Data Monetization: A How NOT To
The Ghost of a Christmas Present
This year I received a Christmas present. The initial excitement quickly waned after the unboxing due to a sudden recognition that the appliance was merely exploitation disguised as innovation. My frustration and dissatisfaction with the device resulted in a speedy return of the gift but the lessons learned from the brief exchange have lingered.
In order to use the device, I had to download the manufacturer’s app to my phone. The app required a Bluetooth connection from the phone to configure the device and the device required a Wi-Fi connection to the Internet to download content. Over-engineered perhaps but I was still excited and onboard until I tried to use it. Once it was connected, updated, configured and launched it offered a “free” trial of its service for a limited time. That’s right. The gift solicited a subscription.
Quickly, I weighed the balance of benefits afforded by a fully functional product and the device’s utility sans subscription. While I understand the subscription model may be appropriate for a cell phone or a streaming service, I was immediately surprised and disappointed given the intended utility of this particular device. This struck me as being no different than an internet-connected spoon. The calculus of pros and cons was shortened, however, when I discovered that all of the “good” features of the device depended upon the subscription. My initial excitement quickly modulated to energized disgust as I realized the con: exploit me for data or deny the usability expected from the device.
Hard Times Call for Innovation
In Doug Laney’s book, “Infonomics” he interviews Graham Waller who provides a terrific illustration of effective data monetization through the story of how a manufacturer’s innovation of a connected tennis racket produced a win-win-win-win outcome through competent data strategy. The connected racket allows players to improve their game through analytics. The manufacturer augments their game through improved customer relations, satisfaction and sales. Their partners improve their games through the manufacturer’s shared insights. And the tennis playing population ups their game through improved competition and engagement improving the popularity and state of the sport. Everybody wins through innovation that garners adoption.
A Tale of Two Companies
In both of these examples, the device requires an app to receive the data, connectivity to deliver the data, and an account for the user to review the data. Both offer the potential to improve an individual’s quality of life while partnering with others to improve the industry at large. And while both appeared to offer innovation it is the tennis racket that illustrated improved adoption. I can still use the racket to play tennis even if I never connect it. The utility of the device is not denied for lack of data. Yes, my personal gains are not optimized if I fail to avail myself to the racket’s full functionality but that’s on me and I can choose to accept that loss. I made the decision, not the manufacturer.
In the case of the tennis racket, innovation leads to adoption because the customer enjoys a sense of value from engagement with the product. In the case of my Christmas present, a sense of exploitation permeated the experience and resulted in reverse adoption.
Customer delight results in brand fondness. Attempts to collect data for data’s sake come across as faux and insincere when they lack a sense of value and utility to the customer.
To illustrate my observation, I offer this simple graphic. The plotting of Device Utility vs. Data Obligation reveals zones of Adoption, Engagement and Exploitation. The spoon represents a high level of utility with zero cost of user data. The tennis racket described above offers value through high utility that exceeds a calculus of data obligation. Like the spoon, the tennis racket still provides utility even in the absence of data and so long as it is regarded as useful it will continue to garner adoption. The addition of data improves the product’s potential for increased engagement with the customer or other data partners. But in the case where a threshold of Minimum Utility is not met the product will not be successful resulting in low adoption and low engagement. This is the zone of Exploitation… the place where my blush of consumer excitement went to die.