Big data has been a foundation of innovation ever since the first suggestion box was put out. Since then, the data set has only kept growing, until now you can filter thousands or even millions of data points. How do you effectively use big data to drive innovation?
Collect Only Relevant Data
Data is often described with water metaphors: as a flood, an ocean, a rushing river, or a surging waterfall. That’s fitting because, if you aren’t careful, you can just as easily metaphorically drown in data as swim in it. If you’re trying, for example, to determine what feature customers want most on your website, it’s more instructive to look at what websites and plug-ins they use on your site, instead of how much time they spend on it. Certainly, you should collect any data you think is relevant, but ask hard questions about which data you need most.
Look Beyond Passively Collected Data
We create data points constantly, from walking around with our phones to clicking on websites. However, passively collected data will only tell you so much. Make a point of actively collecting data. Send out short surveys to customers and clients, research what your competitors are doing and who they’re hiring, and think of other forms of active data collection in which you can engage. You need to pair what people tell you with what they actually do; if the two don’t align, that itself is a telling data point.
What’s Your Goal?
The fundamental mistake made with data is it tells you what you need to know. Data is simply raw material to be shaped by the perspective that looks at it. If you sell physical products, for example, you’re probably more interested in what drives sales, but if you’ve got a service on the market, you’re probably more concerned with engagement after the sign-up or the sale. Much like you can drown in too much data, you can get lost in the forest of interpretation of data just as easily. Choose a direction in which you want to head, whether it’s understanding your customer or looking at which features are used on your site and which aren’t.
One of the most common problems of dealing with a giant raft of data is that by asking a question in a certain way or ignoring the limitations of your data, you can get almost any answer you want. A superb example of this is the claim that this product or that product “made more than the biggest Hollywood movie.” It may be technically true, but if the movie ticket costs $10 and the product costs $100, it’s not as impressive as it sounds. Before you start looking at the data, have the question clearly in mind.
Use A Gut Check
When ice cream sales rise, so do drownings. This is a hard statistical fact, proven across many years. Of course, one doesn’t cause the other; it’s because both rise as the weather gets warmer. This is why gut checks of what the data are telling you are important. If the trends point one way in your data, for example, but your customer actions are telling you something different, it’s worth asking why this discrepancy exists.
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