelihood of recommending it to a friend.  The only force driving traffic to this game is purchased clicks.  To verify this, try setting the Susceptible–>Exposed Parameter to ZERO and the games monetization and traffic will vanish to nothing.  Without artificial traffic pumped into it, this game won’t make a dime.

This scenario isn’t very likely however, even the worst games have some viral potential.  To capture this, set the viral parameter Engaged to .1.  This parameter simulates the idea that every paying Engaged player has a 10% chance of inviting another player to join on any day that they are Engaged.  New players become “Exposed” and flow from Exposed to Engaged at a rate of 10%/Day in this scenario.  We know that in reality not ALL exposed players will become Engaged players in a real-game which is what other parameters in the model are for but these details aren’t important to this demonstration.

In this scenario our virtual game with NO artificial traffic will organically generate life time revenue of $99,997, with peak audience engagement occurring roughly 175 days into the games life-cycle.   Now we are set to conduct our virtual experiment in pushing artificial traffic to a Free-To-Play game.  We simply take the model that includes some virality and push some traffic to it by changing the Market parameter Susceptible–>Exposed.  Try setting it to 10 purchased clicks a day.  What happens to the games life time revenue?

After buying 1000 days X 10 clicks/day = 10,000 clicks the game generates a total life time revenue of… $99,993… five dollars less revenue than the same game with no artificial traffic.  What has changed however is that the games revenue peak moved forward in time to roughly 80 days.  So according to The Saints BRILLIANT EUREKA model, a game that has traffic pushed to it can make less money than a game that has none… now either I must be an idiot who can’t model virality correctly… a distinct possibility… or there is something very deep and important to learn about how Free-To-Play games actually monetize.  Now if you thought I was an idiot you probably wouldn’t read further so let’s proceed on the assumption that my math isn’t wildly out of whack.  What happened?

If you look closely at the graph it’s kind of obvious.  There is a limit to the size of every market for every game.  EUREKA arbitrarily defaults to 1000 but the fact is that there are not an infinite number of potential players for every game.  As players are exposed to a game and make a decision about whether or not to engage with it, they are consumed such that new available players become less common to recruit until the game has run its course and everybody who would possibly play it has eventually been exposed to it.  When you push traffic to a Free-To-Play game all you do is accelerate the consumption of un-exposed audience which the game then churns through faster.  If the game has any virality at all, virality is also amplified further accelerating the consumption of unexposed audience.  But these parameters have NO impact on the games monetization parameters.  If these parameters don’t change that game will always extract about the same amount of revenue from its potential audience.  Pushing traffic at the game will just accelerate the rate at which the game will capture all of its potential revenue but NOT increase the games total revenue potential.

Since pushing clicks to a game costs money and virality is free, it always makes sense to optimize a Free-To-Play game for virality.  A highly viral game doesn’t need traffic pushed to it to reach its monetary potential while a Free-To-Play game lacking virality will be very expensive to promote and make no MORE money than it would have had it been slightly viral.

If you actually want to make MORE money from a Free-To-Play game, marketing is not the way to do it.  Try making small changes to the Engaged–>Immune parameter… better named the Churn Rate parameter and see what that does to your games Total Revenue Potential.

In summary, if you want to accelerate revenue you were going to make anyway from a GOOD Free-To-Play game, go ahead and burn cash driving clicks to it, just realize that you are probably not creating any significant found revenue.  If you want to waste money promoting a BAD Free-To-Play game, drive traffic to a game that NOBODY wants to tell their friends to play, odds are that you’ll end up spending more on traffic than the game generated in revenue because the GOOD games in a network will drive up the cost of buying clicks above the value that a non-viral game will monetize at.  Remember that a viral games generates compound $/DAU because in addition to monetizing it’s users it also recruits new users who will also pay to play the game.  When it comes to the economics of Free-To-Play games our common sense intuition about how they will monetize is often WRONG, which is why I cooked up EUREKA to help everyone understand how to think about them correctly.

The post Futile Marketing appeared first on The Saint.

“I told you so…”

Okay, it’s out of my system.  Now by way of contrast, have you ever heard of a controversy over World Of Warcraft’s inability to share access to the game with friends?  The inability to resell boxed WOW copies?  Their need for an always-on-Internet connection?  Anybody heard this controversy over Apples App market or iTunes?  How about creepy privacy concerns about a network accessible camera on nearly every mobile device in creation?  No?  So why would anybody have a problem with the XBOX ONE being THE SAME WAY?  Isn’t always on, constant connectivity and personalization of all media sales the norm on the Internet everywhere but on the console?

The problem is that Microsoft tried to bridge a market transition that can’t be bridged.  Instead of giving up on the dying boxed retail centric world, they thought they could “extend” it for one more generation with a “clever” blending of online connectivity and retail distribution resulting in confusion and anger from all quarters.  The age of monolithic narrative $60 games is over, fighting it just makes the transition messier.  Hence my earlier advice that they should have simply made a mobile console with a pure online business model and stretched the lifespan of the existing XBOX with more RAM a faster clock and some software updates.  If they had done that they wouldn’t have pissed off their established gamers by launching a TV media box with restricted gaming capabilities, last years PC graphics capabilities and CALLING it a next generation console.  Microsoft’s huge mistake was trying to trick the market into supporting their NEW initiative to dominate the living room with a media center by disguising it as a next generation game console.

The subject of the consumer rage over sharing and reselling games is a fascinating one from an economic point of view because it is illustrative of the problems with the retail business model for boxed games and WHY it is dying.  What angry gamers are saying (in economic terms) is that when they buy a boxed console game for $60 they are paying maybe $40 for their own enjoyment of the game, $5 for the social status of having it to share with their friends and plan to get a $15 discount on the game by reselling it when they are done playing it.  To them the game itself is worth $40.  Note that they DO NOT get angry with GameStop for taking a 30%-100% cut of their games resale value because GameStop is viewed as the market maker that enables them to resell their game in the first place.

It’s so bad that EVEN the Japanese are looking cool making fun of Microsoft

Traditional boxed game publishers foolishly think that the discount dollars and social status dollars consumers associate with their games should belong to them and imagine they will make MORE money if they can block the resale of their games.  Economically speaking all they will discover is that their games are worth LESS money than they thought and by trying to forcibly capture those dollars they will push their gaming audiences to other platforms.  They will also discover the hard way that the sharing of games had marketing value for them that will be destroyed if they prevent it, thereby INCREASING the cost of marketing new games because they killed an important viral word-of-mouth marketing vehicle for their content that has some monetary BENEFIT to them.  In a pure online world game publishers can actually measure and PRICE the value of social sharing and include that value in their games business models in the form of free trial play.  In other words what you are witnessing is a cascade of economic mistakes that will lead to the end of the boxed retail game business leaving only the pure online business which has elegant and established mechanisms for correctly pricing the value of games and social virality.  There is no re-sale market for online games because they have no physical manufacturing and distribution costs to recoup so the re-sale value of an online game is zero, it costs nothing to copy and distribute.  The Internet is a beautiful thing for gaming.

Now If Microsoft were SMART they would sacrifice the retail channels interests in favor of the consumers and the game publishers because it is the retail channel that is dying.  How much consumer rage would there be if Microsoft enabled an online market for XBOX ONE gamers to auction their used games to one another and took a cut of all transactions which they shared with the publishers?   Not much…  What if Microsoft had allowed people to share games freely and for the “Shared” players to be offered an online discount to buy the game online and have it mailed to them?  The discount would come out of the retail channels pocket not the publishers.  Now the publisher benefits from game sharing and can directly correlate game sharing with viral sales via… THE INTERNET!  Isn’t everybody happier in the world where the retail channel gets screwed instead of the consumer and the game publisher?

But that has been my point all along… Consoles are dead because gaming business models have evolved beyond the need for a retail channel and the classic console business model always relied on the retail channels participation in game sales to achieve distribution for the console itself.  Microsoft didn’t get that memo and tried to make a console that compromised the interests of the consumer to prop up the dying retail channels interest in distributing consoles for them and appease the remaining misguided publishers who are still in the console game business mostly because they could not make the transition to online gaming and online business models.  The same economic ignorance that prevents a console game company like EA from becoming successful online after decades of effort is what motivates them to mis-understand how their retail business should evolve and benefit positively from game sharing.

The consumer rage you are seeing over the XBOX ONE launch is really the market beginning to recognize that the era of console gaming has passed and that purely electronic distribution of games supported my microcurrency based economics is the only game business model that makes sense in this era.  Apple got there first and Sony and Microsoft are regrettably deeply invested in an obsolete vision of the console that doesn’t work for a generation of gamers that grew up on free (self-marketing), cross-platform, mobile games with mixed advertising and microcurrency based economies.  Microsoft should have named the XBOX ONE the XBOX RETRO.

The post XBOX ONE Sharing the fun! appeared first on The Saint.

By “ideal” market I mean that the interests of all of the various participating parties are balanced and “fair” in the purest capitalist sense.  By “capitalist” sense, I mean that all participants in the market are rewarded in direct proportion to the paying consumer’s perception of their value contribution to the market.  An “ideal” market defined in this fashion is also an optimally efficient market, meaning that the markets total size is maximized because there are no artificial biases in the market that favor one participant at the expense of another.  Most real world markets are biased in favor of  the channel over others which generally results in the channel making a greater profit at the expense of the markets overall potential size.  Facebook and Apple are both examples of biased markets that sacrifice scale and efficiency for bigger profits to Apple and Facebook.

Both Apple and Facebook charge a 30% sales tax on all commerce revenues and dictate that all market participants rely solely on their commerce platforms.  The result of course is that a certain body of games that some people may want to consume cannot be profitable on these channels with a 30% tax imposed on their revenues.  Both the channels (Facebook and Apple) lose potential market size in favor of extracting higher profits from the smaller market of content that can be profitable with a 30% tax imposed on all of their commerce revenues.  In a large marketplace such as these companies operate it might be fair to observe that the 30% commerce tax helps eliminate bad content from the channel, which is true, BUT it also prevents innovative or new content from being discovered because the risk of creating games that are innovative is much greater given the increased cost of recovering the developers investment in the presence of a 30% tax on all revenues.

To properly analyze how to create an “ideal” game publishing market let’s start by defining the interests of each of the markets various participants.

Consumer:

The consumer has a limited amount of time available to spend consuming entertainment and presumably a limited budget.  The consumer wants to maximize the quality and flexibility of their limited entertainment time at the lowest price possible.

Channel:

The “Channel” generally represents the “shelf-space” provider for the content as well as the “cash registers”.  In an online world a channel can be more abstract but most people understand that Apple devices and Facebook are good examples of online channels that fit this descriptioin.  They provide virtual shelf space for online games as well as the commerce vehicle for consumers to purchase content.  The Channel’s interest is to maximize the revenue and profitability of their limited shelf space.

Developer:

Developers create the content that consumers hopefully want to consume.  Their goal is to minimize the cost or initial risk of their content investment and of course maximize their return.

Advertiser:

Advertisers are third parties who want to monetize a gaming audience that popular content has attracted to a channel.  Online an advertiser can generally be thought of as an alternative to a commerce transaction, which means that in order for an advertisement to be worth showing the advertiser must be willing to pay more to show the ad than a consumer is willing to pay not to see it.

The relationship between advertising and commerce is extremely important in constructing an “ideal” business model for online games because advertising is generally sold in an auction, which as most readers will know is the most efficient way (known) to establish a market price for a good or service.  Advertising also has the property that it can be transformed into a commerce equivalent price by the following equation;

 CPM value of game content = The probability of the user engaging in a commerce transaction      X     The probable value of the commerce transaction    X    1000

*Note that for this equation to have practical application the games that adopt it must be divisible by units of content value that fit in a $.50-$200CPM price range.  This is true of MOST microcurrency based social games

Lastly, in most cases, the most valuable potential bidder for advertising space in a game is…. another game… which means that an advertising auction provides an efficient mechanism for many games participating in a marketplace to compete for shelf space by buying advertising from one another.

What does this observation about the value of advertising mean for creating an “ideal” game publishing market?  It means that if Apple and Facebook wanted to maximize the size of their game markets and participate “fairly” in the share of revenue their channels are responsible for creating they would charge as little as possible for commerce transactions and instead operate the market for advertising in their channels keeping only 100% of the revenue from non-gaming advertisers.  Economically speaking this is the portion of the revenue that corresponds directly to the market value of their shelf space + commerce platform independently of the value of the content ON the shelf space.  Since non-gaming advertisers are effectively bidding for the right to put content on the shelves that the consumers are explicitly NOT looking for they must bid the maximum value of the space to get a presence on it since presumably no consumer will pay the channel to buy the product being advertised.  (Microeconomic speak for “this is a fair way to determine the channels cut of game revenues”)

Why does this model produce an “ideal” publishing market and why should Apple or Facebook favor it over a business model that currently gives them a disproportionate share of the revenue generated by their channels?  Because the wonderful thing about a free online game market is that ANY inefficiency in one channels business model creates opportunities for competitors to capture a share of the market for themselves.  Theoretically if anybody created a completely efficient game publishing market, all other competitors would eventually die off.  In effect Apple and Facebook are making higher margins for themselves on MUCH smaller markets as a result of their business decision to operate biased markets.  The result is short term higher margins for themselves but less content and more competition for their audiences.  Increased competition not only means smaller audiences for their channels but also lower overall prices because consumers have alternatives they can go to for games if they feel that Apple or Facebook’s 30% tax on all revenue makes the games in their channels too expensive for them.  In other words, the overall online game market is smaller and everybody makes less money when the companies who control the leading game channels bias the markets they operate in their own favor.

Now let’s examine how an “ideal” game publishing market might operate.  In an “ideal” game market the consumer gets all the content they have time to consume in exchange for as much money as they are willing/able to spend for that content.  In an “ideal” market the channel profits in direct proportion to the actual value their channel and commerce vehicle provides to the content.  In an “ideal” market game developers profit in direct proportion to the value consumers place on the content they create and in an “ideal” market advertiser’s will pay as much money to advertise their goods and services to a channels “free” players as the paying players pay overall for access to premium non-advertising supported content.  In other words if you visualize a scale of justice, the total dollars spent by advertiser’s to sponsor free content to non-payers should balance the total dollars spent by consumers paying for premium non-sponsored content even if the ratio of paying to free consumers is 1:100.

In such an “idealized” market how much money will everybody tend to make?

The Channel will keep 100% of all advertising revenue that is NOT other games in the channel buying advertising.  What this statement means is that if Nike or Coke wants to sponsor free gameplay in a particular game, they will need to pay, on a CPM basis, as much money as it costs to replace the commerce revenue the game might otherwise have generated selling itself.  Since most games only monetize 1-3% of their audiences that means that 97%-99% of available gameplay is sponsorable by advertising.  Clearly there will be some in-game content that may be so valuable that it is too expensive for an advertiser to sponsor for free and that content will only be available for consumers via commerce purchase.

Those of you who have not read my previous articles on quantum economics may perceive that it is impossible to mix advertising and commerce because the availability of free sponsored play will cannibalize commerce revenues out of existence.  This is true in the physical retail world but as my previous articles on this subject demonstrate is a solvable problem in online commerce because the channel frequently has enough data about consumer behavior to predict algorithmically with very high precision which users are potential commerce buyers and WHEN they are likely to make a purchase.

The reason the total dollars earned via advertising and the total dollars generated via commerce should tend to balance each other is because in an “ideal” market the consumer is effectively bidding AGAINST advertiser’s for the value of their own entertainment.  In other words, sometimes the content is more valuable to the consumer without advertising than it is to any potential sponsor, which results in a commerce transaction, in MOST other cases the value of advertising to the consumer exceeds the consumers’ willingness to pay NOT to see advertising and an ad is shown.  In this respect you can think of ALL advertiser’s combined functioning as one unified bidder in an auction against the consumer who is bidding on their own behalf.  Clearly in a two person auction, one party will never outbid themselves so on a large scale advertising dollars will tend to balance evenly against consumer commerce dollars.

This idealized scenario isn’t always practical in the real world because there are many common situations that create inefficiencies in this kind of asymmetrical auction between advertiser and consumer.  For example the game designer may not have designed the game in question with small enough units of value to satisfy the needs of the Commerce to Advertising CPM transformation.  It would be impossible to get an effective auction going for $60 copies of Halo for example because there are few if any advertiser’s willing or able to buy $60*1000 = $6000CPM ad units.  (This was the whole reason for the failure of the foolish in-game advertising craze led by Massive a few years ago.  It was a stupid idea to try to stick advertising in games that consumers had already purchased)  On the other hand, the game may have such a low monetizable value that nobody would carry out a commerce transaction to buy a pennies worth of play, as is typical of many free flash games.

As a result of there being an extremely wide range of “values” that people assign to online games between free ad supportable content and premium commerce only content AND most companies poor understanding of how to hybridize advertising and commerce correctly, most online publishing channels are highly inefficient and capture only a small portion of their audiences available play time or potential revenue.

Returning to the original question of how much each market participant will tend to make in an “ideal” game market; Consider that ad dollars should equal commerce dollars and that the most valuable ad dollars will tend to come from other games AND that I have advocated that the channel really only deserves the portion of the ad dollars that DO NOT come from other games promoting themselves.  Ad dollars will tend to be 50% of the market and in my experience running WildTangent using a related model, 40%-50% of advertising revenue came from other games which would leave 25%-30% of the channels revenue to the channel provider (Facebook and Apple in this example).  Now those of you reading this article might observe that Facebook and Apple are already getting 30% of the revenue via their commerce tax and I just proposed that they get 25%-30% of the revenue so what’s the difference?  The difference is where the 30% of the revenue comes from.  In their current model it is taken uniformly from all games regardless of their value contribution to the service.  In my model the revenue is taken mostly from games that you would never find on their service today because they are excluded.  Abstractly speaking it’s 30% of the overall revenue but all FOUND money resulting from the change in business model!  Very little of it would have come from most of the kinds of games presently found in their services, because their economics ONLY work for premium commerce based content.

70%-75% of the revenue would tend to go to the game developers.  However the distribution of that revenue would be very interesting because;

In general a small number of games are responsible for the majority of revenue in most online game channels.  The ratio approaches the classic 80:20 rule.  20% of the games make 80% of the cash.  Why does this consistently tend to be the case?  Simple.  After years of studying top performing online games versus weaker performing titles at WildTangent (reference earlier quantum economics articles to see some of that data) I found that there are three ways that an online game can perform well.  It can be very good at engaging an audience but poor at monetizing itself.  It can be very good at monetizing itself but poor at engaging an audience and lastly a game can be GOOD at doing both which makes it a hit.  The number of games that I found in my channel that were actually “BAD” games that nobody want to play OR pay for was very small.  The problem with most “less successful” games was that they were simply inefficient at maximizing engagement and monetization.  Most games traded one for the other and if they got the ratio wrong, their game was a lot less successful than a game that had gotten the balance right.  In other words the major difference between a hit game and a mediocre game was a series of content decisions in the game design that collectively represented a poor balance in the games ability to market and upsell itself.  It was also common for there to be too many of the same kind of game in the channel competing with each other.

This observation is important to designing an “ideal” market for online games because what it means is that games that are great at engaging an audience but poor at monetizing themselves are still a value to the channel, they “attract” audience to the store.  They are ideal advertising targets for high monetization games with poor engagement properties.  Thus games that monetize well will support games that engage well by buying traffic from them in the form of advertising!  Hit games will buy traffic from everybody and raise the CPM value of advertising across the channel thereby increasing the price at which non-gaming advertisers will bid to sponsor free play which in turn will generate more revenue for the channel itself.  Hopefully by now the “elegance” of this idealized marketplace is becoming clear.  We all know that hit games create the value for a gaming channel… for example the main reason that most people initially bought a $400 XBOX was to play Halo.  Thus a hit game shouldn’t have to “pay” for the privilege of being in a channel because it is the HIT content that is responsible for the channels success in the first place.  A game which is great at engagement but poor at monetization is a great source of potential advertising revenue for the channel and the game developer.  If the game developer keeps the portion of ad revenue that is generated just by other games advertising for their players, they will generally get roughly 50% of the ad revenue generated by their content while the channel pockets the other 50% in non-gaming ad dollars for themselves.  Premium games that are weak at self-marketing can buy traffic from other games in proportion to their monetization value.  Since the game developer is in control of their ad buys they can decide what percentage of their revenue they want to share with other game developers to acquire traffic.  If their game is “BAD” from a purely market point of view, then they will not be able to profitably buy traffic.

If I were to start an online publisher today or if I were Apple or Facebook, this is the model I would adopt in favor of my current model in order to increase my share of the game market.  Although they would be sacrificing some margin today, the result would be a much larger market for them over time because a much broader range of content would become profitable in their channels.

If you think these ideas sound too theoretical in nature, keep in mind that I successfully employed a more rudimentary version of this model at WildTangent which quickly became the #1 largest online game site in the US when the first Ad/Commerce hybrid business model was deployed in 2007.  Hi5.com became the 6^th largest online game network in the world in six months when I deployed another variation on this model there.  It’s not just economic theory for me anymore, these ideas have been tried in the real world on a huge scale successfully on at least two occasions and they are rooted in sound economic theory.

Before I conclude this article, it’s worth revisiting the subject of the channel provider’s investment in providing the commerce solution for their channel.  On one hand providing the commerce solution for a channel can create great efficiency of scale and ease of billing which has real value to the game developer and consumer.  On the other hand, dominating the commerce solution can stifle innovation in commerce models and monetization for games which is often unfortunate.  So the “value” of channels like Apple or Facebook controlling the commerce models in their channels can be questionable if they are not continuously investing in improving the efficiency and flexibility of their payment models to maximize their value to the developers and consumer.  Placing a heavy fixed tax on all commerce transactions in their channel certainly imposes a huge negative value on their solutions.  From an economic point of view, it’s a tremendous mistake indicating a lack of sophistication in understanding the economics of the businesses they are operating because they are discouraging premium content developers from entering their channel because premium content (hit games) don’t need their channel to attract players and they are discouraging engaging content developers because they can’t profit from making popular games with low commerce value.   Instead of embracing the value of enabling a rich inter-application advertising market between apps, channels like Apple and Facebook regard them as competitors to their commerce businesses and try to suppress them.  In short my instinct is to strongly suggest that these companies would be more successful over the long haul if they minimized their commerce tax in favor of providing a highly liquid inter-application advertising marketplace.

Given that Apple and Facebook are both publicly traded companies with a significant revenue base tangled up in their entrenched business models for gaming, they may not be in a position to be very innovative or competitive in this space… however I would also observe that there are all new online publishing channels entering the market this year in the form of next generation consoles from Sony and Microsoft that are NOT necessarily deeply committed to any particular online business model yet and who NEED to catch up with Apple and Facebook in online gaming by perhaps taking a more developer and consumer friendly approach to the business models they introduce for their new online services.  I would observe that if they wanted to gain a large base of developers and new audiences, it would be in their interest to consider offering a more “ideal” business model to compete with the ones that presently dominate the market.  They desirable property of an “ideal” game market is that it maximizes revenue with zero drag on audience growth and content acquisition.

The post Creating an “Ideal” Game Publishing Market appeared first on The Saint.

When I was first struggling with these ideas to design a better business model for WildTangent I ran across a puzzle that gave me the insight I needed to solve the problem.  I’ll share that puzzle here as an introductory lesson in what I now call Quantum Pricing models.

You are given 10 red balls and 10 white balls and two buckets.  How would you distribute the balls between the two buckets such that if you were blindfolded and asked to randomly reach into a bucket and randomly select a ball from the bucket you would have the maximum probability of picking a red ball?

Obviously if you put 10 white balls into one bucket and 10 red balls in the other your odds of picking a red ball would be 50%.  Interestingly the result would be the same if you put 5 red balls and 5 white balls in each bucket.  The puzzle, however, does not require that you put exactly 10 balls in each bucket…  I’ll include the solution at the end of the blog, but take time to think about it.  The answer to this puzzle is also the answer to the question of how it is possible to nearly extract the maximum value of a game from an audience without knowing each individual in the group’s optimal price point.

To capture most of an individual’s optimal value we need a probability function that enables us to guess what that optimal value is very accurately without measuring it directly.  For example, if we know how to identify when somebody is playing as though they are hooked on a game AND if we know their time, date and local and we know the optimal conversion point in the game AND we know the games commerce friction co-efficient AND we know the games rough viral properties when it is free THEN we can calculate any individual users PROBABLE value state at the moment they are playing and make a heuristic decision about monetizing it.

EXAMPLE:  Joe Gamer started playing Gnome Wars eight days ago and has played five sessions in the past two days.  According to our addiction profile for Gnome Wars,  Joe Gamer is “addicted” to the game.  Joe Gamer is playing Gnome Wars NOW at 9:30am on a Monday morning… should we attempt our first commerce transaction with Joe?

Gnome Wars probability of converting an addicted player:  3.3%

Gnome Wars average first transaction size:  $25.75

Gnome Wars average LTV: $36.50

Probability of converting any addicted player to commerce on a Monday morning: -23%

Gnome Wars Addicted Player profile:   A Gnome Wars addicted player generally maintains close to peak addiction for 8-11 days with an 11% risk of losing the player during that period.

So let’s decide if we should ask Joe Gamer for money now, or at a different time;

Ask for Money now? 

(3.3% – (1.0 – .23))*$36.50 = $9.27

Ask for Money Later?

3.3%*36.50*91% = $10.96

Individually you risk losing Joe Gamers money if you wait to try to monetize him but collectively the patience heuristic will yield more money from the overall audience.  If you are trying to make payroll however the math may yield a different result…

Ask for Money now? 

(3.3% – (1.0 – .23))*$25.75 = $9.08

Ask for Money Later?

3.3%*$25.75 *91% = $7.73

One might quickly realize that the use of probabilistic pricing can give you control of your revenue recognition within a range of value.  It’s very useful when forecasting quarterly revenue results when you can tune your economy to bring revenue forward or push it back in time depending on what suits your accounting needs.  You can even calculate the price of bringing revenue forward and make a financial decision about doing so.  In this example, bringing revenue forward costs $10.96-$9.08 = $1.88 per transaction.

This brings us to the fascinating subject of dynamic pricing.  Is it possible to sell the same product to two different users at different prices?  The success of microcurrency based business models illustrates at least one example where the answer appears to be YES!  Some people will pay hundreds of dollars/month to play Zynga Poker while others will pay nothing.  However this example is not exactly fair, although paying and non-paying players are consuming the same game, the paying players ARE getting a different experience.   Microcurrency based economies do not, in fact, charge people different prices for the SAME experience.  Suppose I have two people making an in-game item purchasing decision in the same game, at the same point in the game, at the same moment in time, in the same market?  The only difference between the two players is that the value the good differently from one another.  Is it possible to charge them each the optimal price the virtual good is worth to them without them discovering that they paid more or less than somebody else and getting angry?  The answer to this puzzle is very similar to the solution to the ball puzzle I described earlier.

Solution to the Ball Puzzle:

Place all the white balls and 9 of the 10 red balls in one bucket, place one red ball in the remaining empty bucket.  Now the odds of me randomly drawing a red ball from either of the two buckets approaches 75%, a 25% improvement over distributing the balls uniformly between the buckets.  The key is the realization that given 10 balls of each color to distribute instead of one ball of each color it is possible to mix the ratio of balls in different combinations between the buckets to achieve different probability ratios for drawing a red ball!  In a single microcurrency based social game with many virtual goods or in a portfolio of MANY games there are usually MANY monetization opportunities for the consumer not just one.  Probabilistic pricing distributed across many  monetization opportunities makes it possible to dynamically adjust the aggregate price of all virtual goods in the game to approach each players optimal monetization level without regard to the actual price of individual goods.

Hybrid Auction

Now that we have shown that we can assign a price to virality, a price to the advertising value of an audience and a price to the current and future commerce value of an audience then we can answer the question of how to monetize any arbitrary player in the game at any moment in time by running a quick heuristic auction between the three payment methods.  Joe Gamer has clicked on the purchase button for the Gnome Slayers Sword.   We can ask him for money, show an ad or ask him to invite friends, we calculate the heuristic value of each transaction option, compare them to one another and the greatest valued option wins the auction and is presented to Joe Gamer.  Simple!

Not so fast, we haven’t done our Quantum Economic arithmetic correctly yet.  The magic idea of Quantum Economics is that, with a little perspective and good analytics, it’s often possible to capture MOST of the value of a system, not be forced to choose one over another.  By choosing between prices presented by three different payment methods, the implication is that the money available from the other two options must be left on the table in order to capture the greatest value of one of them.  This is NOT actually true.  The uncaptured value of some payment methods can often be deferred to a different occasion where the value is recovered later.  Just because an available payment option was delayed does not mean the value was lost.  Advertising value is the only kind of instantaneous value that is hard to deferr.  If you don’t take an advertising opportunity immediately, it is largely lost.  Virality and commerce opportunities can often be deferred without substantial loss of value.

The user perceives that the ad is worth a quarter since a session of gameplay ordinarily costs a quarter even though less than 5% of consumers ever purchase. Interestingly advertisers ALSO perceive that they are getting a $250CPM placement here. The consumer gets a free session of play, the advertiser is happy to pay a higher CPM for this placement, we make more money! Everyone is magically happy somehow?

Quantum Economics makes it possible to “store” or “borrow” revenue from the future.

My first first-hand experience with this phenomenon was at WildTangent when we faced a difficult business decision during an executive meeting.  Kraft foods wanted to pay us a seven figure sum of money in advertising dollars to make our entire network of games free for a month sponsored by their various food brands.  The hybrid calculation on total revenue yield showed that we would lose as much revenue in commerce dollars as the ad campaign was worth to us.  What was the point in doing that?  Of course our commission based ad sales team pointed out that Kraft was a HUGE account to win and this was a HUGE premium ad buy.  If we were going to turn down deals like that, why be in the business of selling premium ads at all?  I reluctantly decided at the time that although it might be a huge waste of commerce revenue, it was a huge advertising win for us and would lock in the revenue for that month.  We took the deal.  The campaign ran for a month, our gaming traffic DOUBLED because the games all became entirely free, when the campaign ended and the commerce option kicked back in, 80% of the lost commerce revenue arrived in a wave as all of the existing free players and new free players that the campaign had gotten deeply engaged in games, started paying.   We subsequently realized that running waves of free ad supported play followed by lulls generated MORE revenue than choosing advertising over commerce or simply smoothly blending between them.  We also found that oscillating our models also reduced the tendency of the audience to “learn” our heuristics to avoid paying.  We called the practice whiplashing.

To summarize, a proper Quantum Economic value auction between different abstract payment types needs to take into consideration the future value of deferred transactions in order to price them correctly by subtracting the immediate value of lost ad revenue from the deferred value of commerce and virality.  Using the Kraft ad campaign example above the math might look like this;

Users instantaneous commerce value = $1

Deferred commerce value = $1*80% = $.80

Non-deferrable ad value = $.36

Instantaneous commerce value adjusted for lost ad revenue = $1 – $.36 = $.64

Since the future commerce value is greater than the present one and the ad revenue is non-deferrable the optimal decision is to show the $.36 ad NOW and initiate the commerce transaction for $.80 in the future for a total of $1.16 in hybrid revenue.  The COST of not including TIME in your pricing is $.16 per transaction…

*Note that the video ad actually plays while the user is making their choice… we get the ad revenue no matter what the user chooses… “Magician’s Choice”

In this example a Full Energy Refill Pack may have a $1 retail price.  Anybody can buy this pack for $1 at any time… however… in this example a user clicking on this item has been offered it for free in exchange for watching a Coke ad.  By serving an ad to make this item free to users 50% of the time, the “effective” Quantum price of the item is $.50 cents.  If we know that users playing this game will engage in dozens of commerce transactions over their lifetime we can blend the probability of serving a free item offer with a paid purchase offer to the user over their lifetime to generate an aggregate commerce revenue yield from them that may be completely different from the commerce goal for another player consuming the same game under the same circumstances and buying the same virtual goods.

Kids are a great concrete example of a meaningful application of dynamic pricing.  Social game developers are often seeking “whale” players who will spends hundreds of dollars a month on virtual goods without a care.  The trouble with this approach to monetization is that it can be difficult to differentiate a mature adult whale gamer from a kid going crazy with his mother’s credit card.  If Jr. runs up a $200 commerce bill on his mom’s card the game will get a commerce charge-back and an angry support call from an outraged parent at the end of the month.  Credit card thieves will also spend money on a social game without regard to cost.  How do you balance the business cost of handling angry parents and credit-card chargebacks against the benefit of having a small subset of users spend tons of money on a game?  Using dynamic pricing you might change your monetization goal for these players to generate no more than $40 in commerce revenue from them during the first 30 days of play and retain them long into subsequent months by increasing the ratio of free ad sponsored items to paid ones such that new payers are not able to spend more than $40 in commerce expense their first month, no matter how they play.  Once you are confident that the credit card is legitimate and the bill is paid you can gradually turn down the free ad supported item server to increase revenue.

Now we enter the realm of really exotic Quantum Pricing models.  We’ve demonstrated how to think about maximizing commerce value, we’ve shown that it is not only possible but powerful to mix advertising with paid commerce as a way of dynamically pricing virtual goods to maximize revenue.  Finally we take a look at the idea of substituting social messaging instead of currency OR advertising as a form of payment.  Here the user has been offered the opportunity to invite friends or connect to other social networks as an ALTERNATIVE to paying for a virtual good.  Look carefully at the images and notice that the OPTION to pay is always available to the consumer.  The result of positioning payment as an option is to constantly remind the consumer that they are in control and can decide if and when they want to see ads or invite friends INSTEAD of engaging in a commerce transaction.  It also reminds the consumer that the goods they are getting for free have a real cost, they just happen to be getting a deal on them.

Putting it all together

The idea that sets Quantum Economics apart from conventional microeconomic pricing models is the realization that when a good has negligible cost to deliver and support, a huge new range of economic options become possible that do not exist for goods with tangible value.   One of the most pronounced observations is that is possible to replace fixed pricing and fixed business models for probability based hybrid models that are many times more efficient at monetizing an audience across a virtual service than any simple business model can be alone.

We have shown that it is possible to calculate a games optimal value and use that information to calculate the monetary value of the games virality.  We have also shown a Quantum Economic way of treating advertising as an equivalent alternative to commerce in the same context and price its value relative to commerce correctly.  This means that mathematically speaking, commerce, advertising and virality can all be priced and treated the same as money and incorporated into the same business model without having to choose or compromise between them.  Let’s look at an example that puts all of these ideas together.

In this example Joe Gamer clicked “purchase” on a Full Energy Refill Pack in this social game.  Instead of going straight to a commerce page the game served a free alternative to paying for the item… why?  Let’s calculate the “probable” value of different monetization options for this event in the game and determine what we think the user will do here.

Probability of engaging in a $1 commerce transaction at this point in the game:  1.7% = $.017

CPM value of serving a video ad to this user at this point in the game: $20CPM/1000 = $.02

Viral Value of asking Joe Gamer who has no friends in the game yet of inviting friends:  $.03/DAU * .76 virality = $.023

Huh… the MOST valuable PROBABLE transaction Joe Gamer can initiate here is to invite friends, the second most valuable transaction is to view an ad and the least valuable action is to ask Joe Gamer for money…  When Joe Gamers is asked to choose between getting the item for free in exchange for viewing a video ad and paying $1 for the item, which choice is Joe MOST LIKELY to make?  96% of the time, Joe will choose free… as a result of not getting blocked in the game, Joe will play more AND be more likely to invite friends resulting in a net greater value to the game playing for free on this occasion than being asked to pay… Giving Joe Gamer the choice between commerce and an ad, or commerce and inviting is called Magicians choice.  The consumer is offered a choice that doesn’t matter… if our heuristic was wrong about Joe and he ends up making a commerce transaction we didn’t expect, GREAT!

In general, after running Hi5.com, a social network with 60MMU and hundreds of social games, we found that when Quantum Economic probability profiles are used, in general the most valuable thing to ask a user for early in a game is virality, the second most valuable thing is commerce and the third most valuable thing is advertising revenue.  Generally, however, the optimal point of monetization in a social game is much deeper into the game than most game developers realized, substituting advertising to get users further engaged with social games before triggering commerce demands, increased the commerce revenue for many games we tested it with by 30%-80% in part because the MORE free versions of the game were MORE viral and had attracted and retained a larger audience by the time commerce demands started kicking in.

*Note that it was not necessarily incorrect for games to price themselves the way they did if they had no advertising model alternative available to compensate for instantaneous potential commerce revenue losses they would incur in order to defer commerce transactions deeper into their games.  The risk of losing the player in the future exceeded the value of the potentially greater commerce yield from the remaining players at a later date.  Substituting video ads for commerce transactions took the risk out of that financial decision by providing the game developer with a smooth stream of ad revenue during the longer trial period before players were asked for commerce.

Conclusion:

The ball puzzle contains one other important insight, the greater the number of balls and buckets considered in the puzzle the finer control you have over the precise probability of picking any specified color.  In other words the efficiency of extracting ALL of the potential value from an audience increases with more audience and more games.  Moreover as many many hours of deep analytics and data mining has shown me over the years, when you learn to treat a body of content and a large audience as fuzzy probability profiles the need for massive analytics infrastructure seemingly disappears.  You don’t need to track everybody’s individual personal information and behavior to devise a monetization system that captures all of their potential value.  Once you understand the overall structure of an audience’s behavior within a body of content, it is more efficient to treat the entire system as a Quantum Mechanics like probability distribution function and ignore the individuals.  As stated earlier, it isn’t possible to know an individual’s value state and capture it simultaneously.

Track and analyze trillions of individual social events and mine it all for meaning
OR…

x^2+y^2 = z^2
Fire the analytics team…

This insight is analogous to trying to predict how individual gas molecules crashing around randomly in the interior of a balloon will behave.  If you tried to track every single one of trillions of molecules and predict every collision and interaction between every particle in real-time in order to predict their future movements you would need an analytics infrastructure larger than all of the computers available on Earth.  If, however, you stepped back and realized that the collective behavior of the entire system can be described by the one line equation for a sphere’s diameter governed by the gases temperature and the balloons elasticity, you would know everything that mattered about predicting the systems future behavior with minimal analytical requirements.  Did the temperature increase?  Then the balloon’s diameter will increase proportionately… end of calculation…

I’ve had the same experience on several occasions, after months of pain staking data mining and massive data accumulation; I would hit on an insight that described the entire system, once that insight happened, the need for the monumental amount of data and analysis seemingly disappeared because a simple observation was often enough to characterize the system.  I don’t need to know where all the particles are in the balloon anymore, just tell me the temperature and I’ll tell you the balloons diameter.

I made this slide in 2007 to illustrate that a hybrid currency model was a superset of all known downloadable game business models at the time. After Hi5.com I subsequently demonstrated ways to price virality as a form of commerce but I haven’t made a slide showing that symmetry recently

The post What’s so “Quantum” about that? appeared first on The Saint.

Consider this blog entry a draft article on calculating a games optimal monetization properties using Quantum Economic theory.  Based on feedback I expect to iterate on this article over time until it becomes a high quality introductory white paper on the subject.  At some point in the future it would be fun to contrast the Quantum Economic pricing ideas discussed here directly to their Microeconomic counterparts but for the sake of brevity I’m going to plunge straight into the exotic world of HOW to calculate the optimal value of virtual products and design efficient business models to capture them.  To help me illustrate some of the more exotic ideas I’ve made some rudimentary slides that I also hope to improve on over time.

Let’s begin with a really simple equation for describing the “Value” of a virtual good or service.

Value = Potential Commerce Revenue + Potential Ad Revenue + Potential Viral Value – Marketing Expense

Or more succinctly;

V = C + A + V – M

For the purpose of this discussion we’re going to ignore Marketing Expense because calculating the optimal marketing expenditure for a game is a topic for another white paper of its own that relies on the result of calculating the other three critical variables in V.  The principal idea behind calculating V is to figure out what the MAXIMUM possible revenue may be achievable for a virtual good or service assuming that you had the PERFECT business model that captured all of that virtual products perceived value from the people who consume it at the point when they are most willing to pay.  In the classical world of product pricing this task is simpler and often easier to understand, but in the online world where you are trying to figure out a virtual products optimal monetization potential it can be much more complicated, in part, because many virtual products have NO PRODUCTIVE VALUE.  Games are of course the best example of virtual products that cannot have a rational value assigned to them using classical microeconomic pricing techniques.  Games have no use, they waste time and their perceived value is highly subjective to many environmental factors.

How much of this stuff are your games leaving on the table because you don’t know how to price them?

The purpose of figuring out a games “Maximum Value” is to more effectively measure how well a given pricing model, distribution model or marketing campaign is doing at capturing as much potential revenue as a game possess.  If a games “monetization space” is known then it is possible to know when you are reaching the limits of various approaches to maximizing revenue.  It also provides an effective way to measure how “good” a game really is.  For example, we all know that World of Warcraft is one of history’s most successful games of all time, however that does not mean that this great game was efficient at capturing all of its potential value, it may just mean that the game was so fantastic that it made lots of money despite squandering vast additional potential revenue.  What a shame it would be to have wasted billions of dollars in additional potential revenue from this game because it was not known how to calculate the games maximum potential value at the time that it was created?

In my own personal experience, developing these pricing techniques increased the revenue per user of my own online game company, WildTangent Inc. by 1800% per user over three years.

Let’s start slow and simple.  Value = The maximum potential revenue a game could earn over its lifetime assuming that it had a magic perfect business model and marketing strategy that captured every dollar that somebody was willing to pay for the content.  Value is just a number, however mathematically it is described by summing the area of a very complex multi-dimensional value space.  Visualize it as a giant undulating blob.

A crude attempt to illustrate a games potential monetization space with a single simple business model embedded in it, capturing a small area of the games total monetization potential

The purpose of this exercise is to develop a way to figure out a games total monetizable potential given all of the available monetization methods and devise more advanced business models that may combine a variety of approaches to efficiently capture more of a games maximum monetizable value.

Here I attempt to illustrate how different business models capture different subsets of a virtual products potential value. Classical economic thinking would have you conclude that you simply have to pick one model that captures the largest monetizable sub-region of the games potential. Overlapping models might confuse or anger consumers and result in cannibalization between approaches right?

WRONG! Good application of analytic heuristics to business model design can result in MUCH more revenue AND a better, simpler, consumer experience from the careful segmentation of audiences into monetization categories and the heuristic blending of models.

A few of the important dimensions describing this blob are as follows;

• The time consumption profile of the game
• The price/conversion sensitivity profile of the game
• The free play demand volume of the game
• The addiction or conversion probability profile
• The self-virality of the game
• The re-engagement value of the games players
• User purchasing power from their local and/or currency

It’s not necessary to understand all of these properties of the games monetization space to get a sufficient idea of how to estimate its volume or total value potential.  For our purposes it is sufficient to calculate 5 properties of this space to produce a good intuition for a virtual products total monetization potential.

Steps:

1. Calculate the games classical microeconomic demand curve.  In other words, its probability of converting to a purchase over a range of price points.
2. Calculate the games “addiction profile” which is basically a measure of the games probability of converting a user to a purchase at a negligible price at various stages in the game.
3. Calculate the games free play volume
4. Calculate the games negligible price play volume
5. Use the results above to estimate the games viral coefficient

We’ll cover the meaning of each of these calculations in more detail as we examine each of them.  The important idea to understand in advance is that there are three important variables we are attempting to assign a value to;  the maximum commerce value, the maximum ad revenue value and the viral value of the game.  Although virality is a strange and exotic property of virtual goods that can be very difficult to calculate usefully, we can use a crude linear approximation of virality to do a “sufficient” job of estimating the value space of most games.  My much more advanced articles on the EUREKA virality equations deal with this subject in much more depth and sophistication but for the purposes of this paper we will use a more classical linear idea of virality to come up with a reasonable estimate of a games total monetization potential.

For Step 1 we need to build a graph of the games probability of converting a user to a purchase over a range of price points.  This can be accomplished by offering the game to cohorts of test subjects at different fixed price points.  The result is usually a bell shaped demand curve.  This curve tells you the shape of the games demand distribution.  In a classical microeconomic world a marketer would use this information to assign a product the single fixed price that captures the largest area available under this demand curve.  In a Quantum Economic world however, this would be a mistake, because unlike the classical world of physical goods, online it IS possible to effectively offer the same product at different prices to different users based on their analytically estimated optimal price point.  Microcurrency based pricing is very effective at accomplishing this kind of dynamic pricing without consumers feeling that they are being treated unfairly by being charged different prices for the same game.

For Step 2 we need to figure out a games addiction profile.  In other words we are attempting to determine the point in the game play experience when the user has the maximum perceived value that they will ever have for the game experience.  Since this property varies from user to user, it is represented as a graph of user probabilities of converting to a purchase over a range of times or events in the game.  Since the goal of this step is to understand at what points in the game players have the highest perceived value for the content they are consuming, price is unimportant.  We need to conduct this test at the lowest possible commerce price in order to get the best quality data sample of purchase conversion rates across cohorts of users who are asked to make their first commerce transaction at different stages of gameplay.  In my experience a game that has its highest conversion value BEFORE the user plays it is a “bad” game.  A game that has its highest point of perceived value occur early in the game and sustain long into the game experience is a “great” game because it will convert users to purchase early in the game experience and retain them at a high monetization level.

Detecting a games “Peak Addiction” points is important because most forms of commerce transactions involve a high degree of friction related to the time and effort it takes to fill out a form and navigate the necessary security precautions that commerce transactions inherently require.  Commerce transaction points represent a major threat to a games audience retention and virality which in turn has a dramatic impact on the games overall value profile.  Knowing the best moments in a game to ask for money and having an analytical basis for calculating the probability you will get it is the secret sauce to engineering hybrid business models that use player behavior to determine the optimal monetization strategy for players on an individual basis instead of as a group.  If you know in advance, with a high degree of certainty, that a given player  WILL NEVER engage in a commerce transaction, how does it change the way you want to deal with the player?  A common choice is simply to discard the player, but almost all players have advertising monetization value and viral value in addition to potential commerce value.

In general, a good rule of thumb that a user is at or near their optimal point of commerce conversion is when they are self-returning to the game several times a week.  It has also been my experience that the optimal conversion opportunity is after dinner time during the week or best of all, around 2pm on a Saturday afternoon.  Asking a user for commerce during their lunch time can have a high failure rate because people often have limited time to enjoy themselves during lunch and want a quick entertainment fix.  Trying to convert them to a purchase during this period can risk losing a potential future transaction.

Knowing a games conversion profile can be extremely valuable because, in general, if a player fails to convert to a purchase during their maximum point of perceived value for the game… it is very unlikely that they will ever convert… which means they can be safely harvested for advertising revenue or viral marketing without fear of cannibalizing potential commerce revenue.  At WildTangent, we became 97% efficient at correctly guessing which game players would never pay us and converting them to ad revenue.

For Step 3, we need to calculate the “free” value of the game.  For games with classical expense structures like needing boxed retail distribution or having a high support cost per user, this calculation may be meaningless because the cost of supporting free players is not “negligible” for the game.  In a Quantum Economic world where serving and supporting online gameplay is relatively negligible, a games free value is very important to know because most games have extremely long tails of non-commerce monetizable gameplay.  To state it another way, if a game has a 5% conversion rate to commerce then it means that 95% of the games potential audience values the game at some price LESS than can be efficiently captured with a commerce transaction.  *In fact 40% of online gamers are often minors that simply cannot make online purchases for lack of a payment method.  If the cost of delivering and supporting the game is “negligible” then it is often a mistake to deny these users play when they simply cannot or will not ever pay for the experience.  Most games “long tail” of play demand, represents such a large volume of play, that if it were fully monetized via advertising it would generate as much or more revenue than the commerce revenue generated from the 5% of the audience who actually pays.

Consider a game that the average user plays 5 times a week for 20 weeks, resulting in 100 total sessions of play.  If 5% of the audience converts to a commerce transaction and has an LTV of $20, what is the advertising value of the 95% of the audience who is NOT paying?  Assuming that you could play a single $10CPM video ad in front of each free player per session you would generate nearly $1 in LTV from each free player, so a sample audience of 100 players would generate 95*$1 = $95 in ad revenue over their lifetime and 5*$20 = $100 in commerce revenue… almost the same money or double the money if you could capture both!  Clearly for many online games that have negligible operating costs, ad supported free play and commerce supported paid play can be very complimentary business models assuming they can be combined successfully.  As the addiction calculation step suggests, identifying people who will never pay is not that difficult and thus separating your audiences quickly into payers and non-payers makes it possible to capture both revenue opportunities efficiently.

Calculating a games free play properties is simple, make the game entirely free to a test cohort audience.  For many types of games, however, this is not as simple as it sounds.  For social games this can be difficult because the economic constraints of the games virtual goods market is part of the game design.  It can also be difficult for social games because, for the test to be decisive, you really need a player’s friends to all be included in the free cohort.  This challenge is a subject for another paper, suffice it to say for now that I have solved this problem sufficiently for social games in the past to get a meaningful read on the game by simply making the game entirely free in an isolated test market like New Zealand or Australia or by more sophisticated means requiring some modification to the games.

For this test, it is important to capture three dimensions of play behavior, starting with an initial test cohort of say 100 free players we need to learn the games retention rate over time  on a per play session basis.  For each play session the player engages in we need to record the date, time and duration of the session.  We also need to know how many friends free players interacted with during each session of play, how many they  invited to the game and how many accepted those invitations.

Step 4, calculate the games play volume at a “negligible price”.  Once we have measured how people consume and spread the game when it has NO cost, we need to compare that to the same data gathered from player behavior when the game has a “negligible” price.  “Negligible” in this case is defined as the lowest price you can transact in, usually around $1 in Western markets.  Basically we are measuring the basic transaction friction for the game and using it to estimate the overall adverse interaction that the games chosen commerce model has on audience retention and virality.

Step 5, calculate the games free and paid viral coefficients from the data gathered in steps 3 and 4.  The value of the games ability to market itself when it is free has to be included in the games Value equation for the maximum value calculation to be correct.  Every user the game can recruit for itself when it is free is a user that doesn’t have to be purchased or recruited via marketing expense for the game when it is paid for.  The property of online products to be able to do their own marketing is one of the fundamental properties of these products that is captured by what I have labeled Quantum Economic theory and is hugely influential to their online success but is not described usefully by classical microeconomic approaches.  As the EUREKA formulae described in my other blogs on this subject illustrate, it also takes some very exotic math to usefully describe the influence of virality on a virtual products success and overall potential value.  Here we will just consider a simple linear estimation of a games viral properties;  For our purposes we will simply take the ratio of the number of sessions played over two weeks by the free cohort audience to the number of sessions played during the same period by the paid cohort audience.  It’s not always possible to precisely track the viral acquisition of new players between test groups which is why making the game available in a controlled market free or paid and then comparing the normalized session behavior between market tests can be a reasonable alternative to precise viral tracking.  What we are really measuring here is the difference in play volume which happens to include the games viral properties.

Consider a game that attracts twice as many players for twice as many sessions when it is free compared to the same game that has minimal commerce requirements.  IF the game only supported a commerce business model it might “appear” to have a 5% conversion rate to purchase, however, if through the clever application of Quantum Economic business model design the same game was free to 100% of the players who would never pay for it the game would attract twice the audience… 5% of the additional free audience recruited by virtue of the free play mode would covert to purchase doubling the games commerce AND advertising revenue… producing 2X the commerce revenue as the paid only version of the game and 4X the ad revenue as the free game with NO virality would generate.  How much was the viral property of the game worth?  Roughly 500% of the games simple commerce value alone.  Using our simple viral equation the math would look like this.

Value = 1*C + 1*A + 4*V

Our ability to price our game correctly would be woefully inaccurate if we did not include the influence of virality on the equation.  For you mathematicians out there I know that this is an egregious simplification of the influence of virality on a games other revenue properties, but for the purposes of this paper I’m hoping to simply and strongly communicate the essential and fundamental influence of this property of online games in estimating and capturing their total potential value.  Including the influence of virality correctly in the math is at the heart of what makes Quantum Economics an important insight and analytical approach to pricing virtual products.  The important observation is that with good analytic tools Quantum Economics makes it possible to craft online business models that capture MOST of a virtual products potential value instead of just a small fraction of it.  It is NOT actually necessary, as it is in the classical business world, to choose one business model over another.  For virtual products, business models can be mixed, matched and blended together to maximize captured value.  My next blog will demonstrate how to use this data to construct more efficient hybrid business models that systematically extract more of a games potential value as a result of knowing how much value a game contains and where the value is located in the game.

Crude tests on hundreds of social games at Hi5.com and later Magi.com showed some significant improvement in retention and session duration as a result of replacing commerce offers with free ad offers

Overall monetization of social games doubled as result of the increased revenue/user from a mixed advertising + commerce business model combined with the amplified virality that resulted from increases availability of free play to non-paying players. The monetization yield increased over time as the compounding influence of increased virality and retention accumulated. Observe the “Quantum Economic” paradox that these games increased their commerce revenue by becoming apparently FREE to 97% of the audience… who was never going to pay anyway…

The post Finding ALL The Money appeared first on The Saint.

To that end, here is my top 5 list of things you need to “Unlearn” to succeed in online gaming

1)      Online games are not PRIMARILY valued for their production values or “content”

2)      VIRALITY is your god, if you don’t understand its relationship to game design, your games are doomed to fail

3)      Online games must be their own best advertisements, there is no separation between marketing and game design

4)      Online games must be their own best sales force, there is no separation between business model and game design

5)       Social engagement and emergent content are the primary “Features” that consistently define modern hit games

Let’s examine each of these points briefly;

Online games are not PRIMARILY valued for their production values or “content”

By “production values” I mean lots of high quality media.  The traditional game industry relied on selling “boxes” of content that most consumers purchased sight-un-seen after, maybe, reading some magazine reviews about the game.  Each box of game content contained a body of relatively linear, highly authored content that was designed to be consumed over 50-80 hours of play, at which point it was hoped that the consumer would buy another box of game content.  The value of the game was defined by the quality and volume of game assets contained in each box.  Unlike in the retail world, “high production values”  are not the primary value generator for online and mobile content, in fact they are often responsible for a games failure.

1)       Making a game larger increases its distribution friction and hampers virality which, as I will explain shortly, is a MAJOR mistake in an  online world

2)      It is a huge mistake to make online games that have an END.  An online games #1 job is NOT to make money, it is to accumulate and engage audience.  When a game ends, its audience is lost.  Generating lots of revenue is a symptom of a successful online game, not the end result.

In the online world, media assets should be considered a highly conserved resource that should be applied with finesse, polish and extremely high re-use.  There is a tendency of traditional game industry veterans moving into online/mobile game development to believe that their experience with high production value narrative game design will give them a competitive advantage, when the opposite is true.  I have met many disillusioned game developers who made great looking narrative style games and been mystified when they failed online.   It’s not that consumers don’t want great graphics, sound and animation, it’s just that their patience and attention span is usually too short to appreciate them because they’ll move on to something else if trying a new online game requires any time to load, install or otherwise learn.  Consumers won’t give a fat game the opportunity to market itself to them even if it’s great, which is why they can fail online.

VIRALITY is your god, if you don’t understand its relationship to game design; your games are doomed to fail

This is such a HUGELY important point, yet I’m constantly shocked to meet seasoned online game developers who haven’t fully grasped this yet.  There is only ONE efficient way for an online game to succeed and that is to generate virality.  Contrary to popular misconception, it is no longer good enough to just make a game SO GREAT that people just can’t help but talk about it.  Not only is it critical that an online game be so great that people want to talk about it, it is also ESSENTIAL to any modern games success that the game is very effective at enabling and incentivizing people to spread the game through their consumption of it.

I’m going to try to make this next point as clearly and simply as I can;

The online market for audience is HIGHLY EFFICIENT; you cannot spend marketing dollars at a profit to buy traffic for a game that does not amplify its own traffic.  You should not spend a single dollar buying traffic for a game that does not exhibit positive virality FIRST.  You can’t generate profits by buying traffic for a game with poor virality.  Every marketing dollar you spend will return pennies on the dollar spent.  If your game isn’t organically viral first, your marketing budget for it should be ZERO.

The definition of virality that you should work with is that each user who plays the game should, on average, recruit more than one other player to join the game during their active lifetime.  To be clear this means that virality is a function of both the players tendancy to invite other players into the game AND the games ability to retain players over time.  A game can’t compound audience exponentially if it doesn’t keep the older players playing while they are bringing new players on board.

The crucial role of virality in online gaming is one of the fundamental reasons that online games cannot be so big or media rich that they take time or effort to install.  Any design decision that places drag on virality, guarantees the games failure because it will not accumulate traffic on its own.  An online or mobile games FIRST job is to accumulate audience.

Online games must be their own best advertisements, there is no separation between marketing and game design

If you accept (which I strongly recommend that you do) that it’s not practical to buy traffic for a non-viral game at a profit, then clearly there are very few effective ways to market an online game.  The irony of this statement is that an online game…is…online… and they are just media like any ad.  In other words, modern games ARE ads for themselves.  The places you distribute them are effectively ad networks targeting gamers.  The 30% revshare that Facebook and Apple collect for your commerce on their networks is effectively a CPM ad buy that is priced in direct proportion to the value of your games own popularity (virality) to their audiences.  If you want to make less money per user by buying advertising from them on top of their rev-share, they’re happy to take that revenue as well, but remember that each dollar you give them from your own pocket would probably have been better spent making your game a better “ad” for itself in the first place.

To support my earlier points on the subject of virality, would you ever install a browser plugin or download an application online or PAY money to view an ad?  “No?”  Then what does that make and online or mobile game that does this?  A bad ad?  Your game had better be very efficient at selling people on trying it and getting them addicted BEFORE asking them to do any work or pay any money for it… or you’re in the business of wasting money making ineffective online ads.

Online games must be their own best sales force, there is no separation between business development and game design

Second only to being great ads for themselves, online games are also their own markets.  It’s their job to attract, addict, and monetize traffic for themselves.  In the modern online world it is not sufficient to make a great game and expect people to pay money for it without them getting to try it first.  Second it is not sufficient to simply charge a reasonable price for your product.  Your product has no “reasonable price”, it’s a time wasting anti-productivity service!  If you don’t try to maximize the value of your content per player then all of your other efforts have been wasted.  Now this is where it gets REALLY tricky because if you don’t religiously understand and accept the earlier points about virality and self-marketing it’s impossible to correctly price your game because you don’t know how to price the value of your own games ability to market itself!

Think about it like this;

Pretend that the cost of supporting each of your games players is negligible.  Assume for the sake of discussion that your game has ZERO virality and that it costs you an average of $2 per player to buy traffic for your game.  Assume that you purchased 100 players this way.  Further assume that 5% of your players will become payers and that their average LTV is $20.   Since $20*5% = $1/user on average, you’ll be losing a dollar in revenue for every click you purchase.  Now if you offered each of your free trial players $10 worth of paid game currency to bring one friend into the game… how much money would you lose giving away that much currency?

Clearly the LTV of your paid players might drop to $10 each because they were getting half their value free… (Not really but I’ll get back to that subject)  So you would lose half your revenue or 50 bucks right?  But your game now has virality of 1, so your 100 players brought you 100 more, 5% of whom paid you $10 bucks each… so actually you lost nothing?  But those 100 players also brought another 100 new players, which also each pay $50 bucks… and they bring another 100 players who pay another $50 bucks!  Wow, what would happen if you paid each of your player’s $15 bucks worth of premium game currency to bring 2 new players each!  You would get exponential audience and revenue growth twice as fast!

This kind of thinking is highly counterintuitive; however it is exactly how you should think about online game design.  Virality and audience accumulation is more important to get right than monetization because monetization is a very pleasant and exponential side effect of successful virality!  If you achieve positive virality what will happen when you buy a click at ANY price?  You will get an exponential return on that click because of the audience chain reaction that purchased user will generate for you.  What price can you afford to pay for a click for a game that does not have this property?  Remember that the price YOU pay for clicks is set by the games that ARE viral which can afford to pay exponentially high prices for them.

So what have we learned?  Virality, self-advertising and self-monetization are all intrinsic aspects of online (and mobile) game design.  Their relationship to one another is intimately entangled and must be delicately balanced in the game design itself.  If you accept this mentality (which you should) then the implications to game design are profound.

Social engagement and emergent content are the primary “Features” that consistently define modern hit games

These are the properties that ensure that two apparently unrelated games like Mindcraft and Zynga Poker are perennial hits.  These aren’t games as we knew them; these are “structured” playgrounds in which the audiences are free to entertain themselves and each other indefinitely.  Their content re-use and the range of play dynamics they enable are seemingly boundless.  How big would your art department have to be to produce enough high production value narrative content to keep audiences this size engaged as long as these games do?  Not only is it impractical… it’s actually impossible to compete with this kind of game design.  Emergent games in which the game produces endless worlds and physics and the players “author” the game themselves have nearly limitless virality and re-engagement value.

In this respect the term “social gaming” can be very confusing and misleading.  Most people play these games alone with relative online strangers.  They are not being “social”; the other players are providing a bottomless source of emergent content that no human game production team could ever manually author.  What “social” really means is a class of game design that found a way to make a successful play mechanic out of getting the games players to do the games marketing for it.  Brilliant!

This is a relatively new and un-explored space in game design that relatively few game designers have shown a great talent for and yet it is an extremely large opportunity.  Will Wright, famed creator of The SIM’s, is of course legendary for his relatively consistent success with these kinds of games.  As he and Zynga have demonstrated, they don’t have to be massive World of Warcraft scale MMOG’s to work.   In fact, in a world where these games are distributed online, it is vastly more important that these games be elegantly and efficiently designed with the greatest emphasis placed on how efficiently they promote themselves virally and retain audience through extremely high replay value and efficient re-use of media.

I realize that there are successful people in the online game world who might read this article and imagine that they are examples of exceptions to the points I’ve made, but they are most likely, mistaken.  I’ve used very simplified examples to illustrate these ideas but they apply universally, often in much more disguised forms.  Virality or word-of-mouth, as it used to be called, in the traditional game industry was always been a hugely important but poorly understood factor in the success or failure of traditional games.  In the classic retail game world, measuring, or accounting for the influence of virality was nearly impossible and the ability to influence it systematically was also impossible because distribution friction was the same for all console games.  As a consequence it was simply dismissed as an important way to think about game design.

id Software, one of the first hit “Social Game Companies”

DOOM was a bloated 3MB’s to download via a 5600 baud modem

*Old school gamers may recall that id Software’s first hit games were distributed for free on BBS bulletin boards.  Each game was designed to exactly fit on the floppy disks of that era.  Id’s President at the time, Jay Wilbur, told me that they had 500,000 copies of the shareware version of Castle Wolfenstein downloaded and sold 75,000 which made them MORE money than the retail version of Castle Wolfenstein which SOLD 500,000 copies.  Of course Apogee Interactive, the retail publisher of Spear of Destiny (Wolfenstein), had to do very little marketing to promote the retail version of Wolfenstein… everybody already knew about the game from the now famous shareware version.

An appropriate analogy for online games vs retail games is the difference between modern movies and modern television show marketing.  A movie is a fixed unit of entertainment content that people pay a premium to consume on the basis of little more than a 30 second preview and some reviewers comments.  Online games are TV shows, the show itself is the best ad for itself and unlike a movie the shows goal is not to get your money upfront and end as soon as possible, a TV shows job is to get your attention and keep it for as many years as possible through the constant re-use of the same characters and plot elements.   TV shows monetize themselves through a complex blend of advertising and paid business models designed to maximize the total potential revenue from the show as a combination of advertising and commerce dollars.

Somebody from the movie industry trying to learn to make TV shows would make a lot of mistakes learning the vast differences in business models despite the fact that both movies and TV shows are based on the same kind of media.   Somebody from the movie industry might also mistakenly think that they had little to learn from television that could be usefully applied to the movie business… until you pointed out that the future revenue from any movie can easily be predicted from its opening day box office revenues which are ALWAYS an exponential function of the word-of-mouth virality that results from the first impressions of the first audience that views it.  The movie maker is doomed to a never ending treadmill of hits and misses because the viral value of a hit movie which is vital to its profitability is always squandered in a matter of weeks as soon as the highly authored content of the movie has been consumed.  Hence movie studios and console game companies all strive for the Holy Grail “franchise” title that they can constantly recycle in a primitive attempt to capture some of the latent value of their contents social virality.

The post The top 5 things you need to “unlearn” to make great online games appeared first on The Saint.

The purpose of publishing all of this now is of course to ascribe instant and unimpeachable credibility to everything I plan to say about the future of games going forward.  

For starters, I’m not the least bit surprised that the Wii-U flopped, that the the PS4 is likely to flop and without even knowing what Microsoft plans for the NextBox… it has a grim future if it is NOT a mobile device.  Apple has already made the killer next generation game console, any future box somebody makes to sit next to a TV is doomed.  The old retail console market died many years ago, it just takes a while for the corpse to stop twitching and everybody to accept it.  The Arcade game market was generating over 11B/yr in revenue when it died and like today’s console business it took a lot longer for people to admit that it had happened… past tense…

If I had any wisdom to share with Microsoft today, I would tell them to do the same thing now that I told Sony when they sent their CTO to meet with me to advise them on how to compete with the first Xbox.  “Don’t make a new console, you’ll just sacrifice your market-share.  Slap more RAM in the PS/2, crank up the clock rate, stick a LAN chip on it and call it a PS/3.  Use the time and money that saves you to learn how to build an online service.”    Microsoft shouldn’t make another console that isn’t a mobile device, they should slap more RAM and crankup the clock rate on the Xbox360 and call it the next generation, then put their energy into learning how to build a mobile console game business that competes with Apple while they still have a gaming brand, if it’s not already be too late.

The post Tokenomics 2020 appeared first on The Saint.