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Why Customer Insight Requires Predictive Analytics

Why predictive analytics should be an essential cog in any marketers toolbox

16Apr

A company’s knowledge of its customers can make or break it. 

For marketers, there’s no bigger advantage than having an idea of what their target market’s going to be interested in, and whilst it’s not an exact science, having data is better than having no data.

When compiled correctly, predictive analytics can be extremely powerful. Major supermarkets, including Target and Tesco, use their reward programmes to track their customers purchases, giving them sophisticated information on individual people.

The information can be scarily specific, with companies even able to pinpoint whether their customers are pregnant. As we all know, our buying habits are often a reflection of our frame of mind - if a customer purchases more alcohol than normal they might be having a bad week and having this insight gives companies the opportunity, regardless of how ethical it is, to bombard their customers with relevant offers.

As mentioned before, this is not an exact science. Just because someone’s bought more alcohol than they normally would doesn’t necessarily mean that they’re depressed, it’s quite possible that they’re having friends round. With this type of scenario, additional data normally makes the scenario clearer.

Although analytics are an essential tool in any marketers toolbox, relying on it too reasily is not recommended either as the intuition of experienced marketers still holds real value. Due to this, the best scenario is to blend the two together and to supplement the data with real life experiences.

It’s unlikely that many successful companies will be without some kind of analytics programme. We’re in 2015 and companies that ignore analytics are at real risk of being left behind their competitors. In truth, I'm sure that most established players have invested in some form of analytics programme by now.

Now comes the difficult part, using the programmes effectively.

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