Analytics Recipe Cookbook - Summaries

Topic: Predictive CLV for web analytics 

1.  Predictive CLV for web analytics

Posted 01-16-2018 05:29 PM

Introduction:  Customer Lifetime Value (CLV) is a monetary value that shows the amount of revenue a customer will provide the business over a lifetime of their relationship. Predictive CLV is calculated using business specific regression models that are applied to similar cohorts of users. Based on existing data for historical users you can predict behaviour of new users to your business.

Analysis Overview:  We integrate predictive CLV data into our analytics platform such that we can analyze website interaction patterns of users with different level of projected CLV.  The CLV data is calculated as a monetary amount.

Analysis Benefits: 

  1.  You can segment audiences by predicted CLV. This can in turn help you to analyze common patterns and behavior exhibited by two different CLV groups e.g. low rated vs high rated customer buckets.
  2.  These segments could be a direct input to your remarketing, prospect or display ad list. If the ratings for customers changes in the future, it will automatically reflect in your list making sure proper campaigns are directed to respective customers.
  3. Predict your 'most' valuable customers. This in turns makes sure that right campaigns are targeted to them.
  4.  Identify Which products do customers with a low lifetime value tend to research on your site. (and what you can do about it).
Note – This article focuses on possible uses of CLV data in your analytics platform, rather than calculation of CLV itself.

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Abhinav Sharma
Adobe Systems (Corporate Account)
London
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