Instrumented Interconnecteds Intelligent
November, 9th 2015

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Blog by: Bart De Kempe

Big data analytics: acquire, grow & retain customers

The CMO’s role has never been so exciting. Nor so complex. Companies are operating in a more competitive, global market place, in which the customer has almost endless choice. Meanwhile, that same customer’s means of interacting with a company has changed exponentially. Touch-points have multiplied. In addition to the good old-fashioned store, customers are purchasing, dealing with customer service or otherwise engaging with companies across social media, mobile apps and websites.

Clearly, heightened competition and complexity represent a risk. A company that fails to provide the ever more demanding customer what they want, when they want it, risks oblivion. Or in real terms, reduced customer satisfaction and retention, churn and ultimately a hit to the bottom-line. Likewise, it represents an opportunity to the company that grasps and harnesses big data. Across the board: to improve customer satisfaction and retention, reduce churn, diminish customer service costs, and to maximize revenue.


Enter analytics. We now have tools at our disposal that can help the CMO attain a 360-degree understanding of the customer by combining data from all the aforementioned touch-points, both on and offline. Whether the customer is dissatisfied, gearing up to purchase or just exploring options, we can target them via the right channel, with the right message, at the right time. The long-term prospects are immense. From the basic customer segmentation of yesteryear, we are now looking at highly sophisticated segmentation that allows us to classify customers based on lifetime value to a company, not just basic (and often meaningless) demographic data.

How does it work?

Specifically, predictive intelligence can provide insight into each single customer based on buying behavior, web activity, customer service and social media interaction. This level of detail on each unique customer allows companies to predict and personalize marketing and communications efforts for each customer. Are you a bank? Know whether a customer is ready to accept a mortgage offer or cancel a policy and act accordingly. In FMCG? Understand if a loyal customer is ready to switch to a competitor and why, and respond with a special offer.

Mass marketing, as we have known it is no more.

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