A Data Junkie’s Thoughts on How to Use Data Strategically

by Agnieszka Girling, posted October 9th, 2008
categorized under how to, research

The heating up of competitive pressures in the technology markets requires that corporations and product groups make increasingly well informed, data-grounded decisions. As product cycles get compressed, the need for agility undermines some of the traditional data-collection methods. One of the challenges of informed innovation lies in the need to get more value out of the data – faster. Most corporations tend to invest a lot in collecting data (user data, market data, competitive data, and lots more). Most will tell you that they don’t or haven’t really used data they have for all it is worth.

If they do, they may not be telling the full truth: many don’t actually track the data they collect so that when the need arises, they may not actually realize they have some research available to answer their questions or guide their decisions.

Let’s NOT talk about principles for running good research (because plenty has been written on that). Instead, let’s talk about a few simple ideas on how to make data more useful. In other words, let’s talk about how to do more with less.

Part One: From the Horse’s Mouth

I love quantitative data. I really love the idea that you can understand quite precisely (within a small margin of error) what is happening in the world. That’s powerful stuff. The one major shortcoming of quantitative market data – the way we tend to use it in business decisions – is that the “voice of the customer” gets lost in charts and graphs. The same is true in qualitative research summaries, where the findings can distill the user perspective to a few bullet points, but deprive it of any human coloration. 

While graphs and charts – and bullet points - can be incredibly powerful, I have noticed that they need some help to be really effective. I have conducted a simple yawn count exercise, which – while not precise - can be somewhat of an indicator of what I am about to conclude. Over the last 3 months, I have presented data, or watched data be presented (in a variety of meetings, on a variety topics and projects), and have kept an informal count of yawns (yes, yaaaawns), and here is the summary of findings (please don’t yawn):

Yes, it requires a bit of effort to understand this chart, but in short, the slides containing charts or graphs generate a lot more yawns in the audience than the ones containing real user highlights (such as photos or quotes). If you trust my count method, you may even conclude that the difference between the yawn counts is greater than the uncertainty of the data itself. In short, it appears that the mental effort required to understand quantitative data is much higher than to relate to simple human words and images. (Certainly, there have been great presentations of statistical data, including Al Gore’s ecological documentary “Inconvenient Truth”, or the remarkable TED presentation by Hans Rosling, Debunking third-world myths with the best stats you’ve ever seen. That said, those are extremely resource-costly productions).

I have observed the glazing-over of eyes over the years, and had to control some of my own yawns when trying to derive deeper meaning from presented stats. Some audiences are more accepting of data distillations, but others – which I see clearly now that I work among creative folks – have a much more difficulty being inspired by them. So I have come around to the idea that even when presenting quantitative view of the world, the credibility and understandability of your points goes up tremendously if I you sprinkle in a real, human, user perspective. Like this:

The reason it is acceptable and relevant to mix those data types is because the user perspective is just the other side of the same coin as the market statistics. Market research and user research simply represent a macro view and a micro view, respectively. Adding a handful of user quotes or photographs can paint a tangible picture of what users are trying to do, where they’re struggling, or what motivates them. That does wonders for most audiences, including executive ones. I find the influence to be much, much greater if I lead with the “voice of the customer”, and I have, as a result, developed a set of techniques that combine broad view of the market with a direct user perspective.

Echoing the Customer’s Voice

So how do you get those direct representations of the “voice of the customer” without conducting a full round of qualitative research? A few ideas:  When conducting analysis of existing data simply look for quotes and photos. There are tons of real user data sitting around on social networking sites, product review sites, anywhere. Text quotes are easy to find. They are merely a means to frame insights into a conversational tone. They also help keep away from over-generalizing or losing context. By using quotes, you gain a sense of place, emotion, and motivation. 

As far as photography is concerned, we’re not talking about stock photography, but photos from the field. Stock photography lacks the spirit of the problem or opportunity that you are trying to communicate. If pictures are worth a thousand words, you’ll be sure to make good use of your slides by ensuring that each image is used to make one point, and one point only. We’re lucky that our researchers have deep interest in photography so we have a great repository of photos from the field. As one of our researchers said, “It seems that all great photographers are anthropologists deep down.”

If you don’t have relevant user materials on hand, reach to a couple of customers for a chat. We have, where appropriate, resorted to friends-and-family research (got to be careful to ensure that the people you are getting quotes for actually represent the customer segment you are describing). We find that even in projects where there isn’t a formal user research stage (as in, generating new user research), that still talk to a few customers for that human perspective. It makes a ton of difference.

Another thing that works really well is to present the results of analysis of quantitative data as a user persona. While the data may be derived from a quantitative set of sources primarily, putting a face on the customer segment, and associating a few (real) quotes results in a much more inspiring deliverable. In that case, the persona represents the analysis of combined quantitative and qualitative sources.

That concludes the first entry to a 5 part series on how we can use data strategically under any circumstance. Stay tuned for more soon…

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