Forum Discussion
Cohort analysis - retention rate
Hi, I'm new to Power BI and I want to calculate and show retention rate on dashboard.
I have tables regarding user cohort data and we calculate retention rate as below.
ex.
Retention Rate for Android JP user who installed App A through Facebook network, campaign_1, Image_1 during 2020-01-01~2020-01-02
- Retention Rate (D+1) = (50+140)/(100+200)
Retention Rate for iOS JP user who installed App A through Google network, campaign_2, Video_1 during 2020-01-01~2020-01-02
- Retention Rate (D+1) = (30+40)/(50+100)
* Retention Rate (D+n) = retained_users with period n / retained_users with period 0
| App | OS | Country | Network | Campaign | Ad Group | Creative | Date | Period | Retained_users |
| A | Android | JP | campaign_1 | Image | Image_1 | 2020-01-01 | 0 | 100 | |
| A | Android | JP | campaign_1 | Image | Image_1 | 2020-01-01 | 1 | 50 | |
| A | Android | JP | campaign_1 | Image | Image_1 | 2020-01-02 | 0 | 200 | |
| A | Android | JP | campaign_1 | Image | Image_1 | 2020-01-02 | 1 | 140 | |
| A | iOS | JP | campaign_2 | Video | Video_1 | 2020-01-01 | 0 | 50 | |
| A | iOS | JP | campaign_2 | Video | Video_1 | 2020-01-01 | 1 | 30 | |
| A | iOS | JP | campaign_2 | Video | Video_1 | 2020-01-02 | 0 | 100 | |
| A | iOS | JP | campaign_2 | Video | Video_1 | 2020-01-02 | 1 | 40 |
I want to show retention rate by variables (App, OS, Country, Network, Campaign, Ad Group, Creative, Date).
How can I solve this problem ?
You cannot show the retention rate by date. Remove the [date] column from your table visual.
Then it is easy to create the measure. For each "row" of the table visual identify if the period is 0. If yes, skip the row (return BLANK() or 1). If no, create a variable to calculate the sum of Retained_users , replacing the Period filter with 0. Lastly divide the sum of Retained_users for the current "row" by the calculated variable.
5 Replies
- lbendlin
Super User
You cannot show the retention rate by date. Remove the [date] column from your table visual.
Then it is easy to create the measure. For each "row" of the table visual identify if the period is 0. If yes, skip the row (return BLANK() or 1). If no, create a variable to calculate the sum of Retained_users , replacing the Period filter with 0. Lastly divide the sum of Retained_users for the current "row" by the calculated variable.
lbendlin lbendlin
I am wondering if you could help me with a similar issue around attrition rate. I have the data setup in a way that has the periods and the churn for those periods identified.
What I am struggling with is how to get the cummulative totals. (See examples from Excel)
I have spent a week wracking my brain on the caluclation to perform this, but I haven't been succesful.
Period 3 Example
Period 6 Example
I was trying to do a date diff based on the max date where the subscriber count wasn't blank, but I can't get it accross the finish line. I would GREATLY appreciate anyone who could help
- lbendlin
Please provide sample data in usable format (not as a picture) and show the expected outcome.
Thank you in advance for your time and guidance..I am more than happy to attach a file the info below isn't clear.
The formula for the Output is below
Month 3 Sum( Month active Column: rows 0-3 Jan-Jan 2021)/Total Column :Jan-Mar 2021
Month 5 Sum (Month Active Column: rows 0-5 Jan-Nov)/Total Column :Jan-Nov
DATA TABLE
0 4,103 3,674 3,858 4,015 4,391 5,985 4,420 5,390 5,801 2,905 2,880 3,722 3,421 3,789 4,948 2,885 1 2,575 1,917 2,072 2,729 3,067 3,803 2,794 4,169 4,221 2,013 1,993 2,535 2,518 3,598 3,505 2 1,404 961 1,207 1,324 1,560 2,095 1,593 1,648 1,939 969 1,014 1,759 1,190 1,204 3 1,307 967 1,048 1,414 2,042 2,375 1,963 1,674 1,662 1,247 1,126 1,369 1,276 4 846 680 957 1,396 1,605 1,891 1,334 1,513 1,964 924 899 1,198 5 780 1,033 1,186 1,117 1,257 1,449 948 1,199 1,206 739 689 6 1,063 987 838 876 1,044 1,173 944 879 1,000 560 TOTAL 46,798 39,759 42,528 42,541 52,166 63,271 49,469 56,152 59,594 34,984 34,898 49,548 41,968 43,666 58,532 36,388 OUTPUT Attrition Same Month (0) 8.8% M+1 14.9% M+2 17.9% M+3 21.0% M+4 23.7% M+5 26.2% M+6 28.2% Sorry for the view above it trimmed out the month headers on the columns when it converted it. I am more than happy to send an email if you have time
