G2 Crowd’s Chicago Party: A $30 Million Funding and the ‘No Magic’ Man

I stopped by a party Wednesday that is all too uncommon in Chicago: a tech firm celebration. Specifically, I received an invitation from fellow Enterprise Irregular Michael Fauscette to attend a celebration for G2 Crowd’s recently announced $30 million funding round, and I decided to take him up on it.

G2 Crowd is Azul Partner’s (our parent company) downtown Chicago neighbor and one of the few research/analyst/tech shops in the Midwest. (Doculabs, which used to look more like a tech research house, has morphed into a consultancy.) But unlike other tech analyst firms, G2 is taking an approach to tech research centered entirely on crowdsourcing reviews from users — and then analyzing, packaging and publishing the data in various formats.

With Michael Fauscette at G2 Crowd's recent fundraising celebration.

Fauscette joined G2 as chief research officer and has built out a small but sizable team whose job is to analyze and interpret the results of customer reference surveys that are now pouring in (by the minute, from what I heard). It’s a model that is a perfect fit for the millennial generation of enterprise tech buyers, who grew up with peer reviews on Yelp, TripAdvisor and other sites — a group that is unlikely to even know who Ray Wang is (or Bruce Richardson or Andy Kyte, for that matter.) Sorry, guys!

So in 20 years, I have no doubt G2’s model wins (along with others like it) as traditional researchers and analysts like us retire to play golf in Florida (or, in my case, get back to criterium racing, albeit as a geriatric peddler). At the very least, shifting demographics — as millennials rise through the ranks — will cause Spend Matters and others to evolve their approaches to research, at least outside of digital media (Azul’s core business). In fact, we have already.

But the question in the interim is how disruptive G2 proves to Gartner’s Magic Quadrant model — incidentally, Gartner has multiple properties like G2 Crowd that it has acquired — and new, third-party approaches to comparative technology and solution reviews (shameless plug alert!) like Spend Matters very own SolutionMap.

It’s an open question, and I don’t have the answer. G2 and Spend Matters (at least in comparative rankings) are trying to address some of the limitations of Gartner’s model, albeit differently. Newer models are doing this by providing as close to real-time updates as possible (quarterly in our case), direct customer feedback impacting or driving the rankings, and taking persona-driven models as a precursor to “mass customized” recommendations. Azul Partners is doing this in metals procurement, as well, albeit with price focused crowdsourced comparisons through highly granular SKU-level benchmarking in a cloud-enabled model.

Gartner no doubt sees this shift to peer-based insights, too: it has diversified by buying CEB (a peer-to-peer membership organization with a research/benchmarking side) and others like SCM World (another peer-to-peer membership firm with a similar albeit more targeted model than CEB). It also, of course, hosts Peer Insights.

At the party last night, G2’s “No Magic” man was making the rounds (photo credit: Michael Fauscette). While I’m sure the magic will never run out on comparative matrixes as a general concept, G2’s truly rapid ascent in the tech analyst space with its peer-to-peer model is reflective of the changing tech buying demographic, which is more used to swiping left (or occasionally right) than picking up the phone and scheduling time with an expert (or at least one positioned as such).

The "No Magic Man"

Alas (with a hat tip to Steve Lundin) there’s something to be said for The Death of Expertise, a book that should be required reading for the culturally literate today. Still, the value of aggregate peer-to-peer information is infinitely higher than that created by individuals alone. At least in my book. Or was that tweet…

After all, there’s no magic in hard data. It’s the solid state fuel for AI-based expert systems — and maybe the occasional expert, if any of us end up being left — to drive intelligence, insight and, yes, recommendations.

Whether for a date, a place to eat or your next CRM system.

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