FairPay: The Future
of a Radical Pricing Process
An adaptive
pricing process
that can change the game in the media/content industry
Richard Reisman,
Teleshuttle Corporation
(June 20, 2010)
The crisis in revenue models
Free? Paid? Ad-supported? Freemium?
Dead? The creative destruction fueled by the
Internet has led to a crisis in revenue models -- but it
offers a radical new way to create a totally new pricing
process that can change the game.
Traditional business models are under increasingly
severe pressure, especially for digital content, with
its near-zero marginal cost, and the growing expectation
of free content. Sellers cannot afford to provide good
content and services free (or with just ads), but
conventional pricing practices just don't work very
well. This has disrupted music,
TV/movies, news, and other content industries, and seriously threatens the
continuing creation of high-quality content.
One form of Internet-driven creative destruction is posited as
inevitable in Chris Anderson’s influential book “Free: The Future of a Radical
Price:” “eventually the force of economic gravity will win,” driving prices
down to zero. Anderson gives an excellent overview of the current crisis in revenue
models, and builds a richly developed case for the power of Free (especially in
the hybrid form of freemium), but I suggest there is better answer to this
crisis.
What is needed in a revenue model
for digital products, is not to choose
the right price (free or not), but to create
a dynamically adaptive pricing process.
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Selectively offer to let the buyer set any price he considers fair after the sale (Pay What
You Want, post-sale ...or, more accurately, Pay What You Think Fair).
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Let
the seller (or a collective of sellers) track that price and use that
information to determine whether to make further offers of that kind to that
buyer in the future.
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Instead of a fixed price, this process generates
a
cooperative and adaptive cycle of offers and pricing actions, each based on
feedback on how fairly the buyer sets his prices.
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Instead of static pay walls and freemium schemes, this process
supports seamless and dynamic hybrid models. Those who pay fairly, rise
above the pay wall -- those who do not, must face it.
Pay What You Want (PWYW),
in its basic form, is a very old pricing scheme, with
obvious consumer appeal, but is hobbled by fundamental limitations -- getting
people to pay fairly. In spite of these limitations,
PWYW has gained attention as a way to monetize digital
content that can be effective in some situations (as
demonstrated by the rock band Radiohead in the example
below). But we can make it much better.
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I suggest that the market can use the power of Internet scale
monitoring and feedback to enable a new feedback process to solve the
previously severe limitations of PWYW.
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Free also has obvious and severe limitations. We all know that
free is rarely really free – there is no free lunch -- somebody pays – or you
get what you pay for.
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Pay What You Want has the obvious advantage that it combines
Pay
with What You Want. Almost as nice as free for consumers, and something
for sellers. The problem, of course, is the free-rider. Some pay a fair price,
some pay very little, and some do not pay at all. It works to a degree, but
not as well as most sellers need.
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But that is true only when buyers can free-ride without
consequences -- now the Internet offers a new way to let sellers adaptively screen
out free riders.
The FairPay solution
Fair Pay What You Want (FPWYW), or
FairPay for short, exploits the power of the Internet.
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FairPay, uses the Internet to monitor what buyers choose to pay,
and to make that history available to the seller. It also uses the Internet to
facilitate setting the price after the sale,
and after initial verification of value.
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The seller considers the buyer’s history of fairness to decide
whether to make future offers to that buyer to sell things on a FairPay basis
-- or to fall back to conventional set pricing.
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The buyer accepts an offer to buy on a FairPay basis with the understanding
that:
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The buyer is not anonymous, and his payment will be reported and
collected into a history, a FairPay reputation for payment fairness,
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FaiPay is a selective privilege. If the buyer is unfair
in what he pays, that feedback will affect his FairPay reputation, limiting
future opportunities to make purchases on a FairPay basis. The seller is
always in control of whether to make new offers on a FairPay basis, under what
circumstances.
FairPay combines free, paid, and freemium, and makes it
dynamically context sensitive. The buyer pays a fair price (which may
include free when that is fair, such as for sampling, or when value is not
received).
Because FairPay works as
a self-limiting privilege, the
buyer has a strong incentive to be fair and responsible about what he decides
to pay. With its feedback-enforced fairness, FairPay drives a positive feedback
cycle that can potentially create a whole new economic world order for major
classes of products and services. FairPay does not just rely on innate buyer
fairness, but looks over their shoulder and provides
real consequences to help give
that sense of fairness powerful weight. What goes around comes around.
PWYW with teeth.
FairPay processes and reputations might be managed
internally to a specific merchant or publisher -- or applied more broadly, managed
and shared among a network of merchants, much like a credit rating. The
more widely it is used and shared, the more effective it
will be.
Some simple examples
Radiohead
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Before: The prominent rock band Radiohead offered their
album “In Rainbows” in 2007 as a digital download, in one of the most noted Pay
What You Want experiments ever. The average price was reported to be $2.26,
but about 60% of downloader’s paid zero -- a very significant free-rider
problem. Those who did pay, paid an average of $8.05 in the US and $4.64
elsewhere. A very mixed bag -- consistent with widespread evidence from
behavioral economics that people generally have an inclination to fairness, but
that relying on that alone is not likely to make for a good business. The
problem is that this is a one shot deal, with only the vaguest hint of any
consequences.
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FairPay: What if the same offer was made by iTunes or
Amazon for five downloads – framed with the suggestion that if the FairPay
price paid was satisfactory, the offer would be extended to five (or ten or
twenty) more downloads? It seems safe to expect that, knowing their price
would have consequences, free riding would drop dramatically. Those who might
not have paid at all (in a Radiohead one-shot deal) would now be much more
likely to pay something. Most of those who did pay something (with no
strings at all) would now be much more likely to consider paying a bit more
generously, knowing that they are being “watched” and hope to be rewarded with
future FairPay offers.
The Wall Street Journal
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Before: WSJ.com has a substantial subscriber bases, at a
very substantial price (about $100 per year) for a large-circulation digital
product. But most Web users do not spring for any access at all – a loss to
them and to the Journal.
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FairPay: How many more people would subscribe at a lower
price (especially those who might use it infrequently, for the occasional
story) and thus get some modest value? How many don’t care about many
subscription features, such as stock quotes and charts? What if the Journal
framed the offer as only for those viewing fewer than 10 articles per month,
and no advanced features? Would they gain more than lose? (See related
newspaper blog post.)
Hulu, YouTube, etc.
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Before: Hulu, the studio-owned video portal, offers
movies and TV on the Internet with an ad supported model, but finds it hard to
get adequate revenue, and was reported to be considering
paid subscriptions (and recently introduced them as its Hulu Plus service). YouTube has a very similar problem, and has been
estimated to be losing nearly half a billion dollars a year (a figure Google said
was too high and dropping, but by how much?).
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FairPay: What if these video services offered subscriptions on a FairPay basis? (Possibly
with an ad-free benefit, or with the option of light ads
versus heavier ads?) Instead of guessing what price the market would bear for
a premium subscription ($9.95/month?), Hulu could let the market tell them what it will pay.
And for those who pay poorly (relative to their usage), Hulu could simply stop
extending that FairPay offer, and simply require the set $9.95.
To look a bit closer at how this might work, consider an
Internet video service, call it HuTube. HuTube might currently offer free
service, supported by advertising, and might have some premium services behind
a pay wall, charging either by download/viewing, or by monthly subscription.
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An experimental program might be offered to a selection of HuTube
users based on FairPay pricing. This might be aimed at heavy users, and offer
access on a subscription basis on the following terms:
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Unlimited premium access is offered on a month-by-month basis
upon subscription.
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The subscriptions might
include options for access to premium content that
might be behind a pay wall (such as recent
theatrical movies and pay TV and network hit
programs, etc.). It might also include
ad-free, or reduced ad service.
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Before the start of the next month, the user decides on a FairPay
price to pay for the current month (with a usage report provided to the user
for reference).
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Depending on the FairPay price set by the user
for the previous month(s), HuTube decides
whether the FairPay subscription offer will or will not be extended for the next month.
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Once tested, this FairPay subscription plan might be enhanced and
offered more broadly, with various levels of service:
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Price setting might gradually be reduced to a yearly cycle for
established subscribers with good FairPay reputations. Usage reports would be
provided to assist in the yearly pricing reviews,
with details of usage by class of service (premium
content, ad-free, etc.).
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Payments might be
monthly (even if price setting is yearly).
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The options offered to
any user on each renewal/pricing cycle would be
adjusted based on their payment history (with
consideration of any relevant circumstances known or
reported). Thus those who pay fairly get
increasing levels of trust and float above the pay
wall, but those who do not get kicked back down into
the pay wall.
The
case for FairPay
For the
buyer, FairPay can have almost all of the appeal of Pay
What You Want, and it adds a new dimension of fairness
that makes it very beneficial to sellers as well. Because FairPay
variations on PWYW set prices after the sale,
the buyer can have the product "on approval," use it, and verify
its value, with no risk. No fear of buyer
remorse, no need to refrain trying something that
might be of uncertain value. The buyer decides
what to pay after seeing the value of the
product or service.
For
the seller, FairPay
feedback enables the seller to limit risk as well. The
buyer develops a FairPay reputation, a known
history of how well he pays for various kinds of
products and services, under varying circumstances.
That gives the seller the control needed to make
FairPay offers only where his expected risk/reward
profile is attractive, and to limit his
value-at-risk. The free-riders are
screened out, and relegated to the traditional world
of set prices (at least to a greater extent than
those who pay more fairly) .
FairPay
creates a win-win dynamic that can make both buyers and
sellers much happier, and the economy much more
productive.
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Sellers can profitably
sell to everyone who sees a potential value, at a
price corresponding to the perceived value to that
individual buyer.
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Some will pay well, some
will not. But sellers can expect that many
more people will buy, and they will pay a fair price
because their reputation is at stake.
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FairPay can take many
forms, and can enable free sampling and blends of
free and paid that are more dynamically adaptive and
effective than ordinary “freemium” models, and that
effectively makes the pay wall dynamically adaptable
and semi-permeable. (More on that below.)
The net
is that total revenue, and total profit, might be
significantly higher than with a fixed price (at least
for products with low marginal cost, as with digital
media) -- and that total value created can be maximized.
In its
fundamental microeconomics, this is truly a radical
pricing process. It enables more flexible revenue
models with a new level of efficiency in pricing.
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FairPay prices serve as
personalized metrics of the “utility” of a purchase
to an individual buyer. They vary from buyer
to buyer just as the value of a product varies from
buyer to buyer. The FP price for an item sold
is just what it is worth to that buyer at that time,
to a good approximation.
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Set prices have the
inherent limitation of one size fits all (not!).
Marketers know all too well the difficulty of
setting prices, the straightjacket of the demand
curve. Price it too high, and few are sold –
many potential buyers will be lost. Price it
too low, and more are sold -- but will they be
enough to maximize profit? Will too much money
be left on the table in either direction?
(Segmentation seeks to reduce these errors, but
segmentation is more static and granular, and is costly
to design and set up.)
Revenue
models become dynamic and "participative pricing" becomes a
truly collaborative process. FairPay prices might not be
ideal on a first cycle, but buyers and sellers will
rapidly converge toward the ideal. Point number
one of The Cluetrain Manifesto was that “markets are
conversations” – FairPay makes pricing much more of a
conversation, and an ongoing conversation, at that.
Based on that conversation, the pay wall is
automatically customized to each buyer, at each stage in
the cycle.
Sure,
many FairPay users will pay less than they might have on
a fixed price basis. But by how much?
And how does that compare to the few that might pay more
than regular price because they get high value? -- and,
more importantly, to the very large number that might
pay something,
instead of paying zero (by not buying at all).
FairPay, freemium, and sampling – from pay wall to
FairPay buffer zone
An important by-product of FairPay is that it enables
unprecedented richness in consumer-controlled sampling.
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At present, vendors give out free samples to attract new
customers, a process that is very costly, blind, and wasteful. Samples often
go to those who would already buy, or to those who would never buy, and miss
many of those who might want a trial.
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Smart vendors can use FairPay to routinely offer reasonable
levels of sampling at no charge, and such sampling can become conventional
practice.
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In such cases, FairPay systems might enable consumers to sample
without ever bothering to even set a price (automatically setting a default
zero price after some pre-set time). So no pricing action is required at all,
as long as the level of sampling is not excessive, after which a polite
reminder could prompt users to pay, explain, or risk negative feedback and loss
of the privilege of free sampling.
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Once again, the seller expands his market, and reaches all
interested buyers, and buyers pay only what they think fair. (Much better than
Free for the seller.)
That brings us back to freemium -- FairPay models can mimic
many aspects of freemium, but FairPay sampling has significant advantages over
freemium.
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Freemium models
offer fixed boundaries
of free access to some levels or types of access, with greater levels or types
of access behind a rigid pay wall, requiring a set-price payment. Freemium
models work by redistributing costs, so that paying customers subsidize free
customers, but does so in ways that are rigid, granular and hard to tune.
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FairPay processes turn a pay
wall
into a FairPay Zone, a buffer zone in which prices are set after
use, and feedback is used in an ongoing process that might be far more
effective, flexible, fine-grained, and self-adjusting than conventional
freemium models. Instead of setting a pay wall as a fixed, bright-line between
free and paid, the FairPay buffer zone can be wide and richly contoured. It
can contain much of the relationship with many of the population of buyers.
The pay wall remains, but with a reduced role -- primarily to manage buyers with
no reputation or a poor reputation, and for high value items for which FairPay
might be too risky. (See
FairPay Conceptual Diagram.)
The “Long
Tail” of Pricing
I think Chris Anderson might agree that there is another “long
tail” in play here -- a long tail of pricing. Anderson’s long tail (in
his previous book, “The Long Tail”) is a tail of items ranked by units sold. The
long tail of pricing is a tail of buyers ordered by price paid. This long tail
of buyers might turn out to contribute a very large portion of total revenue.
Large numbers of buyers at low prices, who would not otherwise be buyers, can
add up to a very large revenue figure. Sellers might find that revenue from their
current market drops a bit, but the new revenue from their previously non-addressable
market can become a very large number.
FairPay exploits the new capability offered by the Internet
to collect Fair Pay pricing data, to analyze it and to apply it on a large-scale
basis, with ubiquity, immediacy, ease, and economy. A FairPay market platform
can manage the feedback process of making and accepting offers, tracking the
setting of prices after the products or services are delivered, maintaining a
database of that data, and making that data available for analysis by sellers to
determine whether and when to extend FairPay offers. FairPay offer processes
can build on existing market segmentation strategies (which seek to tailor
product features and pricing to different customer segments having
different needs), and enhance them to more
accurately address true feature/price sensitivities for “segments of one.” (See blog post on
The Long Tail of Prices.)
All-you-can-eat, meters, and FairPay
An
example of how FairPay pricing cuts through the
artificial confines of conventional pricing is how it
helps to finesse the classic dilemma of flat-rate versus
usage-based pricing.
Flat-rate
or all-you-can-eat models are increasingly dominant for
many kinds of services, especially in the digital world.
Plans for long-distance phone service, Internet service, content, etc.
have increasingly moved from pricing per unit of usage
(minutes, bytes, articles, etc.) to plans that permit
unlimited usage (per month). Even music shows some signs
of moving from per song and per album "ownership" models
to unlimited music per month models (as in Pandora and
Rhapsody).
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Consumers seem to prefer flat-rate plans because
there is no meter ticking to make them worry about
paying for one more unit, or being surprised by a
large bill.
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However sellers, and some users recognize there is
an economic flaw, in that heavy users and light
users both pay the same. This can be a severe
problem for sellers (such as Internet providers who
must bear the heavy uploads of users of peer-to-peer
file-sharing services like Napster or BitTorrent,
and AT&T's recent move away from unlimited mobile
Internet service).
It can also be a problem for light users, such as
those who would like an occasional Wall Street
Journal article, or occasional mobile Internet
service. Whatever level the flat rate is set
at, one size does a poor job of fitting all users.
All-you-can-eat has consumer appeal, but often leads
to flawed incentive structures that are costly and
wasteful.
FairPay
avoids this dilemma by enabling prices to be based on
perceived value. It lets users consider their
usage level as one factor of many that contribute to
value. They can factor in usage levels (and apply
reasonable volume discounts), but need not be slave to
that. Single ticks of the meter do not necessarily
raise the price. One would expect many clicks to
justify a higher price, but some clicks may be judged as
more or less relevant than others. A user who
glances at many articles for a short time might be
justified in paying less than one who studies a few
articles for a long time. The user's will know
what they did, and usage reports can make that visible
to both buyer and seller. Once again, rigid
pricing rules give way to nuanced estimations of value.
Proponents of new freemium models for newspapers (such
as the New York Times or Journalism Online) speak of
"dialing" different price settings to meet market needs
by changing the number of free articles before requiring
users to pay for an unlimited subscription access.
I submit that it still a one-size-fits-all solution to a
problem that needs more nuance. FairPay enables a
far more nuanced way of "dialing" market behavior
by giving users the pricing dial, but letting sellers
control the renewal dial.
Why
pay more than the bare minimum? -- Win-win markets
Of course
there will be many factors in play that determine
whether buyers do, in aggregate, pay at a "fair" rate
for any given seller and product. Why should
buyers pay more than the absolute minimum they can?
I suggest the answers will vary, but in general,
behavior can be pushed to desirable levels by sellers
that manage their customer relationship well.
This gets
to fundamental questions of how businesses relate to
their customers, and whether they can change the
"conversation" from a zero-sum game of which party can
get the most from the other and give the least, to a
win-win game, where both parties seek a mutually
beneficial value exchange. Society seems to be
broadly seeking a more win-win kind of market, and that
is just what FairPay is all about.
Related
to the ideas in The Cluetrain Manifesto of markets as
"conversations," Dan Pink's book "Drive" summarizes how
there are different mind-sets to motivation, and current
trends are pushing toward more win-win behaviors, building on on three elements: autonomy,
mastery, and purpose. I suggest that FairPay helps
change marketplace dialog to exploit exactly those
elements, by giving buyers much more autonomy,
opportunities to develop mastery, and ability to reflect
their purpose into their pricing decisions.
Sellers who position themselves as partners in value
exchange, frame their FairPay offers thoughtfully, and
work with their customers as partners seeking mutual
benefit, will succeed in getting them to pay fairly.
Those who do not may find it difficult.
One
aspect of this is how well the seller can position the
price paid as being a well-deserved compensation for
value creation, and necessary to ensure a continuing
supply of value. This obviously factors into the
modest success of musicians and game developers with
conventional PWYW sales (why did so many pay more than
one cent?). Such positioning is relatively easy
for sellers who can claim that most of the price goes to
compensation to artists, journalists, or other human
contributors. It is also likely to benefit
companies that, like Apple, are perceived as being
focused on consumer value, or on other kinds of social
benefit, such as green, charitable, etc. (The addition
of charitable elements has been shown is some recent
research on PWYW to very effective in discouraging
free-riding.) Favorable positioning may be more
of a challenge for companies that are perceived
negatively, or simply as commodity suppliers, especially
if not compensated by superior service or other
positives.
A further
method for encouraging good payment levels would be for
a seller to make it known that perks are offered to
those who do pay well. This could be similar to
the perks in frequent flyer programs that provide
upgrades, visible recognition and status, and other
special privileges. Such methods might even include
making some aspects of good payment behavior visible as
a status symbol (possibly only for those buyers who seek
that kind of "conspicuous FairPayment").
Also,
a good FairPay reputation might depend not only on how
well you pay, but on how well you explain why you pay
especially well or poorly in specific cases, thus giving
the seller valuable feedback not just on pricing, but on
the merits of their product. Buyers might be given
visible recognition for such thoughtful feedback (such
as badges) naming them as elite partners, a form of
status reward (like top ranked reviewers on Amazon) that
consumers might seek to earn and display with no fear of
being seen as crass.
Another
factor that can strengthen the effectiveness of FairPay,
as it develops, would be the emergence of shared FairPay
infrastructures among multiple vendors that enable
cross-vendor collection and sharing of reputation data.
As discussed further below, this infrastructure might
behave much like cross-vendor credit reporting and
rating services. Just as with credit reports,
consumers will be more inclined to behave well to avoid
harming a FairPay pricing reputation that many vendors
rely on.
Making FairPay work
Radical change takes effort and education at many levels,
and that will clearly be required to make FairPay pricing processes work. As
just touched on, much of this relates to basic
principles of customer relations.
A first critical success factor is to educate buyers and
sellers in how FairPay transactions can work and why they are desirable. FairPay
turns many traditional ideas about pricing upside down, and shifts considerable
responsibility to the buyer. Sellers will need to provide buyers with clear
explanation of the basic process, and how and why their pricing should be
fair. (See
Sample FairPay Offer.) Sellers will need to carefully frame their specific FairPay offers to
set expectations on value and responsibilities, to define relevant usage metrics, and
to facilitate buyer pricing decisions. Rich data on how buyers use products
and services, and analytic tools for understanding that usage will be important
in buyer pricing, and in seller evaluation of that pricing. Implementing FairPay pricing processes within a business will change fundamental business
processes. But if FairPay can make a material difference in business success,
all of this is a hurdle that can be overcome. And some sellers are well
positioned to do what it takes now.
A second critical success factor is that a FairPay system must
be very painless to use.
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Anderson speaks of a “penny gap:” the problem that thinking about
paying even one cent creates a psychological barrier to a sale. As he
explains, this is a key reason why micropayments have failed to be the
salvation of digital business – they are just too much psychic friction.
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What this means for FairPay is that payment decisions for small
purchases are most efficient when aggregated. FairPay will generally not work
as well if
buyers must think about pricing a single Web page or song or video clip. But it
can work well for a subscription or other bulk purchase. This is how most
people pay now for mobile phones and cable TV – not per item, but per month,
for some large basket of items. As in our HuTube example, similar FairPay
subscriptions could be paid monthly, and for consumers who have established
good FairPay reputations, price setting might be done only annually.
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The better your FairPay reputation, the more freedom you will
have to buy a large number of items on “approval”, and then review a usage
“statement” and settle up infrequently, with relatively low burden (much like
having a high credit limit and extended payment terms on a credit card).
A related
implementation issue on the seller side is to ensure
that the process is not gamed by users who use false IDs
to reenter a FairPay zone under a new name, after being
cut off for unfair payment behavior under another name.
This can be reduced to tolerable levels by using various
ID mechanisms, and by limiting the value-at-risk
outstanding at a given time for any buyer who lacks a
well-established positive reputation. As with all
reputation systems, new participants are most safely
treated as having low reputation until they demonstrate
otherwise (and once established, good reputations are
not lightly sacrificed). The ID problem is much
the same as for conventional pricing systems that allow
some free usage (such as a small number of newspaper
articles), then charge for more. Expanding on some
of these points:
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IP
addresses can be moderately good identifiers, and
can be checked with no burden to buyers.
(Services can be used to inexpensively detect and
reject anonymous addresses obtained through
proxies.)
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Credit cards are widely used to verify identity
(including name and address), without making any
charge, and this adds only a modest hurdle to
buyers.
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To
manage identity risk, a seller might typically limit
users who have yet to establish good FairPay
reputations to low value offers. These might
be for small numbers of items, and only for low
value item types, and then, as good experience is
gained, gradually extended to offer more FairPay
"credit" covering larger quantities and more premium
item types, as noted just above.
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Other
fraud protection methods used in e-commerce can also
be applied.
A third critical success factor to resolve is privacy
concerns and information quality concerns. Obviously detailed data about what
a person buys and what they choose to pay can be sensitive information. To the
extent that uses of FairPay are applied within a given business, such as
iTunes, Amazon, YouTube, etc., that is not much of a problem. Such sellers
already have detailed sales histories that they take great care to keep
confidential and adding FairPay price data to that adds little in the way of
new concerns.
FairPay could be important even if it were limited to use
within trusted, self-contained sellers. But the economic potential is even
greater if FairPay processes and reputations are applied across sellers, and to
smaller sellers for whom a shared infrastructure would be most economical.
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FairPay information is not unlike credit report information which
has similar privacy and data quality issues, and widely accepted methods for
managing those issues (including for disputing/correcting erroneous reports).
Similarly, purchase histories are known to credit card companies.
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Conventions can be developed as to who has access to what pools
of data.
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For example, vendors like Amazon could provide Web services that
support their affiliated merchants in making merchandising decisions without
ever revealing the details of a buyer’s FairPay history or what specific
products they bought.
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Other third-party FairPay merchant services (such as credit card
companies, PayPal, Google Payments) could collect FairPay data and provide
merchandising services to a network of merchants without disclosing the
details.
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Such services might simply make a recommendation as to whether
and how to make an offer, based on inputs from the seller, without disclosing
any of the data used to do so, not even any reputation metric (other than the
contextual recommendation to offer or not).
In managing privacy, remember also that
FairPay data
collection is inherently opt-in – you can avoid any FairPay data collection
about a product simply by avoiding a FairPay transaction. If you don’t want
any given product and price tracked, just don’t buy that product on a FairPay
basis. Use it only in situations where the benefits outweigh the concerns.
Like any new system in a complex environment, effective use
of FairPay will take some ingenuity, and practices can be expected to evolve
with use. But there is no reason to think such usability and appeal issues
cannot be solved effectively. Obviously, rich and robust implementation of
FairPair services is not a trivial task, and that suggests that there will be
economies of scale in developing such services. But there is no reason to
think such services cannot be made available to small merchants and even
individual sellers, much as is done by Amazon, eBay, Paypal, and other such
services. Perhaps we need to think of it as “Pricing as a Service.”
In
addition to the operational value and economy of scale
of cross-vendor FairPay services, the power of the
FairPay reputation feedback cycle will also be increased
by cross-vendor sharing of reputation data. Smaller
vendors will gain critical mass, larger vendors will
have more complete data, and, as noted above, buyers
will know that stiffing one vendor will affect their
reputation, as seen by other vendors.
As to how far through our economy this method can go, that
remains to be seen. FairPay will generally not totally replace conventional
pricing, but can grow into an increasingly important
complement to conventional pricing methods.
-
A sweet spot for initial use, and the area of most urgent need,
is clearly in digital products and services. Particularly good candidates for
FairPay may include:
-
services that are
currently free, but where the seller feels urgent
need to begin charging (such as newspapers and many
video services), or
-
services that are so
pressured for revenue that conventional PWYW is a
serious consideration, in spite of its poor
performance (such as for music and video games), or
-
services that now charge
a high rate, and seek to broaden their market with a
more limited FairPay option for low-end market
segments.
-
FairPay it is also applicable to physical products and services,
as well, especially for those with low marginal cost (such as CDs/DVDs), or with low cost tie-ins
(such as product service and support, and other product related services).
Why not?
This “modest proposal” for Fair Pay What You Want is obviously
radical, and may at first seem naïve and impractical. But I suggest the
impediments can be overcome, and the potential benefits to some businesses, and
to society, can be huge. If you agree, I ask your support to help take the
digital economy to a new level. If you disagree, I would be interested to understand
exactly why. I invite feedback directly, and on my FairPay blog.
June 20, 2010
(revised
8/13/10)
The
FairPay Manifesto (version 0):
-
Markets want to be smart and finely adapted to incentives.
-
The Internet wants to be smart and adaptive.
-
The Internet enables direct feedback that is immensely rich
and timely.
-
Direct feedback is the most powerful way to tune incentives.
-
Free is inherently dumb, because it obscures market incentives.
-
Set prices do not reflect value-as-realized
(by individual buyers).
-
Prices should correspond to value-as-realized.
-
Buyers, not sellers perceive value-as-realized.
-
Sellers should measure and manage buyer perception of
value-as-realized.
-
Maximize buyer perception of value-as-realized and a fair
price will follow.
-
A good pricing process is a conversation.
-
The way to do pricing is to be a pricing process.
________________________________
Richard Reisman is president of Teleshuttle Corporation.
He invites feedback on the FairPay concept, and seeks to work with strategic
partners for the development of FairPay commerce. Reisman has been involved
with digital media since its infancy, in a variety of technology and business
roles, including as consultant, manager, entrepreneur, and inventor (with more
than a dozen patents and a couple dozen more pending). Reisman can be reached
at fairpay@teleshuttle.com. More
on FairPay is
http://teleshuttle.com/FairPay, and on his
FairPay
Zone blog at
fairpayzone.com.
Reader feedback on
FairPay is important to developing this radical concept
-- if you don't want to send an email, please fill out our
anonymous
FairPay concept survey at
http://www.surveymonkey.com/s/J6KMP5Q.