Thursday, April 13, 2017

Finding Value in The Subscription Economy

At the heart of the Subscription Economy is the idea that customers are happier subscribing to the outcomes they want, when they want them, rather than purchasing a product with the burden of ownership.
...Nicely put by Zuora, the SaaS platform company that drives many of the largest subscription services. They have popularized the term "subscription economy," and recently created a Subscription Economy Stock Index that highlights the striking growth of such businesses. This is not just a Zuora thing -- as the Oracle infographic to the right indicates.

This fundamental shift toward subscriptions is driven by the nature of our digital environment, and the power of Big Data and the Internet of Things. It is becoming easy to manage ongoing subscription relationships and service delivery -- and to get increasingly rich understandings of actual value received. We are only beginning to recognize how deeply this will transform how we exchange value in commercial relationships.

This post explores the key concepts of value as they apply to subscription relationships -- and as they are are embodied in the pricing of subscriptions. This draws on "value-based pricing" strategies that shift from simple (but less optimal) cost-based or competition-based models. (These are increasingly transforming B2B markets, but have so far seemed less readily applied to B2C markets. FairPay, a new approach to value-based consumer relationships, promises to change that game.) This post shows why shifting toward value-based pricing -- even if only in small, incremental steps -- is vitally important to maximizing the value of subscription relationships -- Customer Lifetime Value (CLV).

[UPDATE 4/20/17:] Think of this is "value discrimination." Marketers and economists think about "price discrimination" as the way to be efficient about getting the most revenue from each customer. But in recurring relationships, what we really want is value discrimination -- finding the optimal value proposition for each customer. Value discrimination involves optimizing not only the price, but the value of the product/service package that is provided for that price.

Value is complex, multidimensional, and highly individualized 

Our digital age has not only driven "relationship marketing" to become deeper and more powerful, but has changed the economic realities of value -- shifting focus from "value in exchange" to "value in use." That is what the opening quote from Zuora referred to, "the idea that customers are happier subscribing to the outcomes they want, when they want them..." We generally do not really want products for their own sake, but as services that produce outcomes. Subscriptions are not a product with a set value in exchange, but a structure for a service relationship that produces a dynamically varying value in use.

Current subscription models drive toward this idea of value-in-use, but do not yet fully embrace it. Our concepts of value and value-in-exchange are still rooted in the old logic of products ("goods"). Value-in-use can not be known until after use. Not only does value vary from subscriber to subscriber and from period to period, but there are many factors involved in estimating value.
  • Is the value tied to the period of access and/or the amount of access (permitted or used)? 
  • Is it per unit of product/service? 
  • Is it how well the service met quality or service-level standards (performance)? 
  • Is it what the experience achieved, what benefits it led to, or how well liked it was (outcomes, whether objectively measured or in customer perception)? 
  • Is it a matter of broader values, like cultural merit or support for social/civic/environmental values (including economic "externalities")? 
  • Is it affordable to me (willingness/ability to pay), and does what I pay sustain creation of more content or services that I desire?
An ideal market system would factor all of these aspects of value into pricing. For example, the value of a content service is not just how many songs or videos or stories I have access to, nor how many I do access, nor whether they arrive without halts or delays, nor whether I play all of an item or hate it and stop, nor whether the service pays its creators and employees, and avoids pollution, nor whether it is priced within my means. Ideally it is a reasonable combination of all of these.

The question is: how well can we do at approaching that, in a way that still creates a good customer experience without undue complexity? In this digital era, we are gaining a wide range of Big Data that bear on understanding value -- data that directly or indirectly provide new insight into:
  • the usage of products and services with detail on what we use, when, and how completely or intensely
  • the performance of what we use and the quality of the experience
  • the objective and subjective results of the experience.
Marketers are already using newly available data to target their offers, and to factor better predictions of value into their pricing. But subscription pricing strategies are just beginning to address the gap between average predictions of value and the widely varying actual experiences of individual consumers. 

Climbing the ladder of value -- profiting from more win-win relationships

Consider the range of approaches to price that we commonly see in practice and how they track to value. Keep in mind the fact that value in use, the outcome of a service, is difficult to predict in advance, and varies from customer to customer and time to time -- and so is best assessed after use, when the outcomes are known. There is also the problem that important subjective value perception data arises from within the head of the consumer -- that aspect of value can be hard for the business to know, even after the fact.

Uncertainty in quantifying value realization forces us to address the related question of who takes on pricing risk? This has important implications. How much use will I get from my subscription? Must I lock in a package rate to get a volume discount, and then have to wonder if I will use enough of the package to get the value expected? What if I use it, but am disappointed?
  • Pre-setting prices puts the pricing risk on the consumer (causing many to refuse to take the risk at all, resulting in lost revenue), and often leads to disappointed customers (which hurts customer retention, thus reducing future revenue).
  • As practitioners of value-based pricing recognize, offloading pricing risk from the customer is a service, and one that can increase sales and loyalty. Think of it as pricing-risk-management as a service.
  • For digital services (which typically have near-zero marginal cost for unlimited replications), businesses have little to lose by taking on pricing risk (as long as they manage that risk effectively).
Both parties suffer when services are priced in a way that a) poorly correlates to the value the customer receives, and b) forces consumers to take on unwanted pricing risk. Specific strategies can be understood in terms of how they combine three aspects of pre- (versus post-) pricing risk:
  1. Pre-set packaging of an assortment or bundle of items or services in a subscription. Do you have run-of-the-house access to a full range of items or services to choose from, as you decide you want them, or must you choose a specific assortment or bundle in advance? This comes up when you subscribe to TV channels in bundles, or to NY Times news plus crosswords, or support a museum or a musician on Patreon, and choose from multiple packages with different perks at different prices. Do you know in advance what combination you will want and how you will value it?
  2. Pre-set usage levels. If you subscribe to a service, does the price depend on how much you use it, building in volume discounts? Other things being equal, a customer who uses many articles, songs, programs, or whatever, per period will presumably get more value than one who uses only a few. Does the price reflect that? Unlimited usage plans do not -- so heavy users get a bargain, and light users subsidize them (and may not find it worthwhile to subscribe at all). Beyond that, usage-related pricing generally tracks better to value when it applies volume discounts, as with mobile data plans, and TV channel bundles. (Such prices can vary a unit at a time, or be fixed within set usage bands.) Volume discounts can factor in both diminishing returns to the customer and economies of scale to the supplier. 
  3. Pre-set price schedules. Even when pricing depends on usage, and offers volume discounts, that usage is most commonly priced using a pre-determined price schedule, which presumes some average quality of outcomes. More advanced value-based pricing approaches can allow the price schedule, itself, to depend on actual outcomes. For example, the price of an article or song or video may depend on the value I actually get (/perceive) from it. One simple example is when a sales commission depends on the price obtained for the sale. Outcomes pricing is generally not done in current consumer subscription plans (but is a feature of the new FairPay strategy).
Whatever the particular form of pre-pricing, the business must try to predict pricing levels (/tiers/packages) that work on average, but will inevitably work poorly for the many consumers who diverge from the average in one way or another. To the extent that such pricing decisions can be deferred, greater price discrimination can be achieved in a fair and transparent way. That leads to better economic efficiency, higher profit, and happier customers.

More detail on "Understanding the rungs on the ladder of value" is provided in the sidebar below, but to cut to the chase...

Maximizing CLV and Value Experience

The established wisdom of subscription economy businesses is that it all about Customer Lifetime Value (CLV). The problem is that this is generally viewed from a one-sided perspective -- value to the vendor. But value to the vendor is maximized when the relationship is win-win. It is a matter of fair balance -- maximizing CLV requires equal attention to how the customer values the relationship: Vendor Lifetime Value (VLV).

  • It is costly to acquire customers, and therefore it costly to lose them and have to replace them -- recurring revenue models work best when the revenue recurs. 
  • Customers are retained when they feel they are getting good value for their money -- for what they really want. That is especially likely when they feel the business is listening to them, understanding what they value, and seeking to deliver that at a fair price. 
  • To the extent that we can migrate toward pricing methods that offer better mappings to value-in-use, customers will be happier and more loyal, and move toward maximum CLV (and VLV).

It is easy to get lost in the mechanics of pricing and subscription models (which are complicated and full of compromise) and lose sight of the underlying goal -- to find a right price, for each customer -- a price that each customer will view as fair compensation for the value they seek. We are so used to the compromises and nasty zero-sum games that are the dark side of the past century of mass marketing, that we often descend into a cycle of exploitation on both sides. Businesses treat the consumer's perception of the total value proposition as something to manipulate and exploit, and, as a result, consumers distrust businesses and try to "hack" them. But as businesses become "customer-first" and oriented to "customer experience" (CX), we see that what really matters is cooperating in a joint, effort to co-create value, to maximize "value experience" (VX).

A few decades is a long time in our personal lifetimes, and that makes it is easy to forget that we are still in the infancy of the digital era, with many deep changes yet to come. But we do see that a few decades into the digital era we are still in a time of continuing disruption and turbulence. As Peter Drucker said, "The greatest danger in times of turbulence is not the turbulence, it is to act with yesterday's logic." Moving toward value-based post-pricing will move us toward tomorrow's logic -- to reduce the cost and risk in how poorly prices track to value. It is that new logic that will fully realize the value in the subscription economy.

Sidebar:  Understanding the rungs on the ladder of value

A more detailed view of how this plays out in subscription pricing plans is outlined in the following list (drawing on an earlier post). Looking at this progression, ordered roughly in accord with the degree of value-based post-pricing, it becomes apparent that we are only at "the beginning of the beginning" of our evolution toward a commerce for the digital era.
  • Unit sales of items (pre-priced). This is the pre-subscription base case. Examples are song/album, video, e-book, and article ownership downloads (with or without cloud repositories). This is simple and easy, but tracks to value only on average -- and as predicted, not as realized. It is a bargain for heavy users of specific items, but costly or prohibitive (and a management problem) for light use of many items.
  • All You Can Eat (AYCE), unlimited subscriptions (pre-priced). The common model of all the items you want, time-limited to periods of subscription. This too is simple and easy, but has similar kind of unfairness and inefficiency -- still tracking to value only on average (overpricing light users and underpricing heavy users), and considering value only as to the predicted average experience, not the value-as-realized. Many potential subscribers who are unsure of the value or how much they will use (or expect it will not be much) are disinclined to subscribe. Often referred to as paywalls (with all the exclusionary connotations of a "wall,") these also include tiered variants with levels of premium access, including freemium versions that begin with a free tier (but still place a paywall at some pre-set premium level). 
  • Membership models (pre-priced). These are a form of subscription with a more cooperative, participative orientation, such as for publications, artists/creators, or museums -- sometimes using crowdfunding platforms like Patreon or Indiegogo. These may seem more voluntary than hard paywalls, and often include tiers or bundles that include different levels of perks, but still have pre-set prices for given levels of service (see pre-bundling, below, and note that these perks, such as T-shirts and tote-bags, are often gimmicks of questionable value).
  • Partially usage-related subscriptions (pre-priced for the most part). These improve on unlimited models by adding usage-related tiers, such as for varying levels of mobile data service, how many TV channels are viewable in a bundle, or how many DVDs or e-books you can have out at one time. In most cases not only are the price schedules pre-set by the seller, but the customer must pre-select which specific tier or bundle they want. These can track better to value, in terms of usage, but only based on pre-defined units of usage -- without considering the experiential value of that usage.
  • Fully usage-based subscriptions (pre-priced schedule applied to actual, metered usage). Currently, these are most widely accepted in B2B, such as jet engine "power-by-the-hour" and fleet "tires-by-the-mile." These have also been used for B2C, such as the old "per-minute" charges for mobile phone and dial-up Internet services. Consumers often dislike these plans because of the unpredictability of both usage and value, and the relentlessness of the "ticking meter." However, in some B2C uses the tracking of usage units to value can be quite satisfactory. Tire miles and engine hours are manageable and serve as a good estimator of the broader business outcomes.
  • Pre-bundled subscriptions (pre-priced menu). These can be forms of any of the above in which the customer is given a set menu of options (pre-set, tiered packages) to select from at pre-specified prices. The use of tiers and packages with appropriate volume discounts leads to a better fit to value (for the tier or package), but in a very static way -- it forces the customer to select a tier or package before knowing if they really want it and will find value in it, and sets the value based on predicted averages, not actual value in use.
  • Post-bundled subscriptions [new] (post-priced in part based on actual usage -- but still based on pre-set volume discount schedules). This is an enhancement of conventional subscriptions that I have proposed, such as for TV services, that offers discount prices at levels comparable to current TV bundles, but with the composition of the bundle set after the fact, so that customers can watch whatever channels they want, while still benefiting from a bundled-rate discount. This can track significantly better to value as it varies from customer to customer and month to month. It does not directly address outcomes (did you like that program?), but refund options can be provided (for each program view) to add a degree of outcomes tracking (duds are free).
  • Performance/Outcomes-based pricing (post-priced based in part on actual usage, with a price schedule that is based on performance or outcomes). This goes beyond usage alone, to factor in the quality or result of that usage. Performance-based pricing is common in digital advertising (clicks, leads, transactions) and other B2B markets. Outcomes-based pricing takes that farther up the value ladder, and is increasingly applied in healthcare (where the price schedules are typically set in advance, based on prior results in test populations). Of course it would be more desirable to base the schedule (at least in part) on actual individual customer outcomes, where that is feasible (pay if cured). 
  • Soft values as pricing factors (pre-priced or post-priced). This adds consideration of broader values in the overall experience, like cultural merit or support for social/civic/environmental values. Conventionally, this is rarely an explicit factor in pricing, but some aspects are increasingly implicit in prices, in the form of a tacit understanding that consumers are OK with paying a premium for goods and services that support broader human values and/or are produced and delivered in socially responsible ways.
  • FairPay subscriptions (/memberships) (post-priced, with price schedules set after usage). This is the new value-based strategy that shifts to an adaptively cooperative process for "dialogs about value" that get finalized after usage to create the best practical approximation of price to value in use. (FairPay also applies elements of participatory pricing to optimally factor in the customer's perception of value-as-experienced.) FairPay is designed to co-exist, at whatever level desired, with the other methods above, and to be able to subsume them in a flexible architecture for collaborating on value and price (co-pricing). More about FairPay and how it can adaptively seek the best of all of these approaches is addressed elsewhere in this blog. It is not yet clear how widely applicable FairPay will be, but it points to many aspects of deeply value-based strategy that will almost certainly be important in one form or another.

(Other posts in this blog have explored many aspects of the subscription economy, and how FairPay offers a path to a next generation of more profitable subscription relationships. Recent posts explained how and why the FairPay strategy adapts the "value-based pricing" approach that is increasingly transforming B2B markets, but has so far seemed less readily applicable to B2C markets --and how FairPay's new approach to consumer relationships can change that game.)

For a full introduction to FairPay see the Overview and the sidebar on How FairPay Works (just to the right, if reading this at 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.

Thursday, March 30, 2017

Foreword, by Adrian Payne, to my new book on FairPay

Adrian Payne -- one of the foremost authorities on Relationship Marketing and CRM -- wrote a Foreword to my new book that serves as an excellent overview.

Adrian is author of fourteen books, including the first text to be published on Relationship Marketing (1993), and most recently, Strategic Customer Management: Integrating Relationship Marketing and CRM (2013). He is Professor of Marketing, University of New South Wales Business School, Australia and Visiting Professor, Cranfield School of Management, Cranfield University, UK, and has extensive senior management experience. Adrian has been influential in my work on FairPay, and I thank him for many valuable suggestions during my writing.

The full text of his Forward is online.  Here is the opening paragraph:
Enterprises everywhere are recognizing the need to become more customer-focused, but struggle to determine how to achieve this. This compelling book explains how a new innovative approach to pricing—“FairPay”—can help achieve this goal through a radical shift in considering how to price products and services. Pricing is not an area that executives consider with great excitement, yet the approach outlined by Richard Reisman promises to be transformative both in practice and theory. It is likely to receive great interest from enterprises, especially those offering digital products and services where the marginal cost of producing a further unit is close to zero. (More...)
I hope you will read his Foreword -- and my book -- and join us to change how we do business in the 21st Century.

Other early praise:
"Anyone responsible for monetizing digital content in consumer markets should understand this radically new perspective on pricing and how to maximize customer lifetime value. FairPay provides strategies and operational methods for creating better relationships -- to increase loyalty, market reach, and profits." - Shelly Palmer, Business Advisor, Author, Commentator 
"Reisman unveils a new world of possibilities through an innovative and visionary methodology that introduces a reference platform for digital value exchange. FairPay is very versatile in its applications and compatible across industries. It is a great example of what disruption could look like in a new digital business era." - Lucila Pagnoni, News Corp Australia 
"FairPay boldly explores the future of pricing from a co-creation of value perspective. Highly recommended for digital business entrepreneurs, as well as established firms working on their digital transformation." - Jim Spohrer, IBM and 
"A groundbreaking and definitive book on pricing strategy for the digital age. This highly innovative and practical work shows how enterprises can develop relationship-based pricing strategies leading to long-term customer relationships, based on principles of equity and fairness for both customer and supplier." - Professor Pennie Frow, University of Sydney Business School
Order the book now from:

Tuesday, March 7, 2017

Value-Based Pricing Is Transforming B2B -- Now for B2C...

"There is broad consensus...that a pricing orientation based on customer value and customer willingness-to-pay is best and can positively influence pricing power and firm performance." -- Journal of Revenue and Pricing Management
FairPay is a new way to do value-based pricing -- in which prices are set based on the actual value realized by each individual consumer -- with a fair share of the value surplus going to the provider.
  • Value-based pricing has proven transformative in B2B contexts. It is becoming accepted as best-practice, where feasible, even though this approach has been largely unknown in consumer markets. 
  • Now FairPay provides a lightweight way to exploit the economics of digital to achieve similarly transformative win-win results, in a way that is suitable for many mass-B2C businesses (especially for digital content/services).
This post provides background on what value-based pricing is, and shows how and why it is increasingly transforming businesses in the B2B space. It explains why it has generally not been relevant for B2C businesses, and how FairPay provides a new variation on this theme that is specifically suited to consumer markets. (Links to authoritative references are provided -- it is strongly recommended that any manager with revenue responsibility understand this increasingly important new perspective on strategy.)

New pricing strategies can drive business design and disrupt markets

Before jumping into the details, let's be clear that these ideas go far beyond the narrow "green-eyeshade" confines of pricing that many managers tune out. Pricing is an often neglected aspect of strategy, given little attention or respect. But pricing can have huge impact on profitability, and value-based pricing has proven that it can transform fundamental business models and organization structures. It can drive design thinking in ways that improve customer relationships, disrupt competition, and reshape markets. As Peter Drucker said, "The greatest danger in times of turbulence is not the turbulence, it is to act with yesterday's logic." In these times of turbulence, pricing is too important to be left to the pricing specialists. 

Value-based pricing -- seeking optimal value exchange

The terms value-based, performance-based, outcomes-based, and success-based are often used for variations on the same basic idea. (I use the term value-based, for breadth and simplicity, since performance, outcomes, and success are aspects of value.) These all differ from more conventional cost-based (cost plus markup) and competition-based (what the market will bear) pricing orientations, which are widely used, but are more simplistic and generally less effective.

My particular emphasis is on post-usage assessments of value, which are central to individualized, in-context experiences of value -- these are most important to quantifying the true value to a given customer (especially for experience goods). The term value-based pricing is also used for less collaborative, pre-usage pricing variants that are based on generic predictions of value. That is a step in the right direction, but generic predictions are just expected averages, and thus a poor approximation of post-usage measurements of value, as actually realized by any given customer.

Value-based pricing seeks to approximate the ideal of perfect price discrimination, which captures maximum revenue from every customer (including many who would otherwise not actually become customers at all). As currently applied, experiential value-based (post-) pricing has generally been impractical in consumer markets, but it has proven very effective and efficient for industrial items or services. For post-pricing based on value, the challenge has been that this requires 1) that the parties can agree on how to measure value as it is experienced in context, and how to share in the value surplus that the product/service creates, and 2) that they able to do the analysis that requires, after the performance and outcomes are known.

While this had limited where value-based pricing has been applicable, it is widely accepted that digital transformation is rapidly expanding that applicability.

The following sections address how FairPay simplifies this process to make a new kind of value-based pricing practical for consumer markets, but first, let's look at the evidence of why this is so important.

Powerful lessons from the B2B world

The current special issue of the Journal of Revenue and Pricing Management is devoted to value based pricing -- its editorial observes (emphasis added):
There is broad consensus among pricing scholars, consultants, and practitioners that a pricing orientation based on customer value and customer willingness-to-pay is best and can positively influence pricing power and firm performance...More stories of successful transformation are being presented at pricing and business conferences. More firms are piloting value-based pricing with specific projects and technology platforms. 
One of the articles in that issue, The conceptualization of pricing schemes: From product-centric to customer-centric value approaches (by Stoppel and Roth), provides a conceptual structure and a survey of practice to show how this can "strengthen the relationship between customer and provider" and provide numerous mutual benefits.

Helpful background on why this is so powerful is contained in Is Performance-Based Pricing the Right Price for You?, a 2002 paper from Harvard Business School Working Knowledge (emphasis added):
Not every industry or company can benefit from performance-based pricing. But where there is a fit, PBP can be a powerful tool that merges the interests of buyers and sellers, says Harvard Business School professor Benson Shapiro.
Because pricing is such a difficult and complex arena, it has confounded sales and marketing executives and scholars for centuries. In no other marketing element is the two-sided conflict and cooperation nature of the buyer-seller relationship made so clear.
Part of the relationship is a zero-sum game between buyer and seller in which one's gain is the other's loss. Pricing is at the center of this part. But, there is a second, win-win part of most buyer-seller relationships, including almost all business-to-business relationships. The win-win part often includes improved products and services that simultaneously provide greater customer value and higher supplier profitability. We constantly strive to move elements of the relationship from the zero-sum conflict side to the win-win cooperation side to achieve business success and relieve personal angst on both sides. We have searched for ways to move pricing into the win-win category. In some situations, performance-based pricing can make pricing a win-win element of the buyer/seller relationship.
That paper goes on to give many examples, noting its popularity in advertising, as well as "industries as diverse as consulting, trucking, and heavy industrial services." It cites three advantages:
  1. "alignment...between the buyer's goals and the seller's goals
  2. "insurance...when the final performance of the service or product is in doubt," creating "a greater sense of 'fairness' for both buyer and seller" 
  3. "the very process...develops 'wide-band width" communication between buyer and seller...a great deal of buyer/seller cooperation and coordination and literally a much broader agreement.
The downsides cited by Shapiro are that it "is complicated...the amount to be paid can not be determined until after delivery, and often even after usage' and that this "moves both the cost and price risk to the seller," (and that "it is not good for sellers who desperately need short-term cash flow"). It is this complexity that has kept such approaches out of B2C markets until now.

But Shapiro also observes that "the vendor then obtains the opportunity to better manage the spreads among value to the customer, price, and cost to its advantage. With risk comes added opportunity. The vendor who uses performance-based pricing must thus be willing to accept greater, two-sided (price and cost) risk for added reward opportunity." These are advantages that I have highlighted as the motivations for FairPay. This idea of opportunity coming out of risk is important, and is addressed further in the last section.

Additional interesting background that reinforces these points is in the chapter "Pay if it Works" in Smart Pricing, by Raju and Zhang of the Wharton School, and a more recent HBR article

This trend relates to the ideas described in my post, Price = Value, based on the growing acceptance that value derives from services, not goods (even if it is a service that is embodied in a good) -- and that companies can profit from that by setting prices based on the value of their services, not just the goods that they are based on. There have been many successes. Perhaps most familiar to people in content businesses are performance-based advertising pricing models, such as the shift from cost-per-impression to cost-per-click to cost-per-lead or cost-per-action. But industrial services provide many illuminating examples. For example, Rolls Royce profited from realizing that it need not sell jet engines as commodities, but could get more share of wallet and make its customers happier by selling "Power by the Hour," where the airlines pay for what they use, and leave it to Rolls Royce to manage high capital investment and critical maintenance efforts. GE and others now do the same. Michelin now sells tires by the mile to fleet owners.* There have been many more successes, including the example of Salesforce, which uses customized value-based pricing for its large accounts (as reported to me by the executive who managed development of that pricing system a decade ago). An important example where outcomes are increasingly viewed as an essential basis for fair and efficient pricing is in healthcare. (The Stoppel and Roth paper cited above provides additional examples.)

The advent of Big Data and the Internet of Things (IoT) is making this more feasible and effective in a much wider variety of businesses, as described in a 2014 HBR article. Value can be measured in any appropriate manner, reflecting usage, performance, outcomes, and other factors. (I addressed the similar potential for big data about content service use in an earlier post, "E-Books Are Reading You" -- How That Enables a New and Far Better Economics.) 

Value to the consumer! -- a win-win game

Now FairPay takes the principles of the value-based pricing and applies them in a lightweight and intuitive form to consumer markets. In doing this, it can flexibly blend desirable features of other pricing models in a new paradigm. It combines aspects of freemium and participatory pricing (along with post-pricing) in a new way -- one that gives buyers and sellers evenly balanced power to set individualized fair prices in "dialogs about value" -- a collaboration over time that can consider all of the relevant dimensions of value and fairness. Its assessments of value may at first be crude, but because of its continuously adaptive learning process they can be good enough, and get better, on average, as the relationship develops over time. (It also gets more seamless and habitual after a short initial learning period.)

Shapiro's paper nicely points out the zero-sum versus win-win game aspects of buyer-seller relationships (as quoted above). FairPay is based on just such a view, working as a repeated game that seeks win-win cooperation over the course of each relationship. The details of that game are described in my post, FairPay Changes the "Game" of Commerce, and how it works in various industries is outlined throughout my blog. A conceptual perspective on why this is important and how the value surplus can be shared fairly is in my post, An Invisible Handshake for The Digital Wealth of Nations.

Drawing on the conceptual model of Stoppel and Roth, pricing schemes have two key components: measurement units (that provide a basis for pricing), and calculation mechanisms (effectively the pricing rates that derive a monetary amount based on the units). These elements can be addressed in systematic ways in the large B2B contexts where value-based pricing has been successful, but are a challenge for B2C markets. The breakthrough of FairPay is to recognize that the individual relationships in B2C markets operate at a more subjective, intuitive, heuristic level, and that we can exploit computer-mediation to design the pricing game to operate at that same level.
  • FairPay is not the same as traditional person-to-person negotiation, but both operate at a similar and appropriately subjective, intuitive, and human level. 
  • The choice of measurement units and pricing mechanisms can be flexible and dynamic, because cooperation is centered on fuzzy aggregate values where these details are merely reference points for justifying an approximate valuation that is intuitively agreeable. 
  • The business can accept some degree of transaction-level valuation errors (given the low marginal costs), as long as the overall trend of the relationship leads to fair and sustainable profit. 
FairPay pricing is emergent out of fuzzily approximate dialogs about value that converge toward reasonable accuracy and fairness. This has strong foundations in behavioral economics, as explained in Making Customers Want to Pay You -- Research on How FairPay Changes the Game and Thinking Fast and Slow about FairPay: A New Psychology for Commerce in a Networked Age

It is this embrace of fuzziness and emergence that enables FairPay to find a solution that transcends rigorous computational models to cut through the dilemma of unlimited all you can eat (AYCE) models versus metered usage-based models, both of which are inefficient and have consumer acceptance issues.* By accepting pricing risk (which is actually very manageable for digital services), FairPay opens vast new opportunities to collaborate, build loyalty, and upsell -- to maximize Customer Lifetime Value (CLV).

The competitive advantage of taking on risk

Expanding on the observations of Shapiro noted above, an article in the current issue of PWC Strategy+Business, The Uncertainty Advantage, notes that "Creative leaders don’t fear risk — they turn it into a money-making strategy."
There is no better source of profit than your ability to first identify the opportunity hidden in disruptive forces and then use it to differentiate your company from its competitors.
Post-pricing based on individual value is such an opportunity. FairPay recognizes that in a digital world, service providers risk little by taking on pricing risk, because their marginal cost of service is near zero. They can provide  a big win for their customers -- by taking on the customer's risk of disappointment, at little risk to themselves -- and thus create a big win for themselves.

FairPay can help us move from thinking narrowly about user experience (UX) and customer experience (CX) based on rigid, imposed pricing models, to the more central and win-win issue of value experience (VX). Notice that UX and CX consider the perspective of the user/consumer, but they do so with the the idea that the UX/CX is to be managed by the vendor (and with the vendor's unilateral price setting power). VX looks at this from the broader perspective that value is something that neither party owns or fully controls, but is something that both co-create and share in cooperatively. With this central focus on value experience, we can then find ways to cooperatively look beyond conventional notions of pricing, to change the nature of our business models, and make them more win-win.

Which is more win-win way to think about pricing? Which gives your customers a truly "customer-first" experience of value? Which will make your business most sustainably profitable? Isn't it time to give it a serious try?

Some other discussions of value-based pricing on this blog:
For a full introduction to FairPay see the Overview and the sidebar on How FairPay Works (just to the right, if reading this at 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.

*Note important distinctions between models based on actual usage, such as power by the hour and tires by the mile, versus those based on potential usage, such as the all you can eat (AYCE) subscriptions that are becoming dominant is content sales (news, music, TV/video), as described in the Deadweight Loss post. Actual usage is a form of post-pricing, and thus tracks moderately well to realized value, while AYCE access subscriptions are pre-priced, with no correlation to whether usage (and thus value) is high or low. 

At a next level of refinement, actual usage is still not an ideal metric of realized value, especially for experience goods. For jet engines and fleet tires, hours or miles (respectively) will usually correlate well with value, but for news stories or videos, the number of stories or number of programs (or minutes) may not correlate very well with realized value at all. That unforgiving "ticking meter" is why conventional usage-rate-based pricing of content (pay per view and micropayments) has remained unpopular with consumers. The "subscription economy" moves us closer to actual value than an ownership economy does, but the measurement of subscription value is the key challenge in making pricing truly value-based and win-win. That is why FairPay (with its fuzzy, value-based blend of AYCE and usage pricing) can make all the difference.

Thursday, February 16, 2017

Profiting from Habit -- Seamless Monetization

Marketers increasingly recognize how essential habit and seamlessness are. "How to Win and Keep Customers" is the cover theme of the current Harvard Business Review -- the lead article says to focus on habit, not loyalty, while others say that "habit is how we build the connection" and "habit beats novelty."

Some people question whether FairPay is seamless enough, and whether it goes against habit, but I suggest that, done right, it actually builds a stable, self-adjusting relationship based on habit in a way that is natural and largely seamless.

Habit and subscriptions

Subscriptions are about as habitual as commerce can get. The dream of many subscription marketers is to get customers to subscribe, put them on autopay, and hope they never think about it again -- pure habit. Not even "thinking fast" as Kahneman called it, but not thinking at all.

But the reality of the subscription habit is not really so simple -- and poses financial risk to the subscriber. Seamlessness requires not just absence of effort, but absence of risk.
  • Especially for unlimited digital subscriptions, customer usage -- and value -- varies not only from customer to customer but also from period to period. 
  • Many customers are often nagged by the feeling that they are paying too much for a service they no longer find worth the price (and may not be using). 
  • A price that sustains lack of thought from one customer at one period may not do so for another customer -- or for the same customer, for a different period. 
  • Perceived value fluctuates, and when it goes below a threshold, the dreaded cancellation request arises. 
  • Then things get hairy, as previously profitable customers may or may not be coaxed to stay. 
  • Both businesses and consumers spend great cognitive effort (and service agent time) negotiating whether to cancel, or agree on some customized retention offer -- and if successful, that just kicks the can down the road a bit. 
No matter what your subscription price, there are problems.
  • If the habit does not fail for many customers, the question is why not? Is it because your price is so far below the pain point that you are leaving money on the table for most of your customers? 
  • Whatever the failure rate, what about the unseen base of the iceberg?
    ...those who do not subscribe because the price seems too high?
    ...the many customers who don't even consider subscribing because of fear they will regret it?
    ...those who decline even a free trial, because they do not want to have to remember to opt-out? (That barrier is reinforced by the consumer-hostile "roach motel" policy of most subscription businesses that make it painfully difficult to cancel.) 
So what seems a nicely mindless subscription process actually works rather crudely, and not always so mindlessly. (See Winning Back Lost Customers -- Before They Get Lost.)

At the same time, keep in mind that for some customers, seamlessness is not the issue. An important segment of consumers enthusiastically embrace behaviors that are far from seamless. Some consumers willingly bear punishingly high cognitive loads -- some in various forms of bargain hunting (such as to maximize credit card bonuses and airline rewards), others because they are "superfans" and actually want to be deeply involved.

Habit and FairPay

The new FairPay relationship strategy entails a learning curve that may seem burdensome, but it is risk-free, and once established, it can be simpler than conventional subscription (or membership) processes.

When managers consider FairPay, a common initial concern is that it is unfamiliar, and that it imposes a new cognitive burden on the customer. The burden is in the cooperative discovery process that leads to personalized prices, based on dialogs about value (and price) with each customer. In principle, that process is adaptive, forever. That may sound like a formula for a lot of "thinking slow," something humans try to avoid, and marketers rightly wish to help them avoid.

But that is not the full picture, for two reasons. The first, as explained above, is that the seemingly mindless subscription process often fails and becomes burdensome. It involves not only cognitive effort, but financial risk.

The other reason is that FairPay actually can become habitual, and ultimately become an even simpler habit than a conventional subscription (even when that subscription is working reasonably smoothly). As a buyer and seller gain familiarity and gain a shared understanding of received value, the FairPay seller can adapt the process to create a level of confidence and trust in its workings that reduces the cognitive load:
  • After a short learning curve, the seller's algorithms can begin to predict the value that the buyer sees, and can suggest prices that the buyer will generally be satisfied with. These suggested prices can use predictive and anticipatory analytics and machine learning to reflect the dynamics of value, as perceived by the buyer -- reflecting how many and which items are consumed, with what intensity, and with what results -- and that can be shown in the usage report that goes with each pricing request.
  • The buyer sees the progress of that learning as it emerges, and becomes increasingly comfortable that the seller's pricing suggestions are becoming properly personalized to reflect their usage and values. Such dynamic suggestions can become far more aligned with perceived value than any fixed subscription fee.
  • Once that comfort level emerges and is sustained for a while, the buyer can simply put the process on autopilot (using autopay, just like a conventional subscription). The difference is that the buyer always has the option to review recent charges, and can go back to make a unilateral adjustment any time they might feel those prices are out of line for a given period. That can be a one-time adjustment, or can trigger a deeper re-calibration of the personalized pricing process.
  • This process eliminates financial risk to the subscriber -- an important aspect of seamlessness. Customers need not fear subscribing under FairPay, because there is no roach motel -- they will not be required to pay by default, to pay for services they do not use, or to remember and go through hoops to cancel a service they no longer want. 
Because this adaptive learning can become largely automatic, with just occasional re-calibrations, this can actually become just as simple and impose no more cognitive load than conventional subscriptions. Done well, it can actually become more seamless.

And, perhaps more importantly, with a FairPay relationship, there is no financial risk to fear -- consumers need never doubt that subscribing is worthwhile, because they share in the power to set the terms, expending as much or as little effort as they deem worthwhile..

Easing the learning curve

Of course this is a new method of doing business, so early uses will not go as smoothly as they will after businesses and consumers have gained a good understanding of how to use it effectively. So for early uses it is important to be careful to select lines of business and customer segments where it is likely to work well, and where some cognitive load will be tolerated. Suggestions on how to do that are in a companion post, Finding Good and Fair Customers -- Where Are the Sweet Spots?

FairPay is a new pricing method that reduces risk, but involves joint learning. It will not be simpler for all people, all of the time. But it promises to reach a level of habit that will be simpler for many people, most of the time. And as businesses and consumers learn to use it effectively, it will be simpler for more people, more of the time. And that will generate greater CLV, from a wider market.


For a full introduction to FairPay see the Overview and the sidebar on How FairPay Works (just to the right, if reading this at 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.

Tuesday, February 7, 2017

"Subscription-First" ...Why Not Subscriber-First???

"We are, in the simplest terms, a subscription-first business," said The New York Times in its 2020 Report -- an admirable examination and re-dedication to its premier journalism.

But what is missing in this picture? In an age where businesses of all kinds are realizing that their path to success is to go beyond "customer-centric" to become "customer first," is the Times thinking about becoming "subscriber first?"  What they refer to as subscription-first is recognition that the subscriber (not the advertiser) is the customer they must center on. But are they pushing beyond subscription-centric to subscriber-first? Perhaps to some extent, but I have suggested to the Times (and their competitors) that the business of journalism must focus more directly on how business model innovation can facilitate that.

A nice explanation of this difference is in a recent report from MarketingSherpa: "to come alongside customers and help them achieve their goals versus only driving them towards business goals."
A shift from...
Customer-Centric Marketing — aiming at the customer
Customer-centric marketing puts the customers at the center of marketing; all promotions and messaging flow towards them in the way that is most relevant to them. Marketers put themselves in the customers’ shoes to sell to them better.
Customer-First Marketing — elevating the customer
Customer-first marketing uses the customers’ goals as the compass to make decisions about marketing approach. They put the long-term interest of the customer above the short-term company conversion goals. Marketers put themselves in the customers’ shoes to serve them better, thus building a long-term, sustainable competitive advantage. 
It does not appear that the Times has this deeper shift in mind. This may seem a fine distinction, but it can be made operationally important. FairPay is a new strategy for subscriptions that are truly subscriber-first at the core. It focuses all aspects of the business on value as each subscriber perceives it, and does that in the most direct way possible -- by involving the subscriber in setting their subscription price.


The new Times report, Journalism That Stands Apart: THE REPORT OF THE 2020 GROUP, begins with this near the front (emphasis added):
We are, in the simplest terms, a subscription-first business. Our focus on subscribers sets us apart in crucial ways from many other media organizations. We are not trying to maximize clicks and sell low-margin advertising against them. We are not trying to win a pageviews arms race. We believe that the more sound business strategy for The Times is to provide journalism so strong that several million people around the world are willing to pay for it.
It goes on in a later section:
3. We need to redefine success.
The newsroom has embraced data and analytics over the past year, with positive effects. We now have a better sense for which of our work resonates with readers and which does not. We’re producing more resonant work, and we have largely resisted the lures of clickbait.
Now we need to take the next steps. The newsroom needs a clearer understanding that pageviews, while a meaningful yardstick, do not equal success. To repeat, The Times is a subscription-first business; it is not trying to maximize pageviews. The most successful and valuable stories are often not those that receive the largest number of pageviews, despite widespread newsroom assumptions. A story that receives 100,000 or 200,000 pageviews and makes readers feel as if they’re getting reporting and insight that they can’t find anywhere else is more valuable to The Times than a fun piece that goes viral and yet woos few if any new subscribers.
The data and audience insights group, under Laura Evans, is in the latter stages of creating a more sophisticated metric than pageviews, one that tries to measure an article’s value to attracting and retaining subscribers. This metric seems a promising alternative to pageviews.
Yet the newsroom should also understand that no metric is perfect. To a significant extent, we will need to rely on a mix of quantitative measures and qualitative judgments when deciding which stories to do and to promote. Achieving the right balance is tricky. We neither want to equate audience size with journalistic value nor do we want to return to the days when we persuaded ourselves that a piece of journalism was valuable for the mere reason that it appeared in The New York Times.
Subscriber-first -- its all about value to the subscriber -- in terms of the subscriber's goals

The Times seems focused on the value of its reporting to subscribers, but it is not clear that this looks beyond their own objective of "attracting and retaining subscribers." A true customer-first strategy would focus the Times on understanding the value they provide to each subscriber, in terms of that subscriber's goals, and using that to drive decisions. There may be limits to the extent to which this guides editorial, but it should guide product development, business, and marketing decisions. FairPay is a strategy for subscriber-first pricing that can drive all other aspects of the business.

The Times is already moving in the right general direction. They can follow their subscription-first path and seek to maximize revenue by just getting smarter about their goal of getting people to subscribe and stay subscribers. They refer to "more sophisticated metrics." A nice summary of methods they may apply is in David Skok's recent NiemanLab prediction: What Lies Beyond Paywalls (see my comments on that: What Lies Beyond Paywalls -- A Better Way).

The problem is that this is still aimed at the publisher's goals, not the reader's -- trying to psych out the reader, to understand how to better align prices they impose with the value the reader perceives, to get and keep more subscribers. But the reader has unique access to their personal perception of value (as it relates to their goals). Current processes do not involve the reader in real dialog that can expose those perceptions (or their goals) directly -- and signal that the publisher cares about them.

A truly customer-first, subscriber-first strategy would involve the subscriber in measuring value -- from their personal perspective. The FairPay strategy suggests a way to do this (at least for a segment of cooperative subscribers) is to involve the subscriber in setting the price of the subscription, and letting that price vary over time. Only by doing that can the price truly correspond to value -- as it varies from subscriber to subscriber and from period to period. The single price set by the Times ($2.75/week) is too much for many potential subscribers, and too little for many dedicated ones. Too much for a given subscriber in some periods, and too little in other periods.

The FairPay strategy can involve the subscriber in a cooperative and dynamically adaptive process that can quantify the value that subscriber sees (as it relates to their goals), and set the price accordingly.

  • It seeks to do this in a way that is simple, yet balanced to work for both the publisher and the subscriber. 
  • It applies dialogs about value to elicit value perception data from the subscriber that can be obtained in no other way. 
  • These dialogs also serve to deepen the relationship by demonstrating that the subscriber's perspectives and goals are respected. 
  • At the same time, this process gives the publisher a way to validate that information, to nudge the subscriber to pay fairly, and to cut off FairPay privileges for those who are uncooperative. 
  • This operates as a repeated game, a structure that can motivate cooperation. 

Think of it as not just customer experience (CX), but a truly customer-first focus on value experience (VX).

This may not work for all subscribers, at least not right away, but it can be applied to select segments of current and future subscribers to get and retain more subscribers, and thus increase the total value of digital subscriptions to both the publisher and the subscribers. A fuller explanation is in my post, Patron-izing Journalism -- Beyond Paywalls, Meters, and Membership. Suggestions on how this can begin with select segments and then gradually expand are in Finding Good and Fair Customers -- Where Are the Sweet Spots?

The Times (and others) can try basic forms of this strategy in limited, low-risk tests, and learn to refine and extend it. They and their subscribers can learn how to cooperate to get the best and most valuable journalism possible, by the measures that matter -- the satisfaction of each subscriber as well as the profit. They can move from subscription first to subscriber-first. As the MarketingSherpa report shows, this can lead to "customer loyalty, an increase in share of wallet, and sustainable business success."

Some other posts that expand on how FairPay applies to journalism:

For a full introduction to FairPay see the Overview and the sidebar on How FairPay Works (just to the right, if reading this at 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.

Tuesday, January 24, 2017

What Lies Beyond Paywalls -- A Better Way

Are publishers in a zero-sum pricing game with their readers -- a game of psyching them out? Or is a win-win game of cooperation on value exchange with their best current and potential customers a better way to make journalism sustainable? With doubts as to the future of advertising support, this question of how best to motivate direct reader payments is central to the future of journalism.

NiemanLab's astute 2017 prediction piece entitled What Lies Beyond Paywalls (by David Skok of the Toronto Star) explains how advanced marketing technology can change paywalls. I agree, and suggest that FairPay provides an important complement to that -- pointing to a new way to use this technology in an even more effectively predictive, anticipatory, powerful -- and win-win -- way. The idea is to go farther beyond current paywalls, in a new, more "customer-first" dimension: 
  • from one-sided, zero-sum relationships, where the publisher uses this technology to unilaterally impose a price on the reader in a smarter way
  • to cooperative, win-win relationships, where the publisher uses this technology to motivate the customer to participate in setting a price that both parties accept as fair value -- at least for the important subset of users who can be enticed to cooperate -- and it is those who are likely to provide the most Customer Lifetime Value (CLV).
Skok nicely projects the skilled application of advanced marketing technology to journalism:
We can combine machine learning, predictive, and anticipatory analytics to optimize the value exchanged from this reader, on this device, coming from this platform, on this article, at this exact moment in time. In other words, a dynamic meter.
I agree that a dynamic meter is central to the answer -- but suggest we need to go beyond our narrow 20th century mindset about how the meter is used. Instead of continuing to to unilaterally impose prices -- even if based on smarter metering -- I suggest we apply our smarter meter to engage the reader in a more cooperative approach to our value exchange relationship.

A "sophisticated, data driven approach to revenue" to achieve "a dynamic value exchange"

As Skok says, a greater emphasis on "high journalistic or engagement value...makes the notion of having binary on-or-off paywalls and press releases touting '10 free articles a month' seem antiquated." Better learning and analytics enable publishers to drive toward "the ideal value exchange...and then serve [any visitor] a dynamic meter accordingly." That is a smart adaptation of the advanced methods that are increasingly common in all kinds of online marketing to consumers -- but it still has a premise that I suggest is antiquated.

Skok's analysis clearly reflects the nature of journalism as an experience good in which the value proposition is very personalized and dynamic. But no matter how well we apply sophisticated learning and analytics, we can only make an informed guess at how to see value through our reader's eyes. Why not use all of that data -- but complement it with the knowledge of the reader, who understands the experience of their own value perceptions and usage context far more directly than even the most sophisticated publisher possibly can? Instead of trying to psych out the right price (or price schedule) to offer the reader, why not cooperate with them to agree on the right price (or price schedule)?

The participatory, "customer-first," twist of FairPay

FairPay draws on recent findings in behavioral economics that suggest that pricing is most effective, and builds greatest Customer Lifetime Value, when it emerges through a dialog with the buyer in a win-win process.  Such dialog was standard practice through most of history -- before the advent of mass-marketing sacrificed the naturally cooperative nature of commercial relationships.  We already see this re-emerging today in the principle of “value-based pricing” that is now becoming a best-practice in many B2B markets.  FairPay offers a new way to make a similar approach workable and scalable for mass consumer markets.  This is particularly relevant for digital experience goods such as journalism (especially since digital goods have negligible replication costs).
  • Skok points to how modern methods can make seller-set pricing very sophisticated in predicting/anticipating consumer value.  
  • FairPay suggests that even perfectly sophisticated seller-pricing is not as accurate or effective as joint value-setting.  
  • Seller-set pricing fails to fully exploit the buyer’s unique knowledge of received value, and is unable to motivate the cooperative "customer-first" relationship that joint value-setting does.
Using FairPay for selected readers, the methods Skok outlines would be used by the publisher not to psych-out the reader, but to frame the dialog and nudge the reader to prices that are agreeably fair:
  • Learning and analytic methods can be used to suggest prices to the reader, and frame why those suggestions are fair. 
  • Instead of being unilaterally imposed, take it or leave it, they can be presented in a way that invites the reader to agree, or explain why they disagree. 
  • The most appreciative readers may wish to pay even more share of wallet, to support the work they value highly.
  • Large numbers of would-be customers, who would otherwise walk away, can agree to pay a bit less generously, but still add some profit that supports the creation of more journalism.
  • This value setting process can reflect a fully dynamic meter, of the kind Skok suggests -- one that includes reverse meter values (such as advertising attention, viral shares, UGC, and the like).
  • Customers will gain satisfaction and be more loyal when they see that the publisher is putting the customer first, and seeking to find a fair value exchange specific to each individual case.
FairPay would be positioned as a special option for a privileged relationship -- a FairPay Zone -- one that centers on creating a good "Value Experience" (VX):
  • Readers who enter this FairPay Zone can do so at any level of usage, with corresponding prices. It acts as a totally personalized paywall/membership/patronship option with terms that are cooperatively agreed to. 
  • Even readers who "despise" paywalls will likely find the win-win process of the FairPay Zone agreeable -- a truly customer-first, 1:1 experience that centers on value. This can reduce cost-per-acquisition, better convert visitors to subscribers, increase reader satisfaction, reduce costly churn, and thus truly maximize CLV. Instead of the old invisible hand, think of this as an invisible handshake.
  • This FairPay Zone would coexist with conventional seller-set pricing (paywalls, membership, and/or meters). Those would apply at the reader's discretion for those who do not wish to opt in -- and at the publisher's discretion for those who do not demonstrate willingness to play the FairPay “game” fairly and cooperatively. Such alternatives could be any combination of unlimited subscription or per item deals, much as Skok outlines. For those customers who are not ready and willing for the cooperative path of FairPay, that path will remain best practice for some time. 
  • But for customers who are ready and willing, why not engage them in a more win-win customer journey
(FairPay can be implemented by individual publishers, or in aggregator platforms such as Blendle or NextIssue. The back end services supporting FairPay can be developed by individual publishers or by SaaS platform providers that serve multiple publishers.)

Established findings in behavioral economics and game theory provide strong reason to expect that FairPay will be very effective. It is a unique combination of proven elements -- that combination has not yet been fully proven in practice, but can be done with low-risk controlled experiments and then scaled from there, as explained in my book.

Some other posts that expand on how FairPay applies to journalism:
(Much the same theme also relates to the NY Times' recent 2020 Report, which suggests "We are, in simplest terms, a subscription-first business." A future post will expand on the idea that they would do well to begin moving from "subscription-first" to "subscriber first.")


For a full introduction to FairPay see the Overview and the sidebar on How FairPay Works (just to the right, if reading this at 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.

Tuesday, January 17, 2017

Finding Good and Fair Customers -- Where Are the Sweet Spots?

Finding good customers is the essential to success for all businesses. It is especially important in early uses of the new FairPay business strategy that builds cooperative "customer first" relationships.

Almost everyone who hears about FairPay sees its appeal -- but they also see that, because this relationship-centered strategy seems unconventional, it may not be not suitable for all customers (at least not yet). So the question arises: "where does it work best?" Naturally, in experimenting with a new technique, the smart strategy is to begin with the low hanging fruit and low-risk learning. Here is a focused approach to finding those early sweet spots.

FairPay as a change in behavior

People almost universally understand the new balance of power represented by FairPay's invisible handshake as being compelling:
We will give you (our customer) real power to participate in pricing -- as long as you demonstrate that you are fair about it. We will reward your generosity -- but will withdraw this special privilege if you are unfair.
This makes relationship marketing a two-party repeated game that rewards cooperation on both sides, and is clearly in the interest of consumers who are willing to play. (As explained in FairPay Changes the "Game" of Commerce.)

Rational consumers should want to play the FairPay game with any business they want to have a maximally beneficial long-term relationship with. They will get the best value for their money (including value from the relationship that they could not otherwise buy at all). But behavioral economics has shown us that consumers are not homo economicus, not all that rational. So the questions are how will real customers react? There are two related questions:
  1. How hard is it to get customers to use their pricing power fairly, given the current mind-set of many modern consumers to look for bargains -- to take a very short-term view of commerce as a brutally zero-sum game of deals, not relationships?
  2. Is the cognitive load of participating in the FairPay pricing process too burdensome for most customers -- compared to "one-click" seamlessness of "take it or leave it" set-pricing? (Of course this is a bit of a false comparison, given that bargain hunting leads many consumers to take on huge cognitive loads -- such as for credit card bonuses and airline rewards, some extremists spending days researching and making "mileage runs" to get miles with most of the costs and none of the benefits of going anywhere.)
Start with the low-hanging fruit 

The question that matters is not how hard it is to convert your total market of customers, but whether there is a segment of customers who will take naturally to FairPay -- who will make it effective and profitable early on, with a minimum of difficulty:
  • What is the nature of those low-hanging fruit customer segments?
  • Where can we find and engage them? -- in what businesses sectors?
  • How can we target them with niche initiatives to prove the concept and refine it at low cost and risk?
  • How can we leverage our early learning to quickly make FairPay more simple and habitual?
  • How can we then build on that learning with select customers to broaden the market? 
FairPay is an engine that motivates fairness, but it makes sense to begin using early versions of that engine where it will prove most effective -- in populations that will be eager to take to it. And even if expansion beyond those limited populations is slow, why not enjoy that ripe fruit and increase the Customer Lifetime Value (CLV) of your best customers?

Think of these early sweet spots as the thin end of the wedge of behavior change. As customers begin to see how it improves their customer experience -- their value experience -- they will want to use it more, and others will want to join in that.

Natural customers for FairPay

FairPay is not a new behavior, but a reversion to behavioral norms that are natural, and were the way people conducted business with one another for millennia. But that is a change from current consumer mind-sets (bargain-hunting), and some customer segments will adapt to that more readily than others.
  • Some will be slow to shift from short-term, zero-sum thinking -- viewing businesses as an enemy to exploit or be exploited by -- while others will jump at the opportunity to build a productive and cooperative relationship. 
  • The trick will be to find lines of business and customer segments who are most disposed to welcome this new logic, those for whom it is most natural.
The behavioral science behind this is addressed in my post Making Customers Want to Pay You -- Research on How FairPay Changes the Game. The key idea is that there are two factors to work with:
  1. Social Value Orientation (SVO), essentially pro-social versus pro-self, as individual traits
  2. Economic/Exchange Relationship Norms versus Communal Relationship Norms, as situational variables in a relationship. 
The sweet spot is in targeting high Social Value Orientation (pro-social) customers, and nudging them toward Communal Relationship Norms. That suggests two related factors to the segmentation strategy:

1. Start with those disposed to generosity -- “superfans” who are loyal and perceive high value (especially appreciative customers of providers who demonstrably deserve generosity for delivering high quality, service, and social value). They are the ones who will respond best to the pricing privilege that the seller grants to the buyer in FairPay, to price in a way that considers fairness to the seller, and who will be least inclined to abuse that privilege.  Managing FairPay offers for these buyers will be mostly carrot, and not much stick. They are the ones who will be most willing to pay you generously for your product or service -- as long as you establish and maintain your position as deserving, delivering on your promises, and asking in the right way for fair compensation.

2. Start with those disposed to cooperation -- dedicated customers who are thrilled to share pricing responsibility, and are willing to bear some modest burden to do that right. What is needed is
not just a desire to be fair, but willingness to make the effort to do so. For that, the key is to target customers who are dedicated to the product or service and/or the provider. Again, loyal/"superfan" customers are most likely to have this dedication. (Benji Rogers of PledgeMusic observed to me that "superfans will happily crawl on broken glass" to support their favorite artists.)

These are the customers who will be worth your while to start with. The FairPay process enables you to test for these attributes with low risk, nudge those who are amenable toward cooperative and profitable behaviors, and cull out those who are not (at least until there is reason to think they might be more ready to cooperate). Many posts on this blog explore various aspects of how to do that, in various business use cases.

Of course it is still essential to make the process as simple and seamless as possible. More of the theory behind that is outlined in
Thinking Fast and Slow about FairPay: A New Psychology for Commerce in a Networked Age.

(As to the related question of how can we leverage our early learning to quickly make FairPay more simple and habitual, I will address that in a companion post.) 

Natural businesses for FairPay

Some businesses will naturally motivate willingness and dedication of their customers to be fair -- and some naturally attract more than their share of customers who are already predisposed to such behavior. Other posts have examined the application of FairPay to some such businesses in detail, for example:
Those (and other human creator-driven businesses) are some that are obvious naturals, but many other kinds of companies have already established themselves as having a "customer-first" attitude that makes them deserving of Communal Relationship Norms -- demonstrating that they consistently seek to deliver quality products and services, care about dealing fairly with their customers and are respondive to their individual needs. Such business are also in a prime position to start applying FairPay to their most promising customer segments. (Check out my more comprehensive list of Application/Market Sectors that seem especially likely to do well with FairPay.)

Whatever the field of business, a critical success factor will be the ongoing demonstration of customer-first behaviors that continually lead customers to see the business as responsively listening, and deserving of their trust and generosity.

Grabbing the low-hanging fruit

The next question is just which phase of the customer journey to start with -- to further maximize likely success and minimize risk. Three areas are especially promising as starting points for testing:
Other possibilities include selection of test populations in any way that limits risk and targets segments that appreciate the value of the offering and the personalized value proposition, such as:
  • Usage or style segments
  • Content segments (such as long-tail items, or by genre)
  • Device segments
  • Family plans
  • Segments that can highlight “deserving” sellers
  • Trials, specials, coupons
  • Distinct branding or white label offers.
Keep in mind that these can focus on either high value/usage or low value/usage segments. An important feature of FairPay is the price discrimination that justifies lower prices to those who get lower value. For example, retention offers can focus on low usage customers who are well justified in seeking to pay less that the usual all-you-can-eat price. In such cases, those who are asked to pay more can be given to understand why it is that these others pay less, even if that fact becomes known.

Staging the learning process

FairPay is well suited to a step-wise introduction that allows for testing and learning at low cost and risk. The idea is to let both the business and the customers ease into the new logic of FairPay and learn how to apply it effectively. This is addressed in the post FairPay “Free Trial”/“Survey” Mode – Easing into the FP Waters -- And Understanding Your Customers. The Trial/Survey mode it describes can generate significant learning with only simple software -- that can help shape a full FairPay implementation, as well as generate customer value perception data that is valuable in its own right -- even if the project goes no further.

The thin end of the wedge

All of these strategies can lead to effective trials that will serve as the thin end of the wedge of behavior change. The initial strategy should be to find these sweet spots and do low-risk controlled tests there. Businesses and customers will begin to see good results and learn how to apply this kind of win-win strategy. That will generate a virtuous cycle, to increase the loyalty and CLV of the initial customers, then to attract more customers to the game, and then to lead a growing range of firms to create FairPay zones, which will then bring more customers who are ready and willing to cooperate in this more win-win mode of commerce.

With this kind of focused, and carefully staged approach, the risks can be kept small and easily managed, the learning can be done over time, and the potential rewards can be immense!


For a full introduction to FairPay see the Overview and the sidebar on How FairPay Works (just to the right, if reading this at 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.