I am desperately trying to apply a CLV/TLV (Customer Lifetime Value) algorithm to my dataset in R. Unfortunately, the more I read about it, the less confident I get if all makes sense. =)

Do you have an advice on how I can calculate the CLV? I have been consulting Mr. Google for days but couldn't find the right answers. Actually, I am seeking an example of code on Github or so... with a df that represents an algorithm in sBG or CLV in RFM, Naive etc.

I have a normal transaction dataset for a contractual business with yearly contracts and would like to calculate for each and every customer the CLV for my thesis. A previous fellow student of mine tried to do that in Excel and was able to calculate the CLV. However, he couldn't mention to me on what research it was based on. I would like to calculate for every customer the retention rate, secondly, the probabilities of surviving years, calculate a modelled probability to survive in y years and cluster, plus do CLV with revenue.

Most things I found was made in Python and was more for non-contractual business. However, it's not yet clear for me what happens when I apply a non-contractual algorithm to a contractual dataset?!

I would be very grateful if you can point me in the right direction. What kind of approach I should try on the dataset.

I am looking forward to hearing from you!

  • $\begingroup$ Did you solve your problem,? $\endgroup$ – Snedecor Jun 10 '20 at 0:14
  • $\begingroup$ Hi buddy I almost did but stopped working on it. $\endgroup$ – Lebowski Jun 11 '20 at 8:34
  • $\begingroup$ There is a new R package called CLVTools which provids a step-by-step walk-through based on data from an apparel retailer: clvtools.com/articles/CLVTools.html $\endgroup$ – majom Nov 19 '20 at 17:21
  • $\begingroup$ Thanks a lot, I know this guy! now its on R, that's great! I Thank you majom. $\endgroup$ – Lebowski Nov 20 '20 at 18:14

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