Chapter 2An Easy Primer to Predictive Analytics for Marketers

A natural nutrition company has been in business for 60 years. While it is an $800 million business, the marketing team is small and the company does not have an in-house data science team nor have the systems to leverage the data it collected over the years about its customers, many of which were very loyal. The company is using cloud-based predictive marketing software to organize, understand, and utilize its customer data with significant results.

The software discovered customers that make their first purchase without any free membership promotions spend 76.5 percent more than customers who join with a free membership offer. It also found that customers who placed auto ship orders were likely to spend three times more over their lifetime. The company was then able to develop smart campaigns around membership programs to encourage customers to sign up and enroll in auto ship when possible.

The software also sorted its customer base into clusters, or groups of customers with similar interests. In doing this, it found a weight-loss cluster that was underserved and sent additional personalized communications, resulting in a 300 percent increase in revenue. It became clear that customers tend to make the majority of purchases within specific nutritional categories and rarely migrate across categories, prompting an initiative to focus communications to each cluster around the most complimentary products for each cluster. ...

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