Tuesday, October 3, 2017

No, Peggy, That is Not "All There Is" to News Reader Revenue!

In his Newsonomics series, Ken Doctor asks "is that all there is to reader revenue?" -- and reviews some signs of hope that there is more. I suggest there is actually much more -- because we are just beginning to rethink our value propositions for the strange new world of digital.

In homage to Peggy Lee's classic song, "Is that all there is?," Ken asks that specifically as it relates to "Who killed the new subscriber?" He answers that while we still hear Peggy's heartbreak, "we can also hear...the hum of new reader revenue strategies." He finds reason to be hopeful in the variety of emerging new models, but describes serious difficulties and gaps that leave a "great potential in-between." He ends on a more hopeful note from another Peggy Lee song, "somebody loves me, I just wonder who."

So the question is: how can I as a publisher get more people "to love me?" What Ken's review makes clear (in that article and its companion) is that we seem to be stuck with narrow point solutions that each address a segment of the market for a given publisher:

  • publisher paywalls that work marginally well for the most dedicated 1-4% of readers (at least for national/global news leaders, not so well beyond that), 
  • platform-based alternatives (including nascent platforms like Scroll, LaterPay, and Blendle, and, less satisfactorily, Google and Facebook) that seek to attract casual readers, 
  • but very little to address the missing middle. 

There is much ingenuity going into alternative models to address parts of this gap, but still, they are point solutions. Ken talks of going beyond "the binary world of pay/don't pay." He quotes Cosmin Ene of LaterPay: “Walking the walk would require a diversified approach to monetizing content, allowing individual sales and time-based models and not just trying to push towards subscriptions only. There is a whole universe living between ads and subscriptions.” True, but is this just a wider range of point solutions? Isn't there a more coherent solution? ...one family of solutions that can effectively serve a wide range of readers all the way from casual to dedicated? ...one that keeps publishers in a relationship with their readers all the way through each reader's life-cycle (the funnel into the loyalty-loop) as it grows (or not)?

How to get more readers "to love me"

To deal with this whole universe of readers in a coherent and effective way, publishers need to deeply rethink the fundamental economics and value propositions that underlie their relationship with each reader.

  • The problem underlying this narrow market for reader payments is not an inherent refusal to pay for news, but a problem of value propositions -- resulting from the rigidity of one size fits all pricing
  • For publishers it is a high all you can eat price, for Scroll it is a standard $5 shallow dive, up to the meter -- and for LaterPay and Blendle it is a high set price per article. 
  • Both publisher and Scroll subscription solutions may be bargains to some (not good for the publisher), but overpriced for many (also not good for the publisher, since readers cancel or never even subscribe), depending on usage any given month -- and LaterPay and Blendle are not very fair to any reader.
  • The "binary world of pay/don't pay" ignores the willingness of some (but not all) readers to accept some ads -- if they add value rather than subtract it, and if they get credit for their attention.
  • Adding a broader array of distinct point solutions will just confuse everyone.

Scroll and publisher subscriptions are nicely complementary, but both take a narrow approach to matching the price to an individual reader's value proposition. Scroll has a strategy that seems promising for the low side of usage, and publisher subscriptions are more or less workable at the high side, but, as Ken makes clear, both leave a big value-pricing gap in the middle. I suggest more variably-priced models are now workable and could be efficient and attractive across the full spectrum of usage.*

A more economically efficient solution would factor in usage -- not at a fixed price for any given article like LaterPay or Blendle, but rather, on a discounted sliding scale. Undiscounted per-article pricing makes consumers very fearful of the ticking meter, because it leads to overpricing and nasty usage shocks (which is why classic micropayment models have a history of failure). Conversely, even Spotify and Netflix (which publishers look to with envy) find that all you can eat subscriptions are underpriced for heavy users, and overpriced and shunned by many would-be casual users. That inefficiency is costly all around.

Why not a sliding scale of volume-discounted prices? Small numbers of articles would be at a relatively high unit price (much like LaterPay and Blendle, but preferably not that high), but increasing numbers of articles can be discounted to gradually approach the price per article that applies to a subscription -- less at moderate usage, but comparable at high usage. (And there could be price caps to avoid high-usage surprises.) Variable pricing may seem complex, but it can be made simple enough -- another post explains how this could be done for the very similar case of TV bundles.

This is really just a matter of value-based pricing, and of publishers taking more of the pricing risk from their readers. That will take new thinking and experimentation, but those risks are not really as great as the risk of not learning to apply a customer-value-first approach (for all of the reasons Ken outlines). The modern technology of customer journeys now makes personalized pricing very workable.

A shift toward more flexible pricing can also bring other important aspects of value and ability to pay into the picture -- to make prices fair for the fullest range of readers. Those who get high value and those who have high ability to pay can be reasonably expected to agree to pay more than those who get less value and who have lower ability to pay. Those willing to pay attention to acceptable levels of ads should reasonably expect a credit for that. Since replication of news is nearly free, the real objective to to get readers to sustain more creation -- and every contribution helps. Behavioral economics shows that people understand and respond cooperatively to that kind of logic -- if pricing is value-based, transparent, and framed properly. The FairPay strategy outlined on this blog points to new ways to do that efficiently on mass scale.

Love is a two-way street

Do better at offering each reader the value they want, at a fair price for each of them, and maybe publishers will find much more often that "somebody loves me."

After all, pricing, like love, is "a two-way street" (more songs). If you want someone to love you, you must think not of what they can do for you, but of what you can do for them. You must view your customer relationships (and how they center on value) through the eyes of the customer. Publishers still have far to go toward a customer-value-first mind-set, but the general direction is clear.**


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.

*Set pricing is a relic of the age of physical newspapers -- now obsolete. Readers got entire newspapers delivered (or at a newsstand). (And a few other readers bought single article reprints.) Not much opportunity there to price based on personalized value. But now news is an experience good, accessed on-demand from the cloud, in highly individualized usage patterns that are tracked in great detail. Value is much more highly variable, and no longer hard to determine.

**Another hint of progress is in the Google announcement yesterday about their efforts to cooperate with publishers on more flexible and simple subscription models. The Times quotes Google as moving from "one-size-fits-all" models, and as "looking at ways to help people subscribe to publications more easily, including using machine learning to help publishers tailor options to a reader’s preferences and behavior." But again, the big question is whether this gets applied with a publisher-first mind-set, or the customer-value-first mind-set that is really needed.

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