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.)

Monday, December 7, 2015

Design Thinking for a Smarter Media Industry -- Redesigning the Customer Experience

A recent NY Times article on Design Thinking at IBM leads me to suggest how movement toward the FairPay architecture can complement and help fuel the trend toward design thinking -- especially for digital content and services (notably in the media and entertainment industry). That article suggests that "In the design thinking way, the idea is to identify users’ needs as a starting point" and that it involves "user journeys" and understanding user "empathy maps." I suggest that FairPay helps move us toward better design thinking at two levels:
  • As a form of design thinking, FairPay makes consideration of the user -- and empathy and experimentation related to that -- central to every customer relationship.  FairPay is a new logic for conducting ongoing relationships that adaptively seek win-win value propositions in which price = value. FairPay sets prices through an emergent process of ongoing experimentation, with the full participation of the customer. This shifts the entire focus of customer relationships from price to value.
  • FairPay can help drive entire businesses and industries to re-center on design thinking -- by shifting the customer journey to drive dialog with customers about value propositions -- and to reflect that in pricing, so that it factors directly into the bottom line. That can drive everything else.
My own career-long focus has been on what I have called "user-centric" thinking (my half century in media technology began with a user focus, and on the customer side of IBM, with two decades inside IBM "large account" customers, before shifting to media technology entrepreneurship).
  • That focus is what led me to develop the FairPay architecture as a more user-centric form of customer relationship that solves many problems inherent in our old logic of seller-set prices,  take-it-or-leave-it value propositions, and inhospitable customer journeys. 
  • FairPay is built on consumer participation in pricing, as an emergent process that seeks adaptively win-win value propositions. It adds explicit dialogs about value as a core process within every customer journey cycle
FairPay is particularly well-suited to the media industry, where the new economics of digital content challenges traditional notions of value and fair price (as outlined on the HBR Blog). These challenges have put the news and music industries in disarray, and are disrupting TV/video, games, books, software, and other digital services.

There is growing recognition of the problem, and the strategic opportunity for more adaptive and user-centered thinking, as exemplified by this NY Times article and the recent Harvard Business Review cover articles it refers to. There is also growing recognition in the media industry that piracy and ad-blocking are symptoms of customer-hostile value propositions, and that what is needed is not more coercion, but more cooperation.

Having gained recognition of the potential of the FairPay concept from Jim Spohrer, who was the driving force behind IBMs Service Science initiative, I hope to find wider interest in this new strategy from elsewhere in IBM, as well as other companies providing business strategy and process improvement services to the media industry. My hope is that such service providers will help executives in media businesses appreciate the strategic importance of experimenting with unconventional business strategies like FairPay. Again, the appeal here is that the win-win customer journeys of FairPay not only embody design thinking and service-dominant logic, but bring it directly into the bottom line, to help fuel a broader transformation in business.

Specific to the media industry, an IBM white paper is entitled "Smarter Media and Entertainment: Reshaping the operating model and the customer value proposition in the era of big data." While there is obviously much to do in that regard, and much progress is being made, I submit that FairPay provides processes for taking this far deeper than is generally recognized to be possible.

I am now devoting much of my time to developing FairPay as a pro-bono project, because I think it can change the world for the better. I would be happy to work with media companies and their service providers to help develop these concepts and prove them in practice (at no charge). I am also collaborating with some eminent academics who can help with that, and have some interest from media subscription platform providers.  (I welcome inquiries at fairpay [at] teleshuttle [dot] com.)

Background on FairPay and how it works

To understand just how FairPay can fuel this transformation, see the Overview of FairPay 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, November 23, 2015

Forrester's Next Wave? -- Adaptive Subscription Billing with FairPay (+ Zuora, Vindicia, Recurly, Digital River...)

The recent inaugural Forrester Wave Report on Subscription Billing Platforms, shows that the trend toward subscription models -- as an aspect of relationship marketing -- has become very important in many industries.
Key drivers behind the experimentation and subsequent adoption of transformative business model relationships include a desire for stickier customer relationships, a thirst for customer insights, an eagerness to capitalize on the cloud, and an inclination to experiment with connected products.
The next-generation FairPay strategy (as described on the Harvard Business Review Blog) has not yet surfaced through Forrester's radar, but it is on the radar of some of the companies Forrester reviewed, including Zuora, and Vindicia.

FairPay further transforms subscriptions and similar recurring relationships, to re-center the customer journey on value -- adaptively seeking win-win value propositions. This can change the fundamental nature of the customer relationship and how we think about pricing and selling services. It is especially relevant to B2C businesses (and SMB-oriented B2B).

Companies in the subscription/recurring revenue space should be thinking about FairPay and how to do controlled trials to see how it can transform their business. More about that below, but first some general insights from Forrester. (A free copy of this $2,495 Forrester report is available from Zuora.)

"Innovation Is Enabling An Era Of Continuous Customer Relationships"
Firms are shifting from one-time perpetual sales or fixed monthly subscriptions to consumption models that blend one-time, subscription, and usage-based billing... CEOs recognize this shift toward business models that reflect the value of the relationship with the customer:
“There’s a secular movement that’s happening . . . more to an annuity relationship as well as a subscription relationship. These are the long-term relationships we want to have with all customers.” Satya Nadella, CEO Microsoft (May 2015)
“If you went to bed last night as an industrial company, you’re going to wake up today as a software and analytics company.” Jeff Immelt, CEO GE (October 2014)
“We’ve gone from selling boxes, cloud, mobility, or any other solution, to partner with customers on their outcomes.” John Chambers, CEO Cisco (May 2015) 
The report outlines "four key drivers behind the experimentation and subsequent adoption of transformative business model relationships that firms have with their customers" -- two of these are significantly enhanced by FairPay:
  • A desire for stickier customer relationships. ... an additional emphasis on loyalty...
  • A thirst for customer insights. build long-term relationships, monitor engagement, and perform sentiment analysis. 
The eight vendors Forrester reviewed all serve both B2C and B2B businesses, "Zuora, Vindicia, Digital River, and Recurly had unique strengths in supporting consumer or hybrid B2C or B2C-focused subscription scenarios." ("Apttus, Aria Systems, goTransverse and SAP hybris were especially well suited to supporting complex B2B billing scenarios.")

Forrester also noted that some of these vendors have strong relationships with Big Five consulting firms, as well as many ERP and CRM platform providers.

I have had discussions with some of these companies (notably Zuora), and have had expressions of interest by them in adding FairPay support to their offerings if a customer has interest. Should your firm want to consider testing FairPay, please contact me to assist in assembling the appropriate resources (including such platform vendor services, as well as academic researchers willing to help design and evaluate trials). I have been working on FairPay as a pro-bono project, and am happy to explain the concepts, and help companies develop applications of it, at no charge.

How FairPay strengthens customer relationships to change the subscription game

Why you should want to try FairPay? The short answer is better and more profitable relationships with more customers who value your services. It is especially attractive in markets like digital content and services that offer experience goods that are cheap to replicate but costly to create, and for which managing and quantifying the customer's perception of value is a challenge not well met by one-size-fits-all pricing methods. FairPay adaptively seeks personalized price discrimination in a way that customers accept as fair.

This blog includes an Overview of FairPay and a 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). Some of the posts most relevant to subscription billing platforms are:
A significant and growing portion of our economy is conducted in ongoing customer relationships -- FairPay is the way to adaptively seek win-win in those relationships, to make them stronger and more profitable over time. Let's work together to see how to make that happen for your business.

Wednesday, November 4, 2015

Price = Value

Price = Value. The essential logic of FairPay is that Price = Value context, and over time.  Or at least it should, and an efficient economics will seek to approximate that.

Isn't that only fair? -- the only win-win way to do business? Why should we -- both producers and consumers -- settle for prices that are anything less than the best reasonable approximation of the actual value we receive?

FairPay is a new logic for conducting ongoing relationships that adaptively seek win-win value propositions in which price = value.

  • The core idea is that prices should equate to value. Not the producer's preconception of value for an average consumer, but what value a particular consumer actually perceives as realized  in the experience of using the product or service, in the fullness of their individual context.
  • Such a concept of price = value is win-win for both the producer and the consumer. They agree to do business if they expect a value surplus over cost, and both benefit if they divide that value surplus fairly -- fair value to the consumer, while providing a fair profit to sustain and motivate the producer. It allows a producer to provide value to a maximum number of consumers who seek it, in a way that can maximize revenue and profit as well -- especially for products and services (such as digital content) for which consumers may challenge any pre-set price as arbitrary and unfairly out of line with their actual perceived value.
  • Adaptively seeking such win-win value propositions is required because the valuation considerations are complex. It is hard to do this accurately for any one transaction (which is why value-based pricing is now done only in high value B2B contexts). But an adaptive, intuitively reasonable approximation can be cooperatively converged upon over a series of transactions -- and can continuously adjust as things change over time.
  • Ongoing relationships provide an environment that justifies and enables the process of adaptively seeking those win-win value propositions. If the marginal costs of the product/service are low, producers can afford to take limited risks at the start of a relationship (just as they do with free trials or freemium), in hopes of building a productive and loyal relationship that is profitable over the lifetime of the relationship.
  • FairPay is a new logic in that this idea -- that price must be co-created, as a dynamic and personalized approximation of value as exchanged -- creates a very different conceptual framework for how our markets work. It shifts us from a mentality of take-it-or-leave-it prices pre-set by producers, which are often unfair, to a cooperative process of creating value in a way that explicitly seeks to be fairly win-win.
From this perspective, FairPay is a form of co-pricing for services, in which buyer and seller agree on a process to adaptively seek a win-win value exchange -- not focused just on single transactions, but over the life of their relationship. That ongoing relationship perspective opens up a whole new dimension in customer relationships that can deeply alter how we do business -- transforming the nature of the customer journey, as well as the workings of our broader business ecosystems.

This formulation encapsulates the core conceptual perspective that I have absorbed over the past year, drawing on current marketing and service science theory (see my recent posts about ISSIP and the Naples Forum on Service).

Those with a purely practical focus might skip the rest of this post and turn to more pragmatic information on FairPay. The core dynamic of the FairPay choice architecture is described in the sidebar and the practical implications and applications to various businesses are discussed throughout this blog. Check out the Overview, and More Details

Conceptual Perspectives on this New Logic for Business
The greatest danger in times of turbulence is not the turbulence, it is to act with yesterday's logic.   --Peter Drucker
That quote is one of the inspirations behind an emerging reformulation of marketing -- the idea of a "Service-Dominant Logic" (S-D-L), in contrast to the "Goods-Dominant Logic" that developed over the past centuries -- "yesterday's logic." Now we are in a service economy, and are beginning to see that the value of goods is really in how they enable a service -- for example, the value of a car has little to do with the physical product in itself -- its value is in how it provides the service of transportation, in a particular use and context. Is it reliable, comfortable, safe, economical, fun? what mixture, to meet what needs? (Long ago a wealthy friend of mine owned an expensive new Jaguar, but was afraid to drive it far from home for fear it would break down -- high price, costly to create, but low value.) The value of services is understood to be "co-created" by the provider and the consumer in a particular use-context. This has many important implications that have been the subject of an extensive body of work. Proponents of this thinking (including the related field of service science) have been among the most receptive to the ideas of FairPay, such as at my Naples Forum and ISSIP presentations.

I pick up on this further now, by suggesting that what FairPay adds might be thought of as a Value-Dominant Logic (V-D-L) -- as opposed to yesterday's Price-Dominant Logic (P-D-L). FairPay offers a process for seeking fair value, in which price becomes emergent from buyer's and seller's interactions over time. Thus price remains the metric of net value-in-exchange, on which our economy is centered, but now price tracks to value-in-context instead of being pre-set in ways that track poorly to value. The processes of FairPay -- as embodied in cycles of customer journeys -- set price to approximate value. This not only can transform business, but makes a better economics, because prices that track to value make the economy more efficient and productive.

This builds on an earlier post that describes a thought experiment based on imagining an economic demon that reads the minds of buyers and seller to determine the actual value-in-context for each transaction, figures out the value surplus (over cost), and negotiates an equitable sharing of that value surplus between the producer and consumer. Prices set by such a demon would be win-win for both sides. The FairPay process of repeating dialogs about value over a series of transactions serves as a way to approximate what that demon knows, at least on average, over time.

Another post describes how this can be viewed as an invisible handshake -- an agreement between the producer and consumer to work together through the FairPay process to try to come to a common understanding of individual value propositions over time. While this emergent approximation may not be very accurate for any one transaction (especially when the relationship is new), the process seeks to converge on a level of fairness over time, as the parties get to understand one another.

This is win-win for producers and consumers because it allows producers to sell to all consumers who find value in the producer's service, at prices that are dynamically personalized to approximate ideal price discrimination.  That leads to a near-maximum number of profitable and loyal relationships, to maximize total revenue and total value creation. It also enables a near-maximum number of risk-free trials by consumers who think they might find value. All of this brings more value to more people.

Price ≠ Value

We are so used to our current practices of seller-pre-set prices that discriminate poorly (yesterday's logic), that we tend to not realize how that distorts our economy and makes it inefficient. Why do all users of a service -- such as digital newspaper or digital music or video subscription service -- pay the same price? Some use such services heavily, others lightly. Some obtain high value from the services, others just minimal levels of value. Yet they all pay the same price. Not only is that unfair, but it distorts our markets, as a deadweight loss. Many pay less than they should -- and many forgo using such services at all because they the price is too high, even though a lower price would create value and profit.

At a theoretical level, one of the open challenges of service research is that its focus on value-in-context works well at a microeconomic level, but does not translate well into macroeconomics, because value-in-context is hard to measure at a macro level. I suggest the reason is that macroeconomics is centered on price, and in current practice Price ≠ Value. How can our macroeconomics be effective when Price ≠ Value? Revenue is the total of a firm's prices, but total revenue tracks poorly to total value. Similarly for GDP. If we can get prices to track better to value, then our whole economics will be centered on that, and will work better.

Broad considerations of value

Another implication of this Value-Dominant Logic is that value should be very broadly defined to include all aspects that matter to the producer and consumer. Many of the current challenges in getting businesses to better address social values stem from the limited scope of prices, since they are not set to reflect such broader values. We speak of Corporate Social Responsibility (CSR) and Creating Shared Value (CSV) and triple or quadruple bottom lines because our current bottom lines are missing many important components of value. Here again, FairPay provides a rich broadening -- Price = Value, including whatever social aspects of value matter to the consumer. If the consumer values broader social benefits, they can reflect that directly in the price they pay, which then adds directly into the bottom line..

Making it happen

It seems clear that we should be seeking prices that map better to value. We should be exploring how to do that. FairPay suggests an architecture for a process that does that. If the particular process I suggest is found to not work as well as hoped, perhaps understanding why, in detail, will lead us to variant processes and/or process architectures that will work better. One way or another, going down this path should lead us to more value for all of us.

Monday, November 2, 2015

How Consumers Can Nudge Corporations for Good

Richard Thaler raised some interesting points about The Power of Nudges, for Good and Bad in a NY Times opinion piece on 10/31. "Nudges, small design changes that can markedly affect individual behavior, have been catching on" he observes, and then explains his concern that "Many companies are nudging purely for their own profit and not in customers’ best interests."

He concludes the piece with this observation (emphasis added):
As customers, we can help one another by resisting these come-ons. The more we turn down questionable offers like trip insurance and scrutinize “one month” trials, the less incentive companies will have to use such schemes. Conversely, if customers reward firms that act in our best interests, more such outfits will survive and flourish, and the options available to us will improve.
I take that as a nice statement of the power of FairPay, a new framework for choice architectures designed to use the power of nudges to adaptively seek win-win value propositions, and to directly reward firms that work with us to serve our joint best interests.

  • Using FairPay, firms and consumers can jointly create a virtuous cycle in which the consumer nudges the firm to understand what they value and are willing to pay for, and the firm rewards those consumers who work with them by delivering more of what those consumers show that they value. 
  • This builds customer journeys around cycles architected to build a mutually beneficial relationship of service, value, profit, and loyalty.

From this perspective, the appeal of FairPay is in how it deepens the relationship between a firm and its consumers to be more open and responsive, and shifts focus toward value -- in context, in the broadest sense, over the life of the relationship,

  • It not only channels the nudges from the company to the consumer, but also creates a framework for nudges from the consumer to the company. 
  • Consumers who use FairPay fairly will get the most value, and companies who use FairPay effectively will attract and keep the most profitable and loyal customers.

- - -

The core dynamic of the FairPay choice architecture is described in the sidebar and the broader implications are discussed throughout this blog. (Check out the Overview, and More Details.)  Some posts of particular relevance to nudging for good:

Monday, October 26, 2015

New Video on FairPay -- Reisman Presentation to ISSIP 10/14/15

Video is now online at ISSIP from my 10/14/15 presentation on FairPay. ISSIP is the International Society of Service Innovation Professionals, "a professional association co-founded by IBM, Cisco, HP and several Universities with a mission to promote Service Innovation for our interconnected world."  
Video Details:  This is about 24 minutes of presentation, plus some Q&A, with a very interesting and interested audience. A full slide set (including some supplementary slides not on the video) is also online. (Should there be any difficulty with those links, there are alternative locations for video and slides, and future updates of presentation slides will also be online.)
I was introduced to ISSIP when I met Jim Spohrer of IBM, one of its founding board members, at the Naples Forum on Service in June. Jim immediately saw the appeal of FairPay, and how it embodies many of the principles ISSIP is helping to illuminate. He has been very supportive in introducing me to the ISSIP community. That led to this presentation, which was facilitated by Haluk Demirkan of the University of Washington.

As my still-formative and in-expert encapsulation of how FairPay fits with service science and Service-Dominant Logic (S-D-L), these teachings suggest that much of our conventional thinking relates to "Goods-Dominant Logic" that developed over the past centuries -- "yesterday's logic." But now we are in a service economy, and are beginning to recognize that goods matter only in enabling a service -- for example, a nail has little value in itself -- its value is in how it provides the service of fastening, in a particular use and context. The value of a service is understood to be "co-created" by the provider and the consumer in its particular use-context.

From this perspective, FairPay is a form of co-pricing, in which buyer and seller agree on a process to seek a win-win value exchange over the life of their relationship. That opens a whole new dimension in customer relationships that can deeply alter how we do business. (Details of how are in the video, and other pages here.)

One perspective on this might be thought of as Value-Dominant Logic (V-D-L) as opposed to our current Price-Dominant Logic (P-D-L). FairPay offers a process for seeking fair value, in which price becomes emergent from buyer and seller's interactions over time. Thus price remains the metric of net value-in-exchange, but now price tracks directly to value-in-context instead of being pre-set in ways that track poorly to value. The processes of FairPay -- as embodied in cycles of customer journeys -- dynamically set prices to approximate value. This not only can transform business, but makes a better economics, because prices that track to value make the economy more efficient and productive. (Some insight into this stems from my thought experiments relating to an all-knowing economic demon.)

The idea is very simple: P=V. Price = Value (in context). Price should at least seek to approximate value over time. Doing that would make our economy work better for all of us. FairPay suggests a way to adaptively seek P=V. (I plan to expand a bit on this in a separate post.)

On the video, after the talk, is a few minutes of Q&A, with some very interesting questions.

(To add one clarification, I should have given a fuller answer on the first question in the Q&A. The question was about crowdfunding and crowdsourcing. I neglected the second part, and would add this: Crowdsourcing fits very nicely into the FairPay logic, since it is just another form of value, which flows in reverse, from consumer to provider, and just one more dimension of value to be mutually considered and netted out in the "dialogs about value," Just as value from the provider can be measured and then valued, so can value from the consumer.)

Saturday, October 17, 2015

Win-Win Customer Journeys -- With Dialogs about Value

Competing on Customer Journeys is a very interesting article in the 11/15 HBR that presents an emerging marketing paradigm, one that provides just the context for a further step of proactivley ensuring the journeys are maximally win-win. The subtitle is "You have to create new value at every step" -- my work on FairPay suggests a way to enrich the customer journey to do that much more explicitly and effectively.

Edelman and Singer explain that:
The explosion of digital technologies over the past decade has created “empowered” consumers so expert in their use of tools and information that they can call the shots, hunting down what they want when they want it and getting it delivered to their doorsteps at a rock-bottom price...  
Rather than merely reacting to the journeys that consumers themselves devise, companies are shaping their paths, leading rather than following. Marketers are increasingly managing journeys as they would any product. Journeys are thus becoming central to the customer’s experience of a brand—and as important as the products themselves in providing competitive advantage.
They suggest how this can enable "a 'loyalty loop,' ... a monogamous and open-ended engagement with the firm:"

I suggest that this is a big step forward in developing long-term profitable customer relationships, and that it meshes well with the similar kind of continuing feedback loop that drives FairPay. The idea that FairPay adds is to insert "dialogs about value" into each cycle of the journey after the "enjoy" step -- when the consumer knows the value of the experience -- and to adapt the pricing based on that. The enables participative personalization of the value proposition, as a simplified form of value-based pricing:
  • Buy
  • Enjoy
  • Value (added -- dialogs about value, to personalize the value proposition)
  • Advocate
  • Bond
Without this added step, the loyalty loop does not fully realize a central driver of engagement and loyalty -- a proactively personalized value proposition that is win-win for both the consumer and the firm. Without this we just perpetuate the idea that the firm decides on value propositions and tries to coax consumers into accept them. Adding explicit value assessment into the loop engages the customer more deeply and enables the firm to serve the customer far more effectively. This participative element builds consumer loyalty by demonstrating the firm's commitment to learning exactly what each customer values in varying contexts, and seeking to deliver it by customizing the value proposition to match.

Edelman and Singer go to the threshhold of this, and we just need to add this one more step (emphasis added):
We’re now seeing a significant shift in strategy, from primarily reactive to aggressively proactive. Across retail, banking, travel, home services, and other industries, companies are designing and refining journeys to attract shoppers and keep them, creating customized experiences so finely tuned that once consumers get on the path, they are irresistibly and permanently engaged. Unlike the coercive strategies companies used a decade ago to lock in customers (think cellular service contracts), cutting-edge journeys succeed because they create new value for customers: Customers stay because they benefit from the journey itself.
As emphasized on this blog, the driving goal of FairPay is to make price=value, over time. When it comes to value propositions, firms remain coercive, effectively saying: "We give you this value package for this price. If you don't like that, how about this other value package for this other price? If none of our options suit you, we are not listening -- you will have to settle or go elsewhere." FairPay dialogs about value open a new dimension of adaptivity and dialog to personalize value propositions based on individual context, needs, and value perceptions. These dialogs about value become central to the journey, and a key driver of the loyalty cycle. How that is done is shown in the sidebar, and expanded on in the Overview and More Details pages.

Adding this focus on value does not just increase loyalty, but promises to dramatically increase profitability as well. The article presents an example about Sungevity, a provider of residential solar panels:
Sungevity is ... using what it knows about its customers to extend the journey... With granular data on each household’s energy use and habits, Sungevity can advise people one-on-one about managing their energy consumption, and it can recommend a tailored package of products and services to help them reduce their dependence on the grid and reap savings. ... Ultimately, the firm plans to integrate its services with home-management networks that can automate energy conservation (adjusting lights and heating, for example) according to decision rules that Sungevity develops with each customer. Another project is to create conservation-oriented customer communities. 
The value step I propose would bring value pricing into this journey -- in a uniquely simple and lightweight form -- to enable Sungevity to evaluate the savings their services actually deliver to the customer, and to engage in dialog with the customer to share a portion of that value with them. Rather than expecting the customer take a risk that they will get a predicted value, and discounting the price they are willing to pay to allow for that risk, Sungevity can design the journey to share the risk, measure the realized value, and share in that value. Examples of how effective such value pricing can be are in this other HBR article.

FairPay is a very natural extension to the customer journey perspective. Edelman and Singer explain that "The move from selling products to managing a permanent customer journey has required mastering the four capabilities that all companies will need to compete: automation ...; personalization ....; contextual interaction ...; and journey innovation .." The same four capabilities support FairPay as well. 

As the new "logic" of customer journeys becomes accepted in marketing, the related new "logic" of FairPay" and its adaptively win-win value propositions should become increasingly accepted as well. Different levels of FairPay empowerment may be applicable to different consumers and different business contexts, but a more explicit focus on value can benefit almost any customer journey.

Tipping, Fair Pay, and FairPay

Tipping in restaurants made the news this week, raising many questions about "fair pay" the social movement toward fair wages -- but also bearing on the very different issues of "FaiPay" the new strategy for value-based consumer pricing described on this blog (and outlined on the Harvard Business Review Blog).

The news is that the prominent NYC-based Union Square restaurant group is phasing out tipping entirely in most of its restaurants (Union Square Cafe, Gramercy Tavern, The Modern, ...). This is a very complex issue, as noted in the NY Times article on 10/15/15, including issues of customer service, fair wages for labor (the "fair pay" issue), economic policy (do minimum wages apply to tipped workers) and even tax policies.

As described in other posts and the sidebar, FairPay is a strategy for setting prices with user participation, having elements of pay what you want (PWYW) that are much like tipping.

  • What FairPay adds to PWYW is that it is applied in the context of a relationship that continues only as long as the payments are considered fair by the business. Thus the consumer can pay any price they want for a given transaction, but the business can decide to stop offering FairPay transactions to a consumer who they consider to be free-riding. That gives the consumer strong reason to pay fairly, to maintain that privileged relationship.
  • This works very much like restaurant tipping -- especially in the case of diners who might be regulars at a given restaurant, and thus concerned about their reputation for tipping fairly, and how that affects their ongoing relationship with their servers (who may provide less service to those they feel were unfair, and superior service to those who are generous). So the behavioral economics of tipping, and of PWYW, are very relevant to FairPay.

My focus here is not on the complex issues of wage equity in restaurants, but on the behavioral economics of the FairPay model -- as applied to other kinds of value exchange -- how tipping sheds light on broader issues of customer value propositions. Still more broadly, these are questions of the overall effectiveness of how businesses relate to their customers, and the processes for determining how value is shared among consumers, businesses, and workers.


The essence of FairPay is the idea that price should correspond to value -- as actually experienced by the customer in the full context of that experience, as it evolves over the course of the relationship. It is based on open dialog and transparency about the value exchange, the costs, and the economic value surplus that is "co-created." If the parties behave fairly, this lead to economically optimal pricing that produces the greatest overall value for all. The details all have to do with getting that fair behavior.

The Times article on tipping makes some interesting points. One is very supportive of this core benefit, an agreed to value exchange that is win-win for both sides:
Many customers remain deeply attached to the right to reward attentive service, or to withhold that reward. And servers often say that the bonanzas they take home after busy nights far outweigh the risk of getting nothing once in a while.
It is widely recognized that when restaurant service is built into prices, with no discretionary reward for service quality, quality is often poor and customers dissatisfied. There are of course some customers who tip unfairly (or not at all), and depending on the demographics of the clientele, this may or may not be a serious problem. But presumably the problem decreases among regular customers, and it is in just such long term relationship contexts that FairPay seems most likely to do well (and I suggest that its use be limited to such contexts). Just to reinforce the key points, I repeat that quote, with added emphasis:
Many customers remain deeply attached to the right to reward attentive service, or to withhold that reward. And servers often say that the bonanzas they take home after busy nights far outweigh the risk of getting nothing once in a while.
Better for both parties!

Clarity and transparency

As always, the devil is in the details, and there is much complexity here. Some of that relates to clarity and transparency as to who is being compensated for what. Another quote:
By increasing prices and ending tips, Mr. Meyer said he hoped to be able to raise pay for junior dining room managers and for cooks, dishwashers and other kitchen workers. Compensation would remain roughly the same for servers, who currently get most of their income from tips. Under federal labor laws, pooled tips can be distributed only to customer service workers who typically receive gratuities, and cannot be shared with the kitchen staff or managers.
Much of that was news to me, in spite of having tipped in NYC restaurants many hundreds of times over many decades. My impression was that it was the servers who got the tips, not the kitchen staff (but I was not sure if that was always true), but I still have no clarity on whether my tip goes to my waiter alone, to all waiters, or to other service staff (which I presume varies with the restaurant). Makes it hard to know what is fair doesn't it? Without knowing who my tip goes to, it is hard to be fair. But if I know what goes to my server, I have a pretty good sense of the fairness of that (as long as I am cognizant of the common "reference price" that 20% is fair for a normal level of good service).

Another aspect of transparency is that the "dialog" about value in a restaurant is very limited. There is the service and the tip, and maybe some polite chatter or body language, but that is about all. It is rare that either party communicates specifics as to why a given tip might be fair or not.  FairPay suggests that convergence on a mutually desirable exchange will be most effective with clear dialog on what is or is not working with all aspects of the value proposition. That may well be awkward with a restaurant server, but it can be very direct with a business that uses modern computer-mediated dialog services such as feedback forms, and that invites and responds to such dialog.

So the NYC restaurant issue involves many factors not directly relevant to FairPay as it applies to other industries -- such as service versus kitchen staff and wage and tax laws -- but the essence seems to reinforce evidence from studies of PWYW in other contexts that people do pay fairly when given clear information on what they are paying for and why. It seems the problem with tipping is not that it doesn't work well for servers, but that other workers are not doing as well. The article goes on:
“The gap between what the kitchen and dining room workers make has grown by leaps and bounds,” Mr. Meyer said. During his 30 years in the business, he said, “kitchen income has gone up no more than 25 percent. Meanwhile, dining room pay has gone up 200 percent.”
This begs the question of why take tipping away from those it works for? Tipped workers were clearly much better served than non-tipped workers. (As a reference point, the CPI increased 221% in the past 30 years.) Again, my issue is not whether tipping is good labor practice, but what this tells us about pricing models more broadly. It may well be that tipping is less effective in less high-quality, service-oriented restaurants (or where waitstaff may be at risk for abuse by customers or management). But it is those contexts where quality and service are key elements of the value proposition that I suggest are the prime opportunities for FairPay.

Computing value

Another thing that tipping teaches about FairPay is how easy it is for people to compute value intuitively. On hearing about FairPay in other contexts, such as for digital content subscriptions, people often ask "isn't it a difficult cognitive burden for customers to have to think about the value?"

But tipping provides a clear answer -- this computation is not difficult -- it is highly intuitive. We easily do a complex multivariate, multi-dimensional analysis in our head, during and after a meal and know immediately whether we think the service was average, or better or worse, and by roughly what degree. We can then easily figure whether we adjust our average tipping level up or down, and whether to adjust for being a regular or any other special factors, to conclude that we should tip X%. Any computational difficulty is just doing the arithmetic of how much x% of the bill is (with or without tax, rounding, etc.). Other complications relate to whether our tipping is visible to others in our party that we might want to impress -- which is something that may or may not be relevant in FairPay contexts, and may not be much of a problem even when it is a factor.

So all in all, it seems the behavioral economics of tipping is very supportive of the idea that FairPay will prove very effective in selected business contexts. Whether tipping can and should survive in restaurants -- given all of the unique social, labor, and legal issues involved -- is a different question.