How Can Customer Insight Teams Understand a Moving Target?

How Can Customer Insight Teams Understand a Moving Target?

Home may be where the heart is, but it’s increasingly not where the data is. The days of categorising customers solely by their postcodes are over: today we have a wealth of data from almost every part of individuals’ lives in and out of their homes. The trick for businesses is making sense of this data to draw useful and actionable conclusions.

Location data is no longer restricted to IP addresses from home broadband connections. According to ComScore, roughly two out of three Brits now own and use a smartphone — and that figure looks likely to grow as the vast majority of new handset purchases are smartphones.

In addition, as so many online activities now use geotagging by default there’s a wealth of data available about exactly where people go during the day. Of course, using location data to specifically track an individual’s physical movements and activities is both ethically and legally dubious. However, working in aggregates can still be remarkably insightful. For example, analysing comments posted on Facebook by people who are ‘checking in’ at a gym might reveal whether that particular audience is more likely to be thinking about buying health foods or junk snacks when they leave. That information could inform strategic decisions on everything from poster advertising to store locations.

It’s even possible to use ‘sentiment analysis’, that tries to judge users’ moods from their online activity. A national chain can quickly identify a problem with a local store if it sees a lot of negative comments posted while at, or shortly after leaving, a particular location.

The danger is being overwhelmed with the sheer quantity of data that’s available. That’s why location analytics — that combines multiple sources of data and displays them in easy-to-read visuals — is truly the analysis tool of the smartphone age.

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