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The Inconvenient Truth About Data Science

I published this first on LinkedIn and received very positive feedback. If you like it too, go to the original post here and click on thumbs up or share on Twitter. Thanks!

  1. Data is never clean.
  2. You will spend most of your time cleaning and preparing data.
  3. 95% of tasks do not require deep learning.
  4. In 90% of cases generalized linear regression will do the trick.
  5. Big Data is just a tool.
  6. You should embrace the Bayesian approach.
  7. No one cares how you did it.
  8. Academia and business are two different worlds.
  9. Presentation is key – be a master of Power Point.
  10. All models are false, but some are useful.
  11. There is no fully automated Data Science. You need to get your hands dirty.


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RFM Segmentation – Introduction Slides

RFM Segmentation is the easiest and most frequently used form of database segmentation. It is based on three key metrics: Recency, Frequency and Monetary Value of customer activity. RFM is often used with transactional history in e-commerce, but can also work for Social Media interactions, online gaming or discussion boards. Based on calculated segments a marketer can prepare cross-sell, up-sell, retention and reactivation capampaigns. This deck provides a simple introduction to the RFM Segmentation methodology.




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Customer Lifetime Value for Subscription Products

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(cc-by) TaxCredits.net

Estimating Customer Lifetime Value allows you to say how much you can spend on customer acquisition and retention. This is especially important for subscription-based products like games, online services, information marketing, loyalty programes etc. In this article we will use a classical approach to estimate CLV with a simple equation and customer cohort analysis. There are more accurate probabilistic models available and I will look into them in following posts. If you are just starting with CLV calculation for your business, I strongly recommend going for the simple solution first and then becoming sophisticated as necessary. Click here to continue reading “Customer Lifetime Value for Subscription Products”…