Thursday, October 13, 2016

Continuing Chaos in Cord-Cutting Value Propositions...

"The Definitive Guide to Cord-Cutting in 2016, Based on Your Habits," by Brian X. Chen of the Times, notes that:
Every quarter for the last few years, hundreds of thousands of American households have put an end to their TV subscriptions, fed up with the costs of cable subscriptions, channels they never watch and the annoying commercials. 
But he writes this guide because:
What we found was there is no one-size-fits-all solution because each streaming service carries a different catalog of content, and each gadget has access to different services.
He also notes the fundamental flaws in current TV packages, both from cable and cord-cutting services:
For value, cutting the cord isn’t very cheap if you then subscribe to multiple services to gain access to a diverse set of content. For cable subscribers, paying one bill is less of a hassle than juggling multiple bills. And even after you subscribe to multiple streaming services, there is still some content that you may miss out on because it is available only via cable or satellite, like some TV shows or live sports events. 
But for cable, "all you can eat" gets expensive for those who are not gluttons. The real problem is highlighted in this quote from Kirk Parsons of J.D.Power:
“I would love to have the ability to pick and choose what I want as opposed to having four different services,” Mr. Parsons said. “I think we’ll get there, but right now it’s frustrating for consumers to get what they want.” 
A Post-Bundling future

A ready solution to this chaos is offered in a post I did last year, Post-Bundling -- Packaging Better TV/Video Value Propositions with 20-20 Hindsight. Consider the heart of the problem:
  • Cable packages offer channel bundle discounts for moderate and high numbers of channels, but offer little adaptivity to what you actually watch in a given month.
  • OTT packages are "skinny bundles" of fewer channels.
  • "A la carte" pay per view lets you pay for just the shows you watch, but at one-off prices that are prohibitive if you watch many shows.
  • Why is there no volume discount for just what you watch????
The solution is simple. Post-Bundling lets you have run-of-the-house, and watch whatever you want, then calculates a discounted price for just those shows. The pre-set discount schedule can be comparable to a full or skinny bundle, depending on how much you watch (and how much of that is premium programming). For more, see that post.

A simple step toward the win-win future of FairPay

Readers of this blog know that FairPay takes this idea of post-pricing and marries it to deep customer participation in pricing. It does that in an adaptive process that personalizes pricing to match the individual consumer value received. Doing that takes some sophistication on the part of the seller, since the discount schedule is no longer pre-set, but adapts to additional variables such as how pleased you were with the programs you watched in a given month. But basic post-bundling (with pre-set discount schedules) is a very simple step in the right direction, one that can set the stage for an even more win-win future beyond that. Both steps are good for the customer and good for the TV distributor. It will bring the distributor more profits from more and happier customers -- and give them better understanding of how to please their customers.


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, September 20, 2016

FairPay Book Just Published / Related LinkedIn Group

My book on FairPay was just published. It is part of a series on Service Systems and Innovations in Business and Society, curated by Jim Spohrer and Haluk Demirkan of The International Society of Service Innovation Professionals (ISSIP), and published by Business Expert Press (BEP).

Some extracts from early praise (as cited on the book page):
Anyone responsible for monetizing digital content in consumer markets should understand this radically new perspective on pricing and how to maximize customer lifetime value. innovative and visionary methodology …what disruption could look like...
...compelling …promises to transform business...
Highly recommended for digital business entrepreneurs, as well as established firms...
The full title is FairPay: Adaptively Win-Win Customer Relationships. It pulls together a wealth of material from the blog plus new additions. The book has sections that are very pragmatically focused on how FairPay works in specific industry use-cases (as an alternative or complement to conventional freemium subscriptions, paywalls, and other methods). It also addresses the conceptual foundations in marketing, behavioral economics, game theory, and related areas.  It explains how FairPay can solve critical problems in pricing, value propositions, and customer relationships -- with a focus on the digital content and services businesses now in the throes of digital disruption, but also for other businesses.

I hope readers (both early followers and those new to these strategies) will find this not only a useful introduction to FairPay, but also a thought-provoking perspective on the broader issues of modern consumer commerce and how to make it far more win-win. As noted below, there is now a LinkedIn group dedicated to building on this theme.

Some of the new material in the book will be featured in added blog posts over the coming months.

Details on the book and how to get it are now online.

Order now from:
Online Supplement

As an added feature there is a special online supplement to the book with links to updates, blog posts with added detail, and other resources (also accessible as  Even before you get the book, this can offer a preview of much of the content (but in less organized form).

LinkedIn Group for FairPay and related innovations -- Please join!

As part of the online supplement, there is now a LinkedIn Group called FairPay: Adaptively Win-Win Customer Relationship, to enable you to connect with others who share interest in FairPay and related innovations in participative co-pricing, relationship marketing, customer journeys, and behavioral economics - especially to maximize Customer Lifetime Value for digital services.


This is part of a collection curated by Jim Spohrer and Haluk Demirkan of The International Society of Service Innovation Professionals (ISSIP).

  • Business Expert Press is a leader in concise and applied learning resources, and partners with Harvard Business Publishing
  • ISSIP is an organization founded by IBM, Cisco, HP and several Universities with a mission to promote Service Innovation for our interconnected world.
  • Jim Spohrer is IBM Innovation Champion and Director of the IBM University Programs World Wide,
  • Haluk Demirkan is Professor of Service Science, Information Systems & Supply Chain Management, and the Founder & Executive Director of Center for Information Based Management at the Milgard School of Business, University of Washington (UW) -Tacoma

Tuesday, September 13, 2016

Early Praise for FairPay (the Book)

Available soon!  Pre-order now!

"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

"This compelling book explains how a radical shift in how we set prices can help enterprises become more customer focused. It promises to transform business by providing a new operational dynamic for maximizing customer lifetime value."
- Professor Adrian Payne, University of New South Wales Business School

Available soon!

Thursday, September 8, 2016

Customer Journeys of Value -- Measuring the Elements of Value

The Elements of Value, a new HBR article from Bain consultants, provides an excellent structure for measuring value in consumer markets. FairPay provides an adaptive process for managing customer journeys that center on value. These ideas can be applied in combination to drive loyalty loops around value, in order to increase Customer Lifetime Value.

Some interesting quotes from the article:
When customers evaluate a product or service, they weigh its perceived value against the asking price. Marketers have generally focused much of their time and energy on managing the price side of that equation...
What consumers truly value, however, can be difficult to pin down and psychologically complicated. How can leadership teams actively manage value or devise ways to deliver more of it, whether functional (saving time, reducing cost) or emotional (reducing anxiety, providing entertainment)?
...A rigorous model of consumer value allows a company to come up with new combinations of value that its products and services could deliver. The right combinations, our analysis shows, pay off in stronger customer loyalty, greater consumer willingness to try a particular brand, and sustained revenue growth. 
FairPay provides a structure for building relationships around value, by giving consumers limited power to set prices that correspond to the value they receive -- for as long as the seller considers them to be fair about how they do that (but not longer). This is described in my post on customer journeys and the elsewhere on my blog (see links below). The elements of value outlined in this HBR article can be an effective structure for the dialogs on value that FairPay inserts into the customer journey to enable that.

Since there are 30 of these elements, in a hierarchy of four levels (functional, emotional, life changing, and social impact), it would not be practical to force dialog on every element on every cycle -- and only some of them will be relevant to any given business. But the dialog structure can be varied adaptively to introduce relevant elements whenever the customer or the business find them to be relevant. This can enable the dialogs to generate rich value data.

And keep in mind, that these specific elements are just a way to specify and communicate value judgments that are actually very intuitive and nuanced. The beauty of FairPay is that it is driven by the consumer's intuitive sense of value.  The seller can drive the dialog based on analytics such as these, to seek to understand that nuanced and intuitive perception of value through simple questions, while the buyer need only respond, and need not be concerned about the structure that is driving that.

The dynamically adaptive nature of FairPay also enables the level of dialog to be varied over time, to collect this important value data without undue burden on customers. Value dialogs might be relatively frequent and detailed when a relationship starts, but only until a common understanding of value is reached.  Then the dialog level can be cut back, or even dropped completely, as long as both parties are satisfied with putting the adaptation process on autopilot, but then re-engaged in more detail any time either party senses a disconnect on their shared understanding of value (for that particular customer).

The article concludes with a quote from an executive that “I have a lot of people working on product features and service improvements, but I don’t have anyone really thinking about consumer value elements in a holistic manner.” FairPay's embedding of dialogs about value into the customer journey loyalty loop makes thinking about customer value elements in a holistic manner central to routine operations.

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).

Monday, August 8, 2016

How Pokemon Nudges Users to Spend

This Wall Street Journal article explores how PokémonGo and other mobile gaming apps "have mastered techniques for coaxing mobile-game players to make in-app purchases." This provides some crucial lessons about the future of marketing in general -- and the case for the new FairPay strategy in particular.

Here are some very interesting points about ways to get consumers to happily spend money -- points that can be generalized in computer mediated marketing of all kinds:

  • Once considered an unrefined nag, the in-app pitch has been honed so well it coaxes tens of billions of dollars a year from people who have gravitated to free mobile games.
  • They “engage people in a longer financial discourse than you would have in an upfront sale.”
  • Algorithms are playing an increasing part in nudging players to spend. Based on dozens of data points—how often gamers play, what model mobile device they use, location and gender—developers might raise a game’s difficulty level, making no two players’ experiences exactly alike.
  • Data on players’ behavior also are used to strategically tweak prices for virtual goods in real time. “You get people to spend more money if you understand their behavior,” said Niklas Herriger, founder and chief executive of Gondola, a New York analytics firm that develops algorithms for game developers. “You can trace their finger every step of the way.” 

In talking to companies about the potential of the new FairPay pricing strategy described in this blog, the two concerns that are most often raised relate to consumer behavior. Will customers be willing to become engaged in the game of spending money? And can I design the game to nudge users to be fair enough to provide a fair profit? 

The article suggests that both can now be done successfully. With the right choice architecture, a form of game design, customers can be nudged efficiently and effectively. If it can be done in marketing for a game, why not in other forms of marketing as well? 

That suggests the same is true for FairPay. It is a new logic, but a natural one -- the kind of economic cooperation that people have excelled at for millennia.  It is only in the past century that we have been conditioned to think differently. This anomaly has held force for all of our lives and is therefore all we know, but now it is time to jump into to the future. We have the technology -- and both businesses and consumers will love it.

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).

Monday, August 1, 2016

Price Discrimination for the Good!

"Higher prices in an affluent area help bring healthier meals to a poor neighborhood" reads the teaser for an interesting NYTimes article, which goes on to report on a 2:1 difference in prices between two Everytable restaurants only two miles apart in LA:
The big price difference represents an unusual experiment to address the persistent issue of limited food choices in poorer neighborhoods around the country. The higher prices at the downtown store are effectively meant to offset smaller profits at the other location, making the lower-priced restaurant more economically viable.
The article includes comments from advisory firm partner Michael Kaufman:
To make it work, he said people would need to understand why prices are higher in one neighborhood than in another. ...“I think the key to it will be how they tell their story” 
FairPay applies similar logic -- in a more dynamically adaptive, emergent process -- to set prices based on an individual "invisible handshake" that applies a balance of powers to learn what value customers receive, and factor in their ability to pay to determine the fair share they should contribute the the profits that sustain a business. This was explained in my earlier post Price Discrimination Can Be Good!, which was triggered by the equally interesting, if less noble, example of Uber surge pricing.

One key point is that price discrimination is not inherently evil, as it is often viewed. It depends on how and why it is done:

  • When price discrimination is done unilaterally by sellers, to extract maximum profit with no buy-in from customers it can be bad -- especially if done secretly in a way that is exploitative.
  • When it is done with transparency and customer buy-in, based equitably on differentials in ability to pay and value received, it can be laudable, and customers can feel good about it.  
What matters is the openness and fairness of the process. As Kaufman said, "the key to it will be how they tell their story.”

This relates to the broader issue of the growing call for a more socially conscious capitalism, a "fairness economy." We want the efficiency of free markets, but with an awareness of social values and bottom lines that factor in people and planet. Many are seeking ways to to achieve that. FairPay points to a new and more powerful solution.

FairPay's invisible handshake is not just a feel-good image, but an operational process based on a specific balance of powers that shapes the "story" -- a process of dialog that gives pricing power to customers, but only as long as they use it in a way the seller agrees is fair. FairPay can be applied in a wide range of contexts, from those that today lack much social context (like TV), through those that have stronger social context (like journalism and indie music), to those with dominating social context (like non-profits and charities).

Engaging customers, telling the story, and building long-term relationships based on this invisible handshake promises to increase Lifetime Customer Value, to offer more profit, greater market share -- and more total value to society.

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).

Tuesday, July 26, 2016

A Better Revenue Strategy for Non-Profits in the Digital Era

FairPay is a revolutionary new logic for revenue relationships in our increasingly digital world -- it was designed to make for-profit digital business more effective, but also promises to dramatically enhance revenue generation for non-profits

The Internet has given new power to consumers. FairPay accepts that power and works with it to shift relationships from a short-term, zero-sum focus -- one that no longer works effectively for anyone -- to an ongoing win-win focus that seeks to maximize the co-creation of value over a relationship. It creates a new focus on the fairness of pricing and value propositions on an individual basis -- an "invisible handshake." This FairPay handshake is particularly relevant to non-profit services. What better sector to benefit from the fairness and cooperation that FairPay elicits? 

A museum example

I joined the Whitney Museum not long ago, and was offered a complex menu of membership levels and optional features:
  • There was the usual set of levels based on number of people and features to be included, with a set price for each.  This made it easy for me to pick a level, but offered only a crude basis for the museum to seek more share of wallet.
  • There was also a "Curate Your Own Membership" program that let me choose from five series of premium features -- with any one included, and added ones offered for $40 each.  The five series were billed as Social, Learning, Insider, Family, and Philanthropy, with a short phrase explaining the apparently non-overlapping of features in each. That was a nice touch, adding some of the spirit of FairPay, in that it was meant to enable me to better customize my value proposition. The problem was that they made me an offer I couldn't understand. Not having been to any of their events, and not knowing the exact topics, how could I know which I would want? I doubted I wanted enough to buy extras, so just picked one that sounded OK. Great willingness to customize the value proposition, but not very effective at it.
The core problems: unpredictable value, and need to set prices in advance, in ways that cannot be expected to match well to value.

Before looking at other examples, let's dig a bit deeper on the issues here. The problem is there is no real dialog about value, so no real optimization of the value proposition. I have been to the museum several times since joining, and have had no real interaction with the organization. They must know my attendance record, and that I have gone to none of their special events, but I have no hint of that. If they want a bigger share of my wallet, they are not targeting me well at all.

With FairPay, the membership price could be set based on usage, with 20-20 hindsight (maybe every three or six months) -- after I use whatever services I please, and get a usage report that reminds me what I used (exhibit visits, extras from any of the five event series) along with an itemized suggested price from the museum, tailored to what I used and what is known about me (maybe visits were 30 minutes or five hours; some at peak times or not, some to sold-out events, student/artist/senior, etc.). 

The museum could instead offer "post-bundling," a way to create ad-hoc packages of services on demand, at prices that build in personalized volume discounts. That could encourage me to try more services, and to pay more, to the extent that I found them valuable. Even with just a simple form of this kind of "post-pricing," the extras from all five series at the Whitney might be offered to me at per-event prices, but with volume discounts based on number of events attended in a given pricing cycle. That way I need not guess in advance what I might like, and would take no risk of being wrong, (There could even be "roll-over" provisions to smooth over the arbitrary period boundaries, just like "roll-over minutes" on cellular services).

A win-win customer journey with a loyalty loop centered on value

Such post-pricing is an important foundation of FairPay, which adds other key features to generate rich customer journeys that center on win-win value. Modern marketing has come to realize that the key to success is not in individual transactions, but in maximizing return business. Transactions roll into customer journeys, and creating "loyalty loops" in those journeys brings the return business that maximizes Lifetime Customer Value (LCV). FairPay drives those loyalty loops to center on value, to fuel deeper and more effective relationships.

FairPay does this by combining post-pricing with a new supercharged variant of Pay What You Want (PWYW) pricing. Non-profits often apply PWYW principles to donations, but in the digital age, even profit businesses are finding PWYW can sometimes be surprisingly effective. FairPay adds a new balance of powers to make this more effective. The new balancing factor is that the consumer pays what they think fair, knowing that the organization will track that, and make or withhold future offers depending on how fair the price seems to them, based on full consideration of the particular situation. 

Continuing our museum example, with full use of FairPay, the price schedule would just be suggestive (the PWYW aspect). The museum could highlight the value I actually got, based on actual usage data and report that with its suggested price. If I were a regular who came to value the programs, that would be evident to both me and the museum from the usage data, so we could converge on a fair price for what I used. If I went often, the price should be higher. If I ended up just going occasionally, we could settle on lower prices, but still keep me as a supportive patron with a sense of belonging and patronship, at whatever level seemed appropriate. That would still make me more likely to visit than a single-shot set-price pay-as-you-go alternative, and thus more likely to pay something, and more likely to consider a more generous level of payment/donation. Of course at first my price setting might be unduly high or low, but the museum could nudge me toward a good understanding of value and fairness by adjusting the level of perks in its offers (or terminating the privilege of FairPay membership, requiring me to adhere to a conventional price schedule).

(A very similar example of how this can work is described in my post on FairPay pricing for premium tiers for the NY Times -- journalism has much similarity to non-profit cultural enterprises.  Another post takes a broader look at the issues for journalism that are also very relevant to non-profits.)

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).

The big picture -- How "customers" make non-profits sustainably win-win

Consider the spectrum of non-profits, from more service oriented to more charity oriented:
·         Co-operatives that operate much like a business, but with all profits shared by the members.
·         Professional organizations that may offer publications, conferences, certifications, and other benefits
·         Cultural organizations such as museums that may offer exhibits, facilities, and events.
·         Secular or religious organizations that may cover a wide spectrum of direct services like food, housing, schools, hospitals, and museums, and have a wide mix of direct customer recipients and indirect customer benefactors.

"Customers" are central across this spectrum, but with variations in expectations of how pricing applies:
·         In traditional for-profit business exchange, customers are generally expected to pay enough to sustain the enterprise. (But even here, there are social values, such as in the business of journalism, and more generally in various "social" and "environmental" bottom lines, and in "benefit corporations.")
·         In non-profits that deliver services for fees, direct customers are expected to pay for services, but often with the help of subsidies from benefactors (indirect customers) who give donations to make those services more affordable.
·         In pure charities, direct customers may not be expected to pay at all, and benefactors are needed to donate enough to sustain that.

FairPay provides new and better way to address the complex issues of pricing and sustainability across this spectrum.  Consider how this works for the two different (but often overlapping) kinds of customers:
·         Recipients -- direct customers of direct services (the mission). Here, pricing takes on two interrelated dimensions -- what is the fair value of the service, and what is the fair contribution from the recipient (to both the cost of the service, and to the added overheads needed to sustain the organization).
·         Benefactors -- indirect customers of indirect services (the altruistic value of supporting services to others, and the value of being a benefactor, including perks and recognition).  Here, the key dimensions are the value of services to others enabled by the benefactor’s donations, and the value of indirect benefits to the benefactor.
The details will vary with the type of customer and the nature of the organization and mission, but the essential task is the same -- to generate sustaining revenue by setting prices that make the value proposition be "win-win."

Of course these factors are difficult to quantify in any precise and objective way, but the beauty of FairPay is that it puts value into personal terms, with all of the nuance of human evaluation. Value setting need not be precise, as long as it is done through flexible and open dialog.
·         Organizations can frame the value they think they provide in terms of whatever metrics are available (and the metrics are becoming increasingly meaningful)
·         Customers (direct or indirect) can respond by factoring in whatever aspects of value they think important, including their perceptions of what is reported to them, plus any positive or negative factors they think important, including ability and willingness to pay. Multiple choice options (with some interpretation of free-text comments) can enable this to be automatically scored and factored into assessments of whether customer-set prices are fair.
·         The organization can offer "carrots" to encourage generosity, and gently withhold privileges or perks when "sticks" are needed.

FairPay provides a dynamic, emergent process for both sides to learn how to make the relationship maximally win-win. That can bring the organization more customers (recipients and benefactors) and get more share of wallet (the amount that the customers can justify and afford to give).

FairPay was developed because the invisible hand of Adam Smith no longer works well in the digital world. FairPay turns instead toward this new invisible handshake -- an agreement to work together in good faith to build a relationship that is win-win.

If non-profits cannot justify support of their mission on the basis of fairness, what basis do they have? If fairness is the basis, what better process for justifying support than FairPay?

Making it happen

FairPay processes are not difficult to build and put into trials, but still require a degree of effort that might challenge the technical resources of smaller non-profits. This represents a major opportunity for a shared platform that can be used by many non-profit organizations. For example, Tessitura Network is a consortium of over 500 arts and cultural organizations that provides a common e-commerce and CRM infrastructure. A shared FairPay platform (and shared tracking of fairness) could benefit many of its members.

I am working on FairPay as a pro-bono project, and would be happy to assist non-profits in exploring how it might work for them. (I can be reached at fairpay [at] teleshuttle [dot] com.)

Tuesday, June 7, 2016

My Forthcoming Book on "FairPay: Adaptively Win-Win Customer Relationships"

Enterprises everywhere are recognizing the need to be more customer focused, but struggle to see how.  This new book explains a revolutionary approach to pricing – FairPay -- that can change the game.  FairPay is a new logic for conducting ongoing business relationships that adaptively seek win-win value propositions in which price reflects value.

I am very pleased to report that this book is in production, to be published later this year. It will be part of a series on Service Systems and Innovations in Business and Society, curated by Jim Spohrer and Haluk Demirkan of The International Society of Service Innovation Professionals (ISSIP), and published by Business Expert Press (BEP).

Jim saw the potential of FairPay, and how well it is aligned with the service-related innovations he and his colleagues at IBM and ISSIP are championing. He asked that I write this book, drawing on the material in my blog. I look forward to seeing it published in the coming months.

The full title is FairPay: Adaptively Win-Win Customer Relationships. It pulls together a wealth of material from the blog plus new additions. The book has sections that are very pragmatically focused on how FairPay works in specific industry use-cases (as an alternative or complement to conventional freemium subscriptions, paywalls, and other methods). It also addresses the conceptual foundations in marketing, behavioral economics, game theory, and related areas.  It explains how FairPay can solve critical problems in pricing, value propositions, and customer relationships -- with a focus on the digital content and services businesses now in the throes of digital disruption, but also for other businesses.

I hope readers (both early followers and those new to these strategies) will find this not only a useful introduction to FairPay, but also a thought-provoking perspective on the broader issues of modern consumer commerce and how to make it far more win-win.

Some of the new material in the book will be featured in added blog posts over the coming months.

I will be providing updates about the book on this blog as it approaches publication.


Business Expert Press is a leader in concise and applied learning resources, and partners with Harvard Business Publishing

ISSIP is an organization founded by IBM, Cisco, HP and several Universities with a mission to promote Service Innovation for our interconnected world.

Jim Spohrer is IBM Innovation Champion and Director of the IBM University Programs World Wide,

Haluk Demirkan is Professor of Service Science, Information Systems & Supply Chain Management, and the Founder & Executive Director of Center for Information Based Management at the Milgard School of Business, University of Washington (UW) -Tacoma

[Updated 9/10]

Thursday, March 24, 2016

How Blendle Could Do Much Better with FairPay

Blendle has made impressive progress, but still has some serious issues to face with its model. FairPay shows how it can do much better.

This news aggregator that just launched its US beta, after success in the Netherlands and Germany, bills itself as "a Spotify, Netflix, or iTunes" for news, and has major funding and publishers behind it.  I wish them well, and hope they will adapt improvements along the lines suggested here.  I have addressed many aspects of selling news in this blog (see some links below) but let's focus on Blendle.

The heart of the issue is the inherent flaw of a set-price micropayment model (that apparently does not offer volume discounts). According to the Wired report, "Newspaper stories will cost on average between 19 and 39 cents per article, while magazine stories will cost on average between 9 and 49 cents." For light users who want a variety of stories, or even just one or two stories from a publication that is locked behind a paywall, that is a good deal. But for moderate to heavy users, the meter will be clicking away, and the bill will get to be pretty hefty. If one news story in a month costs say 25 cents, should 100 stories in a month cost $25, and 500 in a month (just 17 per day) cost $125? That gets expensive fast, and clearly subscriptions offer much lower unit prices.

Subscriptions are less exposed to bill-shock, but subscriptions have other issues -- they are too expensive for light users and give away too much for heavy users.  My post, Beyond the Deadweight Loss of "All You Can Eat" Subscriptions, explains how neither subscriptions nor micropayments result in prices that are economically efficient and fair for a wide range of users. (The references by Shirky and Odlysko cited at the end of this post specifically address the problems with micropayments in more depth.)

A fundamental flaw of set-price micropayments is that there is no volume discount or pricing sophistication of any kind -- so total billings become unfair and prohibitive to your best potential customers.  That creates inefficiency, lost sales, lost profits, and unhappy customers -- and is something that can easily be fixed.

As a first and relatively easy step, is to provide volume discounts. Why not offer volume discount tiers on Blendle, so that unit costs decrease with volume (across all publications). There might even be a cap on billings. All that takes is appropriate agreements with the publishers and a little added programming. As we know, subscriptions offer the ultimate volume discount (all you can eat), and usage related charges for such items as cellular voice minutes and data bytes are routinely discounted (if not unlimited). Consumers hate the ticking meter, and the risk of nasty billing surprises, and discounts are only fair. Neither costs nor value increase linearly with usage -- why should prices?

That would be a great improvement, but there are still serious issues, How different readers read different stories is not equal, nor is the value they get from them, or their ability to pay. How about readers who skim many stories versus those who linger over a few? How about some who are well-off and gain significant value from financial news versus a struggling retiree who just wants to manage his small nest egg?

Blendle points to its emphasis on journalism versus commodity news as a point of value, but there will still be huge variations in quality and perceived value. The instant refund option is a very nice feature, but far too all-or-nothing. [Update below.]

As a second, and more advanced step, Blendle could use the FairPay strategy to let readers have a say in how much their news is worth to them. As explained in the Overview and other posts on journalism, FairPay does this in a relationship-centered, participatory way that that customers buy into.
  • It structures a new kind of balance of powers that works over a series of transactions to build a relationship.  A consumer is selectively granted new power to set prices, but the seller decides whether to continue granting that power to that consumer. The relationship continues as long as both are satisfied.  This operates as a repeated game to motivate mutual fairness. 
  • This feedback control loop creates a new logic for adaptively seeking win-win value.  At heart, it provides a way to radically simplify value-based pricing to work in mass consumer markets. It builds stronger customer relationships, for greater profit, from a wider market.   
FairPay can give the effect of volume discounts as well as reflect the variations in value noted above. Shirky observes that "users want simple and predictable pricing." FairPay suggests a different way to skin that cat --  not 100% simple and predictable, but close enough, because it offers prices that the user has significant say in.

As a third, intermediate step, Blendle could offer a reverse meter. This could let users who want lower prices get credit for accepting ads. Blendle pitches its freedom from ads, but for some, ads might be a benefit. Similarly, users who share stories virally could get credit for that. This too could be done as a simple add-on, but the added flexibility of FairPay pricing builds in a unified process for factoring in a continuous range of such value factors.

It seems Blendle is off to a promising start, but until they address the issues raised here, I expect their business model will take them only so far. By adding the steps I suggest, I expect they will be able to grow much larger and faster.


Some related posts:
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).

Background on micropayments

Those who have followed the long history of micropayments as the panacea that keeps failing, are familiar with two classic articles, both titled, "The Case Against Micropayments," first by Clay Shirky in 2000, and then by Andrew Odlysko in 2003. Blendle may have solved some of the issues of friction, but as I have noted, others relating to discounting, bundling, and the behavioral economics of value remain. The steps I suggest may help Blendle, and others, solve the rest of those issues.

----- [Update 3/31/16:]  Further notes

I should have included some points made in my earlier post that added comments on Blendle and aggregation:  "...Why should my incremental cost for one more article be very low (actually zero) if I am an average subscriber on an unlimited usage subscription plan, but high if I have the same activity level using a micropayment system? The incremental charge for an added article should be very small (once beyond some minimal level of volume). The reason consumers hate micropayments is this constantly ticking meter – if we cannot make the meter go away, we must at least make it tick very softly."

Also, I should have noted that FairPay reputation data can be especially powerful when collected by an aggregator across multiple merchants or suppliers, as for Blendle. The balance of powers in FairPay can be controlled by the seller to be as relaxed or strict as desired as to what level of consumer generosity is demanded to gain access to offers. For an aggregator like Blendle, different publishers could apply different policies, depending on their strategy for how inclusive or exclusive they wish to be (demanding of premium prices or less demanding, and more open to a wide market). Even for publishers new to the aggregator, the ability to apply reputation data obtained with respect to other publishers served by the aggregator provides a way to target offers to consumers they as yet have no direct experience with (working much like credit ratings).

[Update 4/27/16:] Refunds are too all-or-nothing!

Some early testing reinforces my view that the refund feature is a good start, but much too binary.  On viewing a WSJ article, I get a header link that says "$0.49 - No good, money back guarantee." which leads me to this pop-up at the right.

What if I just skimmed the first couple paragraphs and then moved on? -- should I pay the same as if I studied it and saved it?  What if I thought it was OK, but not worth the full price? Or if I thought it was great, and wanted to add a bonus?

In my case, I already have a WSJ subscription, so why should I have to pay at all?  (I assume both Blendle and WSJ would both like to know that Blendle email caught my eye before the WSJ did, and that the cost of supporting that is not very high. If I should pay anything at all, it is much less than $.49.  I could not even tell is was a WSJ article until I clicked into it because I don't download images in my emails.)

And what if I ask for refunds too often? Will I get slapped?

FairPay would give me a say in how much I paid.

Monday, February 22, 2016

Winning Back Lost Customers -- Before They Get Lost

Keeping good customers is increasingly central to maximizing profit and Customer Lifetime Value (CLV), as highlighted in the March HBR Idea Watch "Winning Back Lost Customers." As our economy shifts toward subscription-based services, companies are realizing that customer acquisition is very costly, and saps profits if churn is high. Win-back offers must be personalized more smartly, to present the right value proposition to the right customer.

Here I build on that article to suggest how companies can
  1. Automatically create personalized win-back offers that are adaptively win-win.
  2. Shift from reactively trying to win back customers who are almost lost -- to proactively enhancing the customer journey to retain them before they get lost at all
FairPay is a new revenue architecture for creating win-win offers, both for retention, and in routine business. Retention is a perfect test-bed for experimenting with this new strategy at low risk -- a new way to seek low-hanging fruit -- and then to build on that.

With regard to conventional win-back offers, FairPay can initially be trialed as adding a new, more automated, and more efficiently win-win tool.

But the deeper breakthrough of FairPay will be to put proactive retention directly into the customer journey loyalty loop.
  • We we know that an ounce of prevention is worth a pound of cure, but even these smarter retention strategies are just belated attempts to cure a customer's dissatisfaction with the value proposition after it has become a serious problem.
  • When proactively integrated into the customer journey loyalty loop, FairPay creates ongoing dialogs about value, so that potentially good customers are routinely engaged to jointly craft personalized value propositions, long before they approach the point of being lost. 
  • Just as smart marketers are building loyalty loops into every cycle of the customer journey, they can do the same for value and retention. 
  • Think loyalty loop = retention loop.
The HBR article on "Lost Customers" shows how sophisticated marketers pay attention to:
  • selecting the right customers to try to retain (using propensity models), and 
  • finding the right value propositions to present successful "win-back" offers tailored to those individual customers. 
Key success parameters for a retention strategy are both cost and ROI. Typical options include discounts, service upgrades, and combinations of the two, and results can be enhanced by tailoring the nature of the offer -- and whether to make an offer -- to the reasons a customer seeks to cancel. The sidebar of the HBR article explains how Cox Communications is getting smarter about customizing its retention offers to individual customers of its cable TV and Internet services, and triggering such offers at the right points in their customer journeys. A big step in the right direction -- of customizing the pricing and features of their offers -- but still doing it in a costly manner, with human intervention, on a reactive exception basis.

We look first at doing this better and more automatically, and then at doing it more widely and proactively.

Part 1:  Adaptively customizing retention offers 

First consider how FairPay can enhance conventional win-back offers.

As described on this blog, FairPay is a new win-win pricing strategy that provides an automated way to adaptively customize business-consumer relationships based on value -- with the full cooperation of the customer.
  • FairPay gives customers new power to dynamically set prices based on their individual usage and value perceptions ("pay what you think fair") -- after experiencing the product and knowing its actual value to them -- while requiring that they satisfy the seller that they are being fair and honest in order to continue that ("play fairly or lose the privilege"). 
  • This draws on a large body of behavioral economics on the human drive for fairness, and turns pricing of subscriptions into a repeated game that motivates customers to set fair prices in order to maintain this win-win relationship. Thus the power of the consumer to set prices is fully balanced by the power of the provider to demand more generosity or halt the game.
  • FairPay serves as a new way to do value-based pricing, in which prices are set based on the actual value to the customer -- with a fair share of the value surplus going to the provider. 
  • Such value-based pricing methods have been widely proven in B2B contexts -- now FairPay provides a simple way to achieve similar results in B2C businesses.
These new methods are not yet tested in B2C practice, but there is reason to think it is just a matter of both businesses and consumers learning how to apply them effectively. Retention offers provide an excellent place to test a variety of variations on this basic strategy in a controlled environment, and learn how to apply them effectively. FairPay generates an ongoing multivariate pricing experiment with each customer.

Retention is a perfect place to introduce FairPay -- in a high-value, low-risk, easily managed and contained environment.
  • FairPay can be offered to limited numbers of customers seeking to cancel, framed as a special trial offer that will be continued only if they price fairly, and only if enough other customers show that they, too, will set prices fairly.
  • FairPay retention options can be offered selectively to known customers, based on data that suggests which ones are worth keeping and which ones seem most likely to demonstrate the positive social value orientation that will lead them to set prices fairly -- using strategies along the lines outlined in the HBR article..
  • Selection criteria can further isolate testing of FairPay to those customers with a history of relatively light usage -- for which discounted prices would be fair, a strong incentive, and still very profitable.
  • FairPay can be tested in controlled populations, and framed as a special experimental offer, to minimize risk -- a privilege that will be continued only if enough customers cooperate, and revocable for any customer who is not reasonable.
The HBR article emphasizes the need to be smart about what offers to make to which customers. FairPay offers an automatically adaptive way to do that, with offers that are flexible and constantly tuned to individual consumer value perceptions.

Customers seeking to cancel are sending the message that the conventional value proposition does not work for them. The way to retain them is to find a profitable value propositions that do work for them -- for their particular situation and point in time. FairPay offers an automatically adaptive process for doing just that.

Why not try more effective pricing for those who are demanding it?

Subscription businesses face not only questions of price, but also the dilemma of whether to apply usage-based pricing (which consumers find unfriendly and subject to nasty surprises), or all-you-can-eat pricing (a one-size-fits-all price that is too high for light users and too low for heavy users). This dilemma is outlined in Beyond the Deadweight Loss of "All You Can Eat" Subscriptions, That post explains how FairPay's adaptive pricing can work better than either option, adding a value focus to blend the best aspects of both plans in a dynamically adaptive way.
  • Retention offers provide a perfect place to experiment with FairPay -- so that each viable customer can be offered the value they seek at a price they can accept -- which can lead to more revenue from more customers. 
  • The beauty of FairPay retention offers is that they are self-adjusting. Once you learn how to set key business rules for what to offer, to whom, and when, it then takes a minimum of live intervention by costly and hard to manage support staff. Customized FairPay offers can be made automatically, quickly, and at low cost, to every customer worth keeping.
Based on what you learn in such a limited trial, you may find it desirable to expand it, refine it, and extend it more widely -- to apply FairPay to customer acquisition, special premium/loyalty programs, and perhaps even to your core subscription pricing.

Part 2:  Proactive retention -- seeking win-win all the time

Managing retention on an exception basis is counterproductive.

Do you let your spouse feel neglected or abused, and ignore that until they ask for a divorce? If customizing value propositions makes sense when customers ask to cancel, wouldn't it be even more effective before they get that far gone? Why wait until then to begin dialog on the issues? Think about what listening to your customers really means. That may seem impractical, but FairPay provides a process for doing that efficiently and profitably. 

Why are we content with poor value propositions for the customers who don't make the effort to complain? Why do we wait for them to cancel? It may seem nice to get customers on auto-renew -- and hope they will never think about what they are paying and what they are getting -- but is that really the way to grow loyalty?

Maybe we would have more and better customers if we tried to proactively find better value propositions for all of them. That is what FairPay is designed to do. Once you have learned the basics of managing dynamically adaptive FairPay retention offers, why not extent that to all of your regular customers? -- at least all of those who seem to desire your product, and then demonstrate their fairness during an initial learning period. (Those who do not prove to be fair can be returned to the conventional set-price plans.)

The whole point of FairPay is to continuously seek win-win relationships that customers are satisfied with. It gives early warning of dissatisfaction, and provides processes to seek to resolve issues -- as customers become aware of them, and long before they ask to cancel. The idea is to build considerations of value -- and how that drives retention -- directly into the loyalty loop, for every cycle of each customer journey. For more on this, see the post Win-Win Customer Journeys -- With Dialogs on Value.

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).

Monday, January 4, 2016

The IoT Cloud of Value -- New Big Data for a Customer-Centric Revolution

Beyond the Internet of Things (NYTimes 1/2/16), about Adam Bosworth's work at Salesforce, leads to the Salesforce Blog and what Bosworth refers to as a "customer-centric revolution." The idea is that Internet of Things (IoT) data can be marshalled and analysed in the cloud to be acted on in real time, to enable a new level of business transformation, and more deeply intelligent, proactive and personal customer engagements -- CRM grows into a Marketing Cloud and the IoT Cloud feeds that. FairPay, the new pricing and relationship architecture described in this blog, can be thought of as adding a new aspect to the IoT that we might consider a Cloud of Value (an IoToV).

I have been writing on this blog about the business transformations enabled by this IoT Cloud of Value, and one post that gets to the heart of this is "E-Books Are Reading You" -- How That Enables a New and Far Better Economics. That post picked up on an interesting NYTimes article about how the instrumentation of e-books provides great detail about how you read them, and explained how that that enables new kinds of pricing and new richness in customer relationships:
How much you have to pay for a book can depend on how you read it -- how much, how long, how deeply, how repetitively. That data is indicative of the value you receive from the book. Why should what you pay to read it not depend on how you read it?
Start a chapter or two and quit, and pay nothing -- just like a Kindle free sample. Skim the whole book in 15 minutes and pay little or nothing -- much like Amazon's "Look Inside." Read a novel all the way through and pay a normal price. Read it three times and pay a bit extra. Study a how-to book, highlight sections, and go back regularly over many months, and pay accordingly (but with a volume discount). Use six travel guides on four countries during a one-week cruise and pay the equivalent of buying one travel guide (a detailed example is in this older post). 
The power of the Internet of Things to enable new kinds of pricing was nicely described in a 2014 HBR article, Companies like GE are increasingly realizing that pre-set prices are often not best for either the supplier or the customer -- and that IoT data can be used to develop custom prices very much along the lines of what FairPay seeks to do. These "value-based" pricing or "outcomes-based" models work very well for industrial equipment where a cooperative team of both producer and customer can negotiate not a specific price, but a method of analyzing value as actually achieved by the customer in use, and then base the price on that, after the data is known. Just as the Internet of Things is making that more widely applicable, working down from the high end, FairPay points to how a lightweight, heuristic variation on that theme can work for computer-mediated mass consumer markets, and work up from the low end.

In another post I describe this in terms of how FairPay can enrich customer journeys by inserting "dialogs about value" (building on IoToV data) into each cycle of the journey (after the "enjoy" step -- when the consumer knows the value of the experience) to adapt the pricing based on that. It is those value-based customer journeys that power FairPay to serve as a simplified form of value-based pricing that is suitable for consumer markets. That can also tie back more broadly into dynamic design of personalized products and their value propositions.

From this perspective of a Cloud of Value, FairPay can be viewed as having two key Big Data components:
  • Implicit signals of value. These are drawn from conventional IoT data, as suggested in the E-Books are Reading You post.
  • Explicit expressions of value. These are new kinds of data generated by the FairPay dialogs about value between the consumer and producer. (These customer expressions can be partially validated by testing their consistency with the implicit signals of value.)
Together, these drive the FairPay process as it seeks to build mutually beneficial customer journeys, and generate dynamic pricing based on customer-context-specific win-win value propositions. That can transform how we do business.

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).

Monday, December 28, 2015

FairPay-What-You-Want for Costly Products? Etsy? Everlane? Tiffany?

Not just digital? Can FairPay work for real products that have significant replication cost? -- such as for a fashion retailer like Everlane or an artisan marketplace like Etsy? There are actually some very interesting opportunities.

FairPay (short for Fair-Pay-What-You-Want) is a new architecture for participative price-setting that adaptively seeks win-win value propositions in ongoing customer relationships. As discussed throughout this blog, the case for FairPay is most obvious for products that have negligible marginal cost to replicate, such as digital content -- since there is no out-of-pocket loss when the occasional customer does not pay fairly-- but a minor variation of the process promises to work well for costly products as well.

The variation is very simple: set a minimum price floor that allows the buyer to set whatever price they want above that minimum. That can ensure that sales are not at a loss, and limit the FairPay adaptation process to apply only to the profit margin that the seller should receive above the cost. This builds on the simpler idea of Pay-What-You-Want (PWYW) with a price floor, which has been common, as described below.

FairPay goes far beyond PWYW to add in seller controls to nudge buyers to price fairly and to exclude those who do not. (It also shifts price setting until after use, when the value of the experience is known.) 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). [Added 12/30: Also see this background on studies of conventional PWYW.]

A nice example of conventional PWYW with a floor was just provided by fashion e-tailer They have a 5-day Christmas sale that offers an array of items at any of three different prices [see 12/31 Update below], Using the example described in a news report at Racked a woman's coat said to normally sell for $250 can be had at any of three prices, and a mouseover frames the rationale for those options:

  • $110: "$0 to Everlane. This only covers our cost of production and shipping."
  • $132:  $22 extra to Everlane. This helps to cover production, shipping, and overhead for our 70-person team."
  • $225.  $115 extra for Everlane. This helps cover production shipping, our team, and allows us to invest in growth. Thanks!"
FairPay is a new concept that would enable such sales to become a regular option for selected customers (including those found to pay well on special sales like this Christmas sale).  For customers who develop very good reputations for pricing fairness, many items might be offered that way all the time.  For customers who gain moderately good fairness reputations, such offers could be more limited, but still for many items (often, if not all the time). Thus FairPay becomes an interesting next step for such a retailer, as explained further below. 

FairPay with a price floor -- for retailers and for marketplaces

Beyond the example of a single retailer like Everlane, FairPay can also apply to a platform for serving many sellers, like, a platform that provides a marketplace for many designers and artisans. 

Let's look at the details of how FairPay can apply to either:
  • The conventional offering is for products to be sold at prices pre-set by the seller. All of the issues with conventional pricing apply here -- notably no allowance for individually varying value perceptions, and no post-pricing that enables the price to be set after the value is known.
  • A 100% FairPay offering would allow buyers to set any price they think fair, after receiving and trying the product, even as low a zero. The seller takes the risk that buyers will not be happy or fair, and that they will set very low prices, possibly well below cost. Even with FairPay's reputation tracking and limitation of sales to those who do not maintain a reputation for fair pricing, sellers face the risk of not recovering their costs on some sales.
  • A solution is to add FairPay with a price floor -- similar to PWYW with a price floor (as used by Everlane), but with the added controls of FairPay that I propose.
  • This hybrid version of FairPay could provide for a minimum "floor" price that is pre-set by the seller, plus a profit margin bonus that is set by the buyer. This floor price set by the seller might be paid prior to shipment (as with conventional sales), to ensure coverage of costs. The FairPay portion would address the profit margin bonus price, which would be set by the buyer, after experiencing the product, as with pure FairPay. 
  • Note that just changing conventional PWYW to have sellers set prices after using the product can have significant benefits in getting better PWYW pricing -- buyers no longer need to discount their prices for fear being disappointed by an untried item. Thus sellers should seriously consider this idea of post-priced PWYW, even before moving to the more advanced FairPay process.
How FairPay works with a price floor

Such a hybrid two-level pricing process (conventional seller-set floor price prior to sale, plus FairPay bonus price set by buyer post-sale) could provide a very effective solution to adaptively seek win-win sales.
  • The process would be explained up front, so that buyers and sellers understand that the initial price is just a base price that only covers the cost of the product (and perhaps a very small profit margin), but that buyers who are happy with the product are expected to pay more than that, once they see the value of what they have gotten.
  • The seller could post a suggested bonus price (with profit margin), but buyers could decide to price higher or lower, based on their own judgment of fair value. 
  • Buyer risk is much less than at full price. Refund options could still be provided to deal with serious dissatisfaction over even the "at-cost" base price.  However, with the lower base price, fewer buyers would be so unhappy they would wish to bother with a return for refund. Many would be willing to keep a marginally satisfactory product at a "bargain" price, given that the value is now known, and there is no further effort to doing that.
  • Seller risk is low, because they will at least cover their costs (except for a smaller than usual number of returns for refund).
  • Both benefit by getting more customers to try the product.
  • The bigger benefit is in cooperatively seeking a fair profit margin. Sellers who are happy can decide just how happy they are, considering all relevant factors, now that the value is known -- and can set the bonus prices accordingly. Sometimes this process might lead to a price below a conventional price, sometimes above, but in any case it leads to repeat customers with loyalty.
  • The reason that is important is the "long tail of prices." Some buyers will happily pay more than a conventionally pre-set price, and that generates added revenue. Many buyers (the long tail) will be unwilling to pay a conventionally pre-set price, but would be willing to buy the product at the lower base price, and then consider adding a bonus. Any added bonus is added profit. Thus the seller sells more products and makes more buyers happy.
  • This can work especially well for quality producers who delight their customers and motivate them to pay generously by triggering the use of communal norms. If Everlane's experience is like that of other PWYW vendors, positioning as a dedicated provider of quality and service can elicit high levels of fairness under communal norms.
  • In the case of artisanal/craft products like on Etsy -- and building on the person-to-person nature of sales in such a marketplace -- communal norms of fairness should be especially applicable to motivate high levels of generosity.
The key to making this profitable and manageable is the fairness reputation tracking and feedback controls of FairPay. The seller (or platform) can track how individual buyers respond to individual offers (and sellers), to learn how fairly a buyer sets prices for what kinds of products (and from which sellers). This provides a database on value perceptions and fairness for each buyer that can be used to manage what is offered to specific buyers (by which sellers), so that sellers can control their risk and nudge individual buyers to maximize their fairness.
  • Offers can be restricted to only those buyers who have a reputation for pricing fairly for the class of product being offered, so that sellers have a reasonable expectation that they will set a fair bonus price.
  • Sellers can decide how much risk they want to take and how wide a market reach they want. Those who prefer a lower number of sales at higher prices can limit their offers to those known to price generously. Those more eager to expand the quantity they sell, at some greater risk to their profit margin, can expose offers to a broader segment of buyers who price fairly but less generously.
  • Some sellers will set liberal fairness thresholds for some products for unknown buyers, so that their behavior can be learned at manageable risk. They may do this with selected product lines (or for limted promotions like Everlane's Christmas sale) that they can use for testing. Tighter fairness threshholds can be applied for sellers or product categories for which they want only more generous buyers.
  • In the case of a multi-seller marketplace like Etsy, the personal reputation data of buyers that is collected by the marketplace need not be exposed to individual sellers (to protect privacy) -- the marketplace can simply avoid matching a buyer to offers from sellers who set a fairness rating threshold that is higher than the buyer's fairness rating. All the seller knows about the buyer is that any buyer who see their offer has at least the desired fairness rating.
  • This mechanism gives a buyer a strong incentive to price fairly and even generously, to maximize the number and quality of offers they see. Buyers will know that it is the most desirable offers (and the most desirable sellers in a multi-vendor marketplace) that set the tightest fairness thresholds -- so the less generous they are, the fewer top quality offers they can expect to see in the future.
Why would this work?

Consider the lessons of conventional pay what you want (PWYW) offers.
  • PWYW has proven reasonably effective for both virtual and real products/services. People can be motivated to willingly pay fairly even when they do not have to.
  • Many sellers of digital products like music and games have done PWYW offers with a minimum price set to at least cover download and credit card transaction costs, with good results. (Additional evidence may come from sellers like Everlane.)
  • Research studies suggest that price floors can be effective, but there is a downside to consider -- setting a minimum can signal a lack of trust in the buyer, or leave the impression that a fair price is not much above the minimum.
  • In the case of real goods with substantial costs, it seems likely that the risk-mitigation of a price floor is more important than the signalling concerns.* Care in framing the floor price as not really fair -- in that it provides no profit and is thus not sustainable -- can help push generosity upward -- as can care in how the suggested profit margin is framed.
So it seems there is good reason to think this could work well for many real goods. Everlane seems a promising example, as a retailer seeking to establish an image for value, fairness, and transparency. Similar advantages may be applicable for design/craft/artisan products -- the seller can emphasize the human value of the artisan. Such use of FairPay could benefit a multi-seller marketplace like Etsy, especially where buyers are unsure what to expect from a seller they do not know (and vice versa). This could be good for the buyer, good for the seller, and good for the marketplace.

Could it work for very high-end products? -- such as for Tiffany? Perhaps not as well as conventional pricing, since at the very high end, high set prices are a signal of exclusivity -- a vendor with cachet like Tiffany can command prices that less prestigious brands cannot. I would guess Tiffany will be among the last places to try FairPay, for that reason. But who knows what variations might become workable once FairPay becomes widely used and understood?


[Update 12/31:]  Wide press coverage of this sale in Business Insider (twice), NY Magazine, Inc, HuffPost, Daily Mail, and others shows the promotional value of PWYW offers, Hopefully they will also report on Everlane's results.

Some of this coverage raised concerns about how well PWYW works, notably in NYMag. Here is an expansion of comments I posted on that article:

This raises many interesting and important questions about how to apply new participative pricing methods like pay what you want (PWYW) that try to find a win-win with the customer -- but we are at very early stages of understanding how to do them most effectively. I believe Everlane is on the right track, and that with proper framing of the offer, and what is expected of them, PWYW -- and more advanced variations on it, like FairPay -- will change how we buy things.

The cited research by Gneezy (which I included in my Resource Guide to Pricing) and others is very interesting, and offers many insights, but does not tell us what results can be obtained with better framing (and after people gain familiarity with such new approaches). A more established example of PWYW is tipping in restaurants. True, it makes some people a bit uncomfortable, and some want to eliminate it, but most of us manage to do it as second nature (apart from any arithmetical challenges that an online system would eliminate). We simply look back on the experience and consider whether service was better or worse than average (intuitively considering many factors, including how we feel about the server, and our plans to frequent the restaurant in the future), to come up with a tip that seems about right. With some experimentation, much more effective variations on how to present PWYW offers can be explored and refined.

(BTW, Panera has been doing PWYW continuously since 2009 in their Panera Cares locations, and are now serving about one million people per year.)

Simple improvements to PWYW:  Here are two very simple things Everlane and others could test to improve their results (even without the sophisticated feedback control process that FairPay adds):

  1. Provide a slider that allows any price within an allowable range. For the coat example, the quantum jumps in the allowed prices are quite large: from $110, to $132, to $225. Maybe I am willing to pay $150 or $175 because I want to support them, but $225 just seems a bit steep for an overstock sale -- but I only pay $132.  The same framing levels could be presented, but with the ability to pick an intermediate price that seems fair to me.
  2. Let people pay the base price up front, and then follow up to ask them to decide on the bonus price after they receive the product and know how they like it. This would be only a bit more complex to do, would still assure costs are covered, but would gain all the benefits of post-experience pricing. Instead of wondering if I will really like the coat, and pricing low, because I am afraid to end up disappointed, I would know how much I liked it, and not have to discount from what I would later agree would have been fair.

*Of course a price floor can be used in any FairPay context, including digital goods with low marginal cost (just as is done for PWYW offers). Market testing (as by Everlane) is needed to understand under what conditions that is desirable, and how to set and frame such a minimum price.

(Acknowledgement:  My thanks to Florian Gypser, an architect and designer based in Austria and Thailand who contacted me to inquire about using FairPay for consumer fashion products. That led me to begin this post, to highlight these opportunities. ...And to Everlane for provding a nice case study -- which I hope they will add to with a report of their results.)