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Analysis to solve the problem of abandonment of Plarium users

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Plarium Datathon


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"At the end of April 2020, we've noticed a drop in our company's profit. About 2 weeks later, we've detected a sharp drop in Retention rates.
A smaller share of players continued to play beyond the first day of downloading our game..."


The objective of this analysis is to try and identify the source or cause of these changes in our metrics and provide suggestions for recovery.

Dataset includes:

  • Date
  • Country (top 11 countries and all others under "Rest of the world")
  • Affiliates (top 11 affiliates and "Rest")
  • Regs the number of players who've downloaded our game and started playing
  • Ret_Day1 the number of players who've returned on the next day to play again
  • Ret_Day7 the number of players who've returned 7 days later to play again
  • Spend the total sum we've invested in marketing activity
  • Depositors_DX (Day0, Day1, Day7, Day10 and Day30) the number of players who've purchased at least 1 item with real money, in our game (this is an accumulative number so for instance Day10 includes all depositors of the first 10 days)
  • Deposits_DX the number of purchases of items with real money, in our game (this is an accumulative number as well)
  • Deposit_Amount_DX the sum of real money used by players in our game (this is an accumulative number as well)

Results

The detailed business report can be found here.
You can find the notebook for cleaning the data and some analysis here.

Tools I used

  • Pandas
  • Matplotlib
  • Seaborn
  • Tableau

drawing

Plarium logo

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