“Risk-Free” Subscriptions to The Celestial Jukebox? (A Working Draft)

[Republished from my blog, The Fair Pay Zone. The version there has updates.]

They promised us an “Infinite Jukebox” — but we never expected the price to be infinite

The early days of the Internet promised an “infinite,” “celestial jukebox,” with instant access to all the content in the world. But instead of heaven, we are now facing “subscription hell.” Yes, we can now enjoy nearly infinite access — but the price also seems to be approaching the infinite. What we have here is not a failure of technology but a failure of business model innovation.

The future of subscriptions is to make them risk-free to the consumer. For digital services, the provider risks little except the opportunity to take money in exchange for no value. That will be less and less tolerated.

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Your thoughts? This is still in formative stages, and feedback is invited.*
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One issue is that subscriptions are all about relationships, and that is more true than ever in our digital world. Our current relationships are dysfunctional because businesses make consumers take on pricing risk for no good reason. Consumers see the risks they face, realize that makes little sense for digital services, dislike that, and dislike businesses for demanding that. The compounding issue is that the inherent abundance of replicating digital services makes consumers even less willing to accept pricing risk.

Providers seem to think current models are the only way to do business — if they think about it at all. (Some prefer not to think about it, and love the value proposition of “autopay forever,” hoping you forget that they are sucking money out of your wallet every month.) Even those with better intent and more desire to innovate are stuck in the scarcity-based economic mind-set of real goods, and have not really understood the value-creation power of the new economics of abundant digital services. We are still mired in your father’s subscription models — models for mailing pre-defined assemblages of print and squeezing pre-defined sets of TV channels into an analog cable:

• Business know that consumers like simplicity.
• They also know that consumers hate surprises.
• So subscriptions are made simple: unlimited, flat-rate, all you can eat (AYCE).
• But AYCE distorts incentives — it overcharges light users and undercharges heavy users. It limits risk at the high end, but not at the low end or the middle.

Businesses know there are problems here.

• They have difficulty acquiring customers, and so offer introductory discounts (jam yesterday)
• They have difficulty retaining customers, and so offer retention discounts, but only after you try to cancel (jam tomorrow)
• But there is rarely any discount in normal times (never jam today).

Seeing the problems with AYCE subscriptions, some turn to another unrealized dream of the Internet — like an old style jukebox, our infinite jukebox should take nickels — so-called “micropayments.”

• But micropayments just change the pattern of risk: how many nickels will I need?
• This reduces risk at the low end, but not at the mid end — and dramatically raises risk at the high end.

We have limited forms of micropayments for decades, in the form of pay per item (PPI) or pay per view (PPV). But, run up enough micropayments and those digital microbucks add up to real kilobucks. That is a fatal problem, even if we can make taking the micropayments totally frictionless. (Many grasp at new hope from cryptocurrencies and blockchains, but, much as they may reduce friction, they do not solve the problem of risk.)

The problem remains: consumers hate risk! Both classes of current models force significant and unnecessary pricing risk onto the consumer. We can easily do much better, for most kinds of subscriptions to digital content or services.

What is a risk-free subscription?

Here is the basic idea of a “risk-free” (or “no-risk”) subscription. (Compare it to a conventional unlimited subscription that costs, say, $5/month.)

Let’s design a risk-free subscription that costs $0 to $7 per month depending on how much you use. Let’s design a volume discount that varies — to work much like micropayments for low usage — and much like an unlimited subscription at high usage — with graceful blending in the middle.

• Get “run of the house” access to whatever items you want
• If your usage for the month is zero, your bill is $0
• As your usage for the month grows, your bill grows, but with declining cost per item. Your bill will go from $0 to $7, depending on how many items (and how many of them are premium items).
• To avoid the risk of bill-shock when you used more than you intended, you never have to pay more than $7.

This is a simplistic example, and the price ($7 versus $5) for this added flexibility may actually be reduced over time. If many more people subscribe (because they have lower risk), total revenues will grow and the ARPU (Average Revenue Per User) target can be reduced (to attract still more subs), so the unlimited cap might shift to $5, or even lower.

We can improve on this (as explained further below):

• add nuance to our usage metrics to move us closer to a value-based metric that understands that some clicks are more valuable than others
• layer on options to more fully support the ongoing investment of publishers and creators.

(This risk-free subscription is a generalization of a model I first suggested in 2015 — “Post-Bundling — Packaging Better TV/Video Value Propositions with 20–20 Hindsight” — and have since discussed with major TV providers. That provides added detail on the use-case for TV/video bundles.)

Of course this is not absolutely risk-free, but it is much closer — and yes, there are some levels of risk to the provider — both of which are discussed below. But first, a closer look at consumer risk.

Consumer risk in an unlimited subscription

Think about the consumer’s issues when they decide whether to subscribe, …as they continue, and …if they consider cancelling:

• Will I use enough to justify the monthly price — now, in the past, and going forward? Am I using the service often enough?
  Am I happy with my interest level in the selections offered?
  Am I satisfied with the quality of the items I consume?
  Do I just skim many items, or quit part way through?
  Do I get the desired value (or enjoyment) from the items?
• Which premium channels should I buy access to?
  How would I know in advance?
  Did I watch enough items on the premium channels I chose and paid extra for?
  Was I happy with the premium channel items that I did consume?
  Did I regret that I could not watch programs on premium channels I did not subscribe to?
• Is this subscription one that deserves to be in the “portfolio” of sources I pay for unlimited access to (given all the content sources of this kind that I want)?
  Did I find this month that I wanted other services I did not subscribe to?
  Can I afford to add still more subscriptions?
  Is this a subscription I should drop, so I can afford something else?
• How can I predict any of this reliably?
  Do I know what will be offered in coming months?
  Do I know what alternatives will draw my attention elsewhere?
  Will I be paying for periods where I am on vacation or too busy?

The problem is that most digital consumer services offer constantly changing collections of experience goods. Especially for content services, we have only limited ability to predict what value will be offered, what items we will actually choose, and what value we will realize. That is highly unpredictable, except in hindsight.

Subscription providers seem to ignore this. They focus on customer acquisition and customer retention (and its converse, churn), but how many of them consider the dynamic value propositions of value/risk to each individual consumer? They optimize for CLV, the Customer Lifetime Value to them, but not for VLV, their Vendor Lifetime Value to the customer. How many businesses really think about how they justify their share of the consumer’s wallet?

As more and more content of all kinds goes behind flat-rate subscription paywalls, how many subscription are simply unaffordable to many consumers who might gladly pay a profitable amount for occasional access? How many services offer discounts only for new customers, or those threatening to cancel? What about those who would be continuing customers at modest but still profitable levels? A few top publications like the New York Times are making money with subscriptions paywalls — but only about 3% of their readers subscribe! — and most news publishers do much worse. What a waste to both consumers and businesses! Surely we can do better!

The game most subscription providers play now, is one that charges at flat rates that work for their best customers, but that leave more moderate customers on the ragged edge of saying no. And the vast majority of those who might pay for moderate amounts of content do not subscribe at all. Some providers are even more cynical and customer-hostile, hoping you will take a trial and forget you are paying $5 a month, and then making you jump through hoops when you realize you no longer want to.

Consumer risk in micropayments (pay per item)

Why do consumers hate micropayments? — even if they are frictionless? Because consumers hate unpleasant surprises.

• What if I run up a huge bill?
  What if I get hooked on a binge?
  What if my kid goes overboard?
• Will I be sorry I paid per item instead of getting an unlimited subscription?
• What if I select items but find them disappointing?
• What if I like to skim, and so access many items but get little value from each?

These problems are inherent in micropayment models that do not have significant volume discounts or other value-adjustment provisions. Pay per view movies have a profitable niche, but viewing more than a few gets very costly. News services like Blendle have been even less successful — they offer single articles, but at 25–49 cents each, the bill rises quickly.

The psychological distress of the ticking meter has been well established. Think of telephone minutes, cellular data megabytes, and the old days of online minutes on AOL. Knowing the billing clock is ticking makes it very hard to enjoy using a service. We are always worried: “what shock will I face when I see the bill?”

20/20 hindsight and post-pricing

My work on FairPay highlights the difficulty of setting prices before the experience, why that is an issue of risk, and how “post-pricing” can avoid that problem. The value of experience goods is best known with 20/20 hindsight. Consumers are much happier paying for the value they get after they know what the value actually is. The classic Our Gang “Pay as You Exit” story illustrates the power of that.

Provider risk and profit

Back to my opening statement, “the provider risks little except the opportunity to take money in exchange for no value.” Providers will, of course be quick to argue that they do face risk, but to what extent? Since the unit costs of access to existing content and most other digital services is negligible, the risks are not the marginal costs of service, but the usual subscription issues that drive CLV — CAC (customer acquisition cost) and retention/churn — and the risk of just not having enough subscribers.

The deeper provider risk issue relates to the predictability of cash-flow — whether they can expect to fund their content creation and marketing expenditures going forward.

• Compared to micropayment/PPI models which are already totally dependent on usage, the risk-free model should not worsen predictability — and might improve repeat activity enough to make predictability much better. Many businesses are hit-based, and deal with it, and all but the smallest publishers can spread that risk.
• Compared to flat-rate subscriptions, the obvious concern is that the steady stream of monthly payments from each customer might become much less steady. However, the law of large numbers (many customers) will tend to smooth that in aggregate. Also, if the risk-free offering is designed well, there is reason to expect that reduced CAC and churn will dramatically increase the number of subscribers, so that overall revenue and net profit will be much higher, even if it is more variable.

Cynical providers be very reluctant to shift from the “get them on autopay and hope they never think about it again” gravy train — but isn’t that really very thin gruel?

Tuning the model

That is the basic idea, and the core of the case for it. It will take good design, testing, and refinement to prove it out and get it to work well. That can start with limited, low-risk tests. There is reason to expect that to validate some promising sectors and customer segments, so it can grow from there.

The rest of this draft explores some ideas on how to build on this strategy, by further reducing consumer risk and adding more value-based metrics of usage — and by keeping the impact on provider risk manageable. Value-based pricing is increasingly viewed as best-practice in B2B — we need to be more creative about applying that for B2C.

The discount curve

A key feature of the risk-free subscription is that it depends on usage, but adds a volume discount. Designing the discount curve that gets built into the price schedule will be critical to making it behave in a way that can make consumers comfortable. Consumers want simplicity, so the trick may be not to expect consumers to look closely to understand whatever tiered or continuous schedule of rates is used, but to simply give some examples of what to expect at representative usage levels. As long as customers have a sense that the curve is reasonable, and that they can see their detailed accounting for any month if they want to, that may be enough — as long as the cap on total rate is not too high, and they don’t reach it too quickly. (Of course one or more levels of premium pricing might be reflected in this schedule as well.

Extension: The money-back guaranty, and the skim discount

One thing Blendle, the news micropayment aggregator, did well was to offer an unconditional refund button on each article viewed. That is a good start, but too all-or-nothing. It may be much better to let users specify a percentage refund they want, so that they can ask for a partial “satisfaction discount” when they are disappointed, without shying away because they feel a full refund would be unfair if they did get some value.

Related, is the skim discount. Instrumentation increasingly makes it practical to determine the time spent consuming items, and what portions are consumed — why not discount the unit price if the time spent is clearly short, or the item is clearly not finished? This kind of tracking also makes it possible to confirm that subscribers are being honest about claims of dissatisfaction, and limiting refund privileges for those who go overboard.

Extension: value-based usage metrics

Advertising-based revenue models lead to click-bait, and there are valid concerns that usage-based revenue models can create the same kind of harmful incentives. A simplistic usage metric such as number of items accessed, may well create similarly misaligned incentives for quantity without quality. But extensions like the satisfaction discounts and skim discounts above, will shift this from a simple count, toward a more nuanced value-based metric.

Further extensions can add more sophisticated value metrics (and the bonuses of the next section) to make this model more reflective of the true value of the experience to the consumer. Such metrics may factor in time spent with an item (dwell time), how full a portion of it is consumed (aborts and sampling), is it re-accessed, does it lead to further actions (outcomes), is it shared, etc. Of course most users will not want to dig into this complexity, but a simple “relative value/intensity of use” metric for each item could be reduced to an average and included in their statement. That is likely to be accepted as long as it seems reasonable.

Extension: A publisher-sustaining bonus, and a creator-sustaining bonus

The real challenge in sustaining digital services, especially content services, is that we are only beginning to realize that we must have a new social contract. We must pay to sustain the supply of future content, which is costly, not to access current content, which costs almost nothing. A risk-free subscription can make this transparent and discretionary:

• At the end of the period (along with the statement that reports on usage, and what the “risk-free” price came to), invite a voluntary bonus to sustain the publisher.
• Remind the subscriber what they accessed and what they apparently got the most value from.
• Invite them to add a bonus payment, to reward the publisher, to better enable them to continue to supply more like that.
• Also, invite them to make this a recurring bonus (that can be cancelled at any time), so the publisher has more certainty of continuing revenue.

This can work for single publisher subscriptions, and for aggregations. Aggregators can suggest that bonuses be contributed for each publisher the consumer patronizes heavily (as well as a bonus for their own curation services).

A similar bonus can be offered to reward and sustain creators/artists — the authors, musicians, filmmakers, gamemakers, or podcasters that each customer patronizes most heavily. Report the top candidates each month, and encourage a voluntary sustaining-bonus contribution that goes directly to them — one-time or continuing. This might substantially increase consumer willingness to pay, and might generate significant benefits down the value chain, to enable digital services to create value far more sustainably.

This would work as a new kind of hybrid model, adding a component much like recurring crowdfunding (as supported by Patreon and similar recurring variations of Kickstarter and Indiegogo) into the mainstream of subscription businesses. Of course these bonuses need not be entirely voluntary — there could be some required minimum “sustaining fee” — or some premium-level sweetener could be added that requires a minimum fee.

A low-risk step for publishers in the direction of FairPay

Notice how this risk-free subscription becomes a way to edge toward FairPay while limiting risk to the publisher. The simple no-risk subscription outlined here uses the 20/20 hindsight of post-pricing to largely eliminate the consumer risk in conventional pre-priced subscriptions (and micropayments). It does that in way that keeps the provider in full control of the price schedule. FairPay goes farther to reduce consumer risk, in a more unconventional way, by adding customer participation in setting the price. Powerful as that promises to be, it is understandable that many providers are hesitant to give up that control.

The extension features outlined above gives the customer limited power to effectively adjust the price. They can adjust downward with the guaranty and upward with the bonuses. That moves incrementally toward FairPay, with a basic level of participation in a portion of the pricing.

It may be hard for publishers to make the case that they should be able to “take money in exchange for no value” — but they do have a legitimate case that if they must invest to provide the value that consumers want in the future. A consumer who values the service has some obligation to sustain that investment.

• Think of the base risk-free subscription as the way to maximize market reach, and ensure a base level of compensation commensurate with usage. (A component of price that is controlled by the provider.)
• Think of the sustaining bonus as the way to nudge consumers to sustain the ongoing creation of services they value. (A component of price that is controlled by the customer, within limits set by the provider.)

Think about where to start with this, test it, learn how to manage it, and move toward a solution that serves more consumers and generates more profit for providers.

And, with this kind of win-win model, we can more sensibly sort out a balance between publisher-specific subscriptions and aggregated services (as Apple has given added prominence to) — to find a harmonious mix that is good for consumers, publishers, and aggregated distribution services across a full spectrum of dynamically varying usage levels.

Why not give it a try?

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*Your feedback is invited. Comment here or email me
(FairPay [at] teleshuttle [dot] com).

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More about FairPay

A concise introduction is in Techonomy, “Information Wants to be Free; Consumers May Want to Pay”

For a full introduction see the Overview and the sidebar “How FairPay Works” (just to the right, if reading this at FairPayZone.com). There is also Selected items (including links to videos and decks).

The Journal of Revenue and Pricing Management, “A Novel Architecture to Monetize Digital Offerings” provides a scholarly but readable overview.

Or, read my highly praised book: FairPay: Adaptively Win-Win Customer Relationships.

(FairPay is an open architecture, in the public domain. My work on FairPay is pro-bono. I offer free consultation to those interested in applying FairPay, and welcome questions.)