FairPay Changes the “Game” of Commerce

FairPay literally changes the “game” of commerce — from a series of independent one-time games of individual transactions, to a repeated game of relationship. Modern consumer commerce is built on seller-set pricing of transactions that is optimized for mass marketing to make sales in the short term. (Even recurring subscriptions have pre-set prices designed to get subscribers, not keep them.) That model can now be seen to have two fundamental failures:

  1. Despite the rise of 1:1 marketing, this model has little structural orientation to retaining customers by building long-term relationships that maximize loyalty and customer lifetime value (the games are essentially independent and zero-sum).
  2. Despite the growing prevalence of experience goods, this model gives little consideration to how individual variations in value received can affect the value proposition.

It is our habit to think of seller-set pricing as a given in consumer markets, but that only dates back to the mid-1800’s and the rise of department stores. Traditionally (and still in much of the less-developed world), commerce and pricing were dynamically personalized, based on human negotiation and personal relationships. The strategies of FairPay may seem to go against what we are conditioned to think of as normal behavior relating to price, but, in reality, they merely return us to more natural human behavioral norms (See So Last Century!.)

How FairPay creates a new kind of relationship focus can be seen most sharply in a slight clarification of my older diagram that highlights its structure as a repeated game. This version makes the game as easy as 1, 2, 3 — at the most essential level, it has just three repeating steps:

1. Set the rules (Seller)

Just as in current practice (for mass-marketing), the seller sets the ground-rules of the game. The seller decides to whom to make an offer, on what terms and conditions. That gives the seller overall control. The seller makes the ground-rules clear to the buyer up front, so both parties understand the nature of the game. FairPay is a game that seeks fairness, transparency, and cooperation.

2. Set the price (Buyer)

“Price it Backward.” Reversing traditional practice, with FairPay the buyer is granted the power to set the price — and does that after using the product/service and seeing its actual value in use, and in context (“post-pricing”). The buyer is the one who has direct knowledge of the perceived, realized value in the buyer’s unique context — and after use is when that value is best known and quantified. (Obviously the buyer has selfish incentives to set the price lower than the actual fair value, but FairPay provides a new way to balance that selfish motivation.)

3. Repeat the game? (Seller)

“Extend it Forward?” This seller power is what makes FairPay work to converge on fair prices over the course of the relationship, balancing the power of the buyer to set the price. The buyer knows this is a repeated game, and must consider the consequences when exercising his price-setting power. The seller tracks the price, and determines, in the context of the overall history, whether it seems fair enough to the seller to continue the game for another round. That motivates the buyer to price reasonably fairly. FairPay offers are not always open to all — they are a privilege that can be granted or withheld.

  • Repeating the steps (back to Step 1, with a growing shared understanding)

If the seller pricing is judged fair by the seller, the game repeats, returning to Step 1. At that point the seller can adjust the rules by changing what is offered, under what terms and conditions. If the buyer pricing is judged as generous, more attractive offers may be made. If fair enough, similar offers may be made. If fairness is questionable, more restricted offers may be made, and probationary warnings may be given. Fairness is determined not just from the current transaction, but with consideration to the fairness reputation score that buyer has established over the history of the relationship. If, after repeated tries to nudge the buyer, the seller concludes the buyer is just unwilling to play fairly, the seller may decide that game is not to be repeated further.

  • Ending the game — Fallback to conventional pricing relationship

If the game is not repeated because the seller concludes the buyer is unfair, conventional set-pricing offers would typically be maintained as the fallback option. In any case, the buyer knows that if they want to maintain the FairPay privilege of setting their own price, they must satisfy the seller that they are being at least marginally fair about it, most of the time.

A new kind of balance of powers

The game of FairPay applies a central balance of powers, as seen in the dialectic of the two arrows:

  • Price it Backward reflects the buyer’s power (and privilege) of setting the price after he knows what the product was actually worth to him (unlike the conventional case where he risks buyer’s remorse)
  • Extend it Forward reflects the seller’s power to gate the FairPay offers, to control the rules and to repeat the game or not — to limit FairPay offers as a privilege granted only to those who set prices fairly.

This balance of powers drives convergence toward fair, personalized pricing, in the context of an overall win-win relationship.

This process is participative in that the buyer has real say in the pricing, but the seller still gets to limit their risk, and retain overall control of the business. This participative process ensures that both parties continue only if they agree that the prices are fair. The longer this continues, the closer the prices get to an optimal win-win value exchange.

This participative nature is what gives FairPay real power to enable a company to build a deep relationship with its customers — to achieve high loyalty and sustainable competitive advantage. Instead of a series of largely independent zero-sum games (transactions), we move to a repeated game that seeks win-win (relationships).

Thus FairPay realizes the economic ideal of individually differentiated prices that correspond to the utility and price sensitivity of each buyer, in a way that avoids the feeling of unfair “discrimination.” Unfair price discrimination is a problem of roles and perception — there is nothing inherently wrong about price discrimination (done fairly, it increases our total economic welfare) — if the buyer sets the price, then the “discrimination” is inherently acceptable and fair.

How this changes B2C relationships is described in Harnessing the Demons of The Digital Economy, How it moves us beyond the invisible hand (which no longer works for digital products/services because there is no scarcity to allocate in balance with demand) is described in An Invisible Handshake for The Digital Wealth of Nations.

Playing the game

Of course the first few cycles of a new FairPay relationship may result in wildly unfair prices as buyers and sellers just begin to learn about one another and what value is obtained. But there is little real cost to that initial learning period when marginal costs are near zero — as is the case for most digital products/services. The first few cycles are simply expendable learning experiments in relationship building. Throughout the process, the seller remains in control of how much of which products/services to offer to which customers before prices are set, and so remains in final control how much value to put at risk — effectively limiting “FairPay credit” or value at risk. This is done using the buyer’s fairness reputation score in much the same way as a credit rating.

FairPay creates Win-Win Customer Journeys — With Dialogs on Value. By applying “dialogs about value” during these three steps of the FairPay game (an enriched form of “loyalty loop”) the seller can explain why a suggested price seems fair to them, and the buyer can explain why they disagree and decided to set the price higher or lower than that, and the seller can use that information (plus other data) to determine how fair that price is. (The other data can include measured data on how the product/service was used, and other available data about the buyer and his usage, such as relating to value achieved, ability to pay, etc. All of that data can be used to validate the dialog.)

With transparent dialog, each side lets the other know what they think is fair, and what the other should consider. If they cooperate effectively, they converge toward a win-win relationship based on personalized prices that fairly reflect the actual value to that individual customer. Each side is motivated to build a reputation for fairness in assessing value. If either side becomes convinced the other is simply unwilling to be fair, the game ends. In that case the entire relationship may end, or it may revert to a conventional pricing relationship, based on conventional seller-set pricing.

A scholarly research paper on “The Evolution of Cooperation in Infinitely Repeated Games” observes that “cooperation does prevail … when the probability of continuation and the payoff from cooperation are high enough.” That supports the expectation that FairPay will generally work well if the business makes the repeated game attractive to the customer, and applies reasonable, but not harsh, controls on repetition and FairPay credit outstanding to limit the losses in cases where the customer fails to cooperate. (Some basic background on repeated games is in Wikipedia and Policonomics.) [Update 11/30/16: Very relevant new research paper — see Update note below.]

Some perspectives

Letting the customer set the price after receiving the product/service may seem to businesses as a terrifying leap. But the seller’s power to continue or discontinue the repeated game, and to adjust the rules on each cycle, make all the difference. The seller retains overall control of the game, and manages how much value is at risk. With products that have low marginal cost, the value at risk is small and readily managed.

Many readers will see a similarity to pay what you want (PWYW) pricing in FairPay — but consider the important differences:

  • First, keep in mind that PWYW has proven to be surprisingly effective in some applications. People naturally do want to be fair and generous (up to a point), even when they do not have to. This is well established by a wealth of recent studies in behavioral economics and actual business trials. (See Making Customers Want to Pay You — Research on How FairPay Changes the Game,)
  • The problem with PWYW is that most buyers pay, but many do not pay enough to be sustainable for routine business. Too much unfair pricing behavior can limit the usefulness of PWYW — but PWYW is applied in the form of one-time games that impose no penalty for unfair pricing. .
  • It is the motivation to continue the repeated game of FairPay that turns it into a totally different game — one in which there is a very clear cost to the buyer for being unfair.

Note also that no other B2C pricing method sets prices backward, after use.

  • It is in hindsight that the true, realized value of a product/service becomes known, and that is when the buyer knows enough to set a fair price (especially for experience goods), without discounting for fear of buyer’s remorse. That is also when the seller can see what value the buyer appears to have received, based on actual usage data — how many items did they consume, when, and how.
  • This enables a value-based pricing strategy — much like those that have proven highly effective in B2B contexts — but in a form that is simplified and scalable for mass B2C use.

For more detail on how the process works, and how it integrates with conventional pricing, please see my post with additional diagrams.

Toward a win-win market economy driven by fairness

Throughout most of history, market economies have had a orientation to human relationships that operated as repeated games — apart from a historically short and dehumanizing detour through a regimented form of mass marketing that we have been conditioned to view as normal. Now our digital age presents a new way to restore that win-win human element — one that exploits the scale efficiencies of modern marketing, but that returns individual human relationships and values to the fore.

*[Update 11/16/16: A Value Loop — perhaps the best term for this would be a “value loop,” since we are creating a positive feedback loop that seeks to maximize value. The business sees it as Customer Lifetime Value (a result of loyalty) and the customer sees it as Vendor Lifetime Value (as described in Chapter 23 of my book).]

**[Update 11/30/16: A very relevant new research paper, The Pay-What-You-Want Game and Laboratory Experiments by Matthias Greiff and Henrik Egbert, examines the basic repeated game structure that FairPay applies, and gives strong support to the expectations of success as outlined here. (A blog post expanding on this research is planned.)

— —

— —

For a full introduction to FairPay see the Overview and the sidebar on How FairPay Works (just to the right, if reading this at FairPayZone.com). There is also a guide to More Details (including links to a video).

Even better, read my highly praised new book: FairPay: Adaptively Win-Win Customer Relationships.