The corporate name change of Facebook to ‘Meta’ is a refreshingly honest approach to the company’s business model. FB derives billions in revenues by trading free image storage space for invaluable metadata on your friends, your birthday, your location, and (yikes) your browsing histories that allow the delivery of frighteningly targeted advertising. So, their new name hits the nail on the head in describing what they are selling.
Of course, Meta is not the only company to trade a useful service for their users’ metadata. Expensify, for instance, gives away their expense management software in exchange for incredibly hard-to-obtain information on corporate spending patterns and vendors that can be used for hyper-targeted b-to-b advertising.
How many other opportunities are there to trade services, content and/or software for valuable data? Well, any type of online buyer’s guide should work under this model. Instead of enhanced listings and preferred placement a known user’s search data becomes the key part of the business model because it represents a real intent and ability to purchase precisely while the buyer is doing their pre-purchase due diligence. The pricing model is different (e.g., $25/hot lead v. $0.25 for an email of a potential buyer), but the model really is not different at all from one of publishing’s very earliest business models.
Other business model variations involve trading your detailed profile and future purchasing requirements in exchange for better pricing. This VRM (‘vendor relationship management’) approach has been the Holy Grail for online information services (i.e., it’s potentially a bigger market than the CRM market), but only modest attempts have been made so far to tap into this incredibly rich vein of metadata. If VRM ever really happens it could potential ‘unmask’ the budgets and associated vendors for every department in every organization.
So as Facebook comes clean about how it gathers and sells super-targeted _personal_ eyeballs to its advertisers, b-to-b information services should take note about how they too can methodically assemble various pieces of critical intent metadata (directly or indirectly via licenses) and then package and sell that timely “insight” to marketers for top dollar. There are more than a few b-to-b players out there showing that, while the market for b-to-b buyer intent and contact data may not be as monolithic as the consumer data behemoth that is Meta, there is room for dozens of b-to-b data firms to make tens or even hundreds of millions of dollars each and that ain’t “meta” money!
