Peer influence and the use of Magic Quadrants
The New Scientist has an interesting article commenting that the long tail may be less potent than previously postulated — and that peer pressure creates a winner-take-all situation.
I was jotting this blog post about Gartner clients and the target audience for the Magic Quadrant, and that article got me thinking about the social context for market research and vendor recommendations.
Gartner’s client base is primarily mid-sized business to large enterprise — our typical client is probably $100 million or more in revenue, but we also serve a lot of technology companies who are smaller than that. Beyond that subscription base, though, we also talk to people at conferences; those attendees usually represent a much more diverse set of organizations. But it’s the subscription base that we mostly talk to. (I carry an unusually high inquiry load — I’ll talk to something on the order of 700 clients this year.)
Normally, I’m interested in the comprehensive range of a vendor’s business (at least insofar as it’s relevant to my coverage). When I do an MQ, though, my subscriber base is the lens through which I evaluate companies. While I’m interested in the ways vendors service small businesses at other times, when it’s in the context of an MQ, I care only about a vendor’s relevance to our clients — i.e., the IT buyers who subscribe to Gartner services and who are reading the MQ to figure out what vendors they want to short-list.
Sometimes, when vendors think about our client base, they mistakenly assume that it’s Fortune 1000 and the largest of enterprises. While we serve those companies, we have more than 10,000 client organizations — so obviously, we serve a lot more than giant entities. The customers I talk to day after day may have a single cabinet in colocation — or fifty data centers of their own. (Sometimes both.) They might have one or two servers in managed hosting, or dozens of websites deployed via multi-dozen-server contracts. They might deliver less than a TB of content per month via a CDN, or they might be one of the largest media companies on the planet, with staggering video volumes.
These clients span an enormous range of wants and needs, but they have one significant common denominator: They are the kinds of companies that subscribe to a research and advisory firm, which means they make enough tech purchases to justify the cost of a research contract, and they have a culture which values (or at least bureaucratically mandates) seeking a neutral outside opinion.
That ideal of objectivity, however, often masks something more fundamental that ties back to the article that I mentioned: namely, the fact that many clients have an insatiable hunger to know “What are companies like mine doing?“. They are not necessarily seeking best practice, but common practice. Sometimes they seek the assurance that their non-ideal situation is not dissimilar to that of their peers at similar companies. (Although the opening line of Tolstoy’s Anna Karenina — “Happy families are all alike, but every unhappy family is unhappy in its own way” — quite possibly applies to IT departments, too.)
This is also reflected in the fact that customers often have a deep desire to talk to other customers of the same vendor, on an informal and social basis. That hunger is sometimes satisfied by online forums, but the larger the company, the more reluctant they are to discuss their business in public, although they may still share freely in a one-on-one or directly personal context.
IBM was the ultimate winner-take-all company (to use the New Scientist phrase) — the company that everyone was buying from, thus guaranteeing that you were unlikely to get fired buying IBM. Arguably, it and its brethren still are at the fat forefront of the outsourced IT infrastructure market share curve, while the bazillion hosting companies out there are spread out over the long tail. Even within the narrower confines of pure hosting, which is a highly fragmented market, and despite massive amounts of online information, peer influence has concentrated market share in the hands of relatively few vendors.
To quote the article: Which leads to a curious puzzle: why, when we have so much information at our fingertips, are we so concerned with what our peers like? Don’t we trust our own judgement? Watts thinks it is partly a cognitive problem. Far from liberating us, the proliferation of choice that modern technology has brought is overwhelming us — making us even more reliant on outside cues to determine what we like.
So I can sum up: A Magic Quadrant is an outside cue, offering expert opinion that factors in aggregated peer opinion.