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.)
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).
