The concept of Customer Lifetime Value (CLV) might seem self-explanatory, but there are lots of misconceptions of what CLV is and how we can best use it. In short, CLV is a model that estimates the value that a customer brings to your company during its expected time of customer loyalty. If implemented using adequate analytical techniques and predictive models, a high number of use cases open up, including value-based segmentation, evaluation of marketing initiatives and optimisation of acquisition.

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Recommendation engines have gained increasing popularity since Netflix showed how to successfully recommend new movies to their entire user base on a large scale. However, knowing when a recommendation engine is a good fit for your purpose and when it is not can be non-trivial. This first post, in a three-part series, dives deeper into the world of recommendation engines and how you can utilise them to drive business results.

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