I’m pondering my poll results from the Gartner data center conference, and trying to understand the discontinuities. I spoke at two sessions at the conference. One was higher level and more strategic, called “Is Amazon or VMware the Future of Your Data Center?” The other was very focused and practical, called “Getting Real with Cloud Infrastructure Sevices”. The second session was in the very last slot, and therefore you had to really want to be there, I suppose. The poll sample size of the second session was about half of the first. My polling questions were similar but not identical, and this is the source of the difficulty in understanding the differences in results.
I normally ask a demographic question at the beginning of my session polls, about how much physical server infrastructure the audience members run in their data centers. This lets me cross-tabulate the poll results by demographic, with the expectation that those who run bigger data centers behave differently than those who run smaller data centers. Demographics for both sessions were essentially identical, with about a third of the audience under 250 physical servers, a third between 250 and 1000, and a third with more than 1000. I do not have the cross-tabbed results back yet, unfortunately, but I suspect they won’t explain my problematic results.
In my first session, 33% of the audience’s organizations had used Amazon EC2, and 33% had used a cloud IaaS provider other than Amazon. (The question explicitly excluded internal clouds.) I mentioned the denial syndrome in a previous blog post, and I was careful to note in my reading of the polling questions that I meant any use, not just sanctioned use — the buckets were very specific. The main difference in Amazon vs. non-Amazon was that more of the use of Amazon was informal (14% vs. 9%) and there was less production application usage (8% vs. 12%).
In my second session, 13% of respondents had used Amazon, and 6% had used a non-Amazon cloud IaaS. I am not sure whether I should attribute this vast difference to the fact that I did not emphasize the “any use”, or simply because this session drew a very different sort of attendee, perhaps one who was farther back on the adoption curve and wanting to learn more basic material, than the first session.
The two audiences also skewed extremely differently when asked what mattered to them in choosing a provider (choose top 3 out of list of options). I phrased the questions differently, though. In the first session, it was about “things that matter”; in the second session, it was “the provider who is best-in-class at this thing”. Where this really became a radically different result was in customer service. It was overwhelmingly the most heavily weighted thing in the first session (“excellent customer service, responsive and proactive in meeting my needs”), but was by far the least important thing in the second session (where I emphasized “best in class customer service” and not “good enough customer service”).
Things like this are why I generally do not like to cite conference keypad polls in my research, preferring instead to rely on formal primary research that’s been demographically weighted and where there are enough questions to tease out what’s going on in the respondent’s head. (I do love polls for being able to tailor my talk, on the fly, to the audience, though.)