I’ve been pondering the following quote from David Friedberg, founder and former CEO of Climate Corporation: “Our strategy is to make the probabilistic deterministic wherever possible, and reduce the error in what remains probabilistic.” Climate Corp is a crop analytics company Monsanto purchased in 2013 for almost a billion dollars and a multiple of revenues. They have the wonderful tag line “If your fields could talk, what would they say?”
In the digital age, our cell phones, intelligent voice agents, robots, self-driving cars, satellites, sensors, the Internet of Things, and so on, paint and capture a vast universe of data, effectively creating a digital twin of everything. Given this torrent of available digital description, every business should strive to model the future, or in David’s words “make the probabilistic deterministic wherever possible.” Because if you can model the future better than the next guy and can reduce the error on the “predictions,” you win. (See an interesting article on the Magic of Predicting Demand from Data.)
How can you do that? One approach is to redesign your business model to become a “subscription business.” Dollar Shave Club was purchased for over a billion dollars by Unilever even though it had only about $165 million in prospective revenue. Why would Unilever pay so much? Because DSC had turned shaving and its accessories into a subscription business, which then enabled it to know more about each and every customer, including address, buying history, and payment history. DSC has far more customer information than Gillette, a company that has been in business since 1901, despite offering a simple product. A more sophisticated subscription could develop a model of customer behavior, likes, dislikes, household, etc.
Every business-to-consumer company has the potential to disrupt or be disrupted by a subscription model. Many businesses under threat by Amazon are vulnerable because Amazon knows more about their end customer than they do. Think about the difference between the Bose radio in my kitchen and my Amazon Echo. The Bose knows nothing about me. It does not know where it is; what I listen to; when I get up; what I like, etc. The Echo, in contrast, knows many of my consumption patterns—such as when I use it and what for—and gives me access to all the services that reside on top of that platform. Great sound quality is only one dimension of my relationship with the device. Bose should be worried.
These dynamics are not only in play in the business to consumer world. I believe in this decade business to business companies will amass similar intelligence on their clients as their B2C counterparts have on consumers. A global, complex, services company probably only needs to know about 10 million people worldwide to develop compelling customized communications to each and every one of them about their firms and markets. Those 10 million people would include customers, potential customers, regulators, government employees, etc. Acknowledging that the data on these people changes (probably by 10 percent to 15 percent per year) and the people move in and out of the population (by about 5 percent to 10 percent), a modern B2B marketing organization needs to be able to manage a continuous database of information on those 10 million by centralizing all the relevant information inside the firm (what I call an inside out process) and capturing data on folks from the “outside in.” Ten million people seems like a lot, and a number that large would be relevant for only a large complex firm. For other markets, such as high-end personal banking, the number could be much smaller, and practical to manage. Even politicians do it, often profiling many if not all voters, totaling in the millions.
Established businesses need to take this seriously now if they are to protect their status as market leaders, because already there are challengers circling. A firm in Silicon Valley called Accompany (www.accompany.com) has a database of over 300 million entities, which it updates with about 500,000 new ones per day. Amy Chang and Matthias Ruhl started Accompany about three years ago and built the algorithms which gather and codify any person or company’s digital exhaust into a useable database. I’ve been using it to prepare for meetings and it is so useful. It helps me get the latest and greatest information, relationships, twitter feed, article citations, you name it, for people I’m working with and/or meeting. It is not perfect, but it is super good and getting better all the time. A tool like Accompany, or LinkedIn, could provide a backbone for a population description of any B2B’s audience. Those who move first will have a deeper relationship with these suppliers and create the organizational capabilities to turn data into dollars.
Now is the time to build a model of your market and start managing to a population – just like subscription business do.