Data might be getting bigger, but its definition is getting smaller


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Data is getting big right? We all know that by now. We’ve got the message. It’s getting so big that it’s bursting at the corporate seams, bubbling up from the research, insight and analytics floor in to the boardroom where more often than not it’s deposited as a vast incoherent mass on the CEO’s, CMO’s, CSO’s or C-whatever-O’s floor, in the hope that someone spots a number that they like and doesn’t ask any difficult questions.

Possibly a bit cynical, and to be fair it’s widely acknowledged that data storytelling is of paramount importance for the modern-day analyst or researcher. One often unacknowledged challenge however, is educating the rest of organization on exactly what data is.

For some reason it seems that the practice of web analytics increasingly has a monopoly on the use of the word “data.” It’s a mistake I’ve seen time and again in organizations that I’ve worked with and for: more often than not, at a senior level, the word “data” is being used synonymously with analytics data. i.e. behavioural, metered, observed and tracked data. For some reason, the vast amounts of research, analysis and insight produced through “traditional” market research methods no longer seems to count.

Suddenly self-reported, attitudinal, ethnographic and surveyed research doesn’t fall within the definition of “data”. I’ve even heard a piece of survey-based market research being referred to as “qualitative research” … heaven knows what the results of an actual focus group from the UX lab would be referred to in this context. A “quick catch-up” with our audience maybe?

I’m no Big Data luddite by any means. Helping publishers harness the power of their own first party analytics data to tell compelling stories for brands and consumers alike is something I’ve had a lot of fun doing, I just think we need to remember not to throw the baby out with the bath water as we become mesmerized by the shiny and new promise of what big data can deliver.

Behavioural web analytics data can only ever tell us so much in isolation. It struggles to tell us about people’s attitudes, or what their sentiment is towards something or indeed what it is that’s driving their behavior on a deep routed cognitive basis. Big Data has been fantastic at raising the profile of insight teams, at placing data at the heart of the strategic decision making process and at democratizing data analysis, but it comes with its own warning too. As the recent facebook video metrics debacle highlighted, if behaviours can be gamed, then so too can behavioural metrics, and often such nuances are undetectable to the uninitiated.

At the same time, the traditional research and insight world cannot rest on its laurels, safely assured that only they have the technical rigour to bring data to life. The world of Big Data (however you choose to define it) and market research become greater than the sum of their parts when combined, and indeed some of the most interesting projects I’ve ever conducted have done just that.

Nothing is going to stop data getting bigger, guiding the strategic process with ever greater degree of accuracy and accountability. If you’re going to get big with your data however, make sure you stay big with how you think about its definition too.

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