It’s a pretty big claim for a little book, but the 51 page Customer Analytics for Dummies says that, by reading it, you will learn to “acquire new customers; grow customer lifetime value; retain customers at risk of defection; enhance customer loyalty and advocacy.”
Customer analytics, it explains, is the process by which predictive insights that will aid the achievement of these goals can be derived from available data. The challenge, however, is that “capturing [data] analysing it, and acting on it to get closer to your customers can sound like an overwhelming concept.”
But, fear not, Customer Analytics for Dummies says: “Sophisticated yet easy-to-use analytic tools are now available for both large and small companies to collect and analyse the data they have to make solid predictions regarding customer behaviour. As a result, customer analytics is no longer the daunting concept it used to be.”
And that pronouncement comes with a warning: “For businesses looking for a competitive edge, it’s no longer a nice-to-have. It’s a necessity.”
However the book contains no guidance as to any of the easy-to-use tools. It focuses entirely on the concepts and techniques of customer analytics, which, in isolation from specific tools are likely to be just as daunting as ever.
What it does show is how some of these tools can be used, once implemented. For example, if an organisation has put in place technology to determine a customer’s social network influence score based on an analysis of the social media presence, then a customer service agent can use that information to make an assessment of the value of that customer when making a retention offer.
Analysis of social networks is a big and growing area of customer analytics.Social analytics “Captures and analyses social data to help predict customer behaviour and take effective action.” Previously, the closest way to get this kind of data was with survey research or focus groups. Social media can provide richer and more meaningful information because the data comes from people saying what they want to say.
Customer Analytics for Dummies explains also how technologies of decision trees and neural networks can be used to microsegment customers for very targeted marketing. “Neural networks are able to uncover complex patterns in the types of customers and rank each customer based on a score, or likelihood, to respond to a specific offer. Decision trees build a very open and interpretable visual that show the patterns that were discovered.”
Anomaly detection algorithms “can identify the behaviours that lead to defection so you can proactively reach those customers at risk of leaving with the right offer to make them stay.” You can also “identify those customers who are a drain on your resources so you can focus your efforts elsewhere.”
There’s much more in Customer Analytics for Dummies. Reading it will certainly give you a good idea of what’s possible with customer analytics, and you’ll know what to look for in customer analytics products. The big challenges lie in identifying all sources of relevant data, putting in place the means to make these data available for analysis, and making the results of analysis available when and where they are needed.
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