Tuesday, January 24, 2017

What Lies Beyond Paywalls -- A Better Way

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

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

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

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

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

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

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

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

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


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

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

Tuesday, January 17, 2017

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

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

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

FairPay as a change in behavior

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

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

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

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

Natural customers for FairPay

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

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

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

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

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

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

Natural businesses for FairPay

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

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

Grabbing the low-hanging fruit

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

Staging the learning process

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

The thin end of the wedge

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

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


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

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