We’ve been thinking a lot lately about how TI can make money to support infrastructure and future development. We’re still unsure what kind of organisational structure will best serve the goals we’ve got for TI (a conventional startup, a B Corp, a non-profit foundation, or something else?). But we’re increasingly sure that there’s a clear business model to support whatever we come up with, built around selling high-volume access to the data we collect.

In the short term, TI is nicely positioned  at the intersection of social-media analytics (Gnip, Radian6, etc) and scholarly impact (ISI, Scopus, etc). The great things about this confluence from a market perspective are:

• There are a bunch of special academic-specific sources (insulating us from competition from Gnip et al).
• The institutional inertia of big players like the ISI and Scopus makes them unlikely competitors in the short- to medium-term. They see this stuff as toys. Once they don’t, it’ll take time to develop relationships with many providers, relationships we’ve been building for the last year.
• As budgets tighten, there’s a growing clamor for more and better metrics to support  funding applications.  There’s growing dissatisfaction with the IF, but still a culture comfortable with (addicted to?) making decisions based on popularity in social sharing networks (which the literature, at its core, is).

Of course there are challenges here; the IF is a very well-established brand, and citations are the coin of the realm. But there’s also a growing sense that the Web opens exciting possibilities for scholcomm that we scholars are letting slip away.

The scholarly impact market—which ultimately drives the whole scholarly enterprise—is based on 1960s data sources and 1960s technology. It’s ripe for disruption. And selling this new data with a low-risk SaaS model is the perfect way to get that disruption started.

Over the long term, sources like TI can be the infrastructure upon which all of science is built.  Future researchers won’t read journals, but rather customised feeds, filtered using data gleaned from their social networks. As a provider of that data, total-impact sits atop a powerful revenue stream, as well helping to push science into the future.