Hi Community,
I am trying to work out whether Ad exposure influenced users to activate the advertised app.
I have a logic defining what counts as "influenced", but it requires one data set to look up multiple rows in the other, and I don't know how to I express it using Alteryx.
Please refer to the attached excel sheet for visual representation.
Basically, I have 2 inputs. One is ad exposure history, containing userIDs and dates when they were exposed to the ad. Second is app usage history, containing userID and dates of when the advertised app was activated. I want to flag each row of the former when app activities were present in the latter within 5 days after the ad exposure. That way I can identify which ad exposure to whom worked and which did not.
I initially thought the first step is to join the 2 data sets, but this will expand the data sets greatly. Perhaps I should summarize the second data set, but I don't know how.
Does anybody know smart ways to perform the desired processing?
I thank you for taking in a look in advance!
Thank you,
Yoshi
Solved! Go to Solution.
Hi @Sekiro,
I prepared solution for you. Firstly I changed type of data from string to date time format. Then I joined it together,
Indeed I applied Summarize tool, with max action to take 1 if there are 1 or 0 avaiable.
Let me know if it something what you look for.
Regards,
Karolina
Hi KarolinaRoza,
Thank you so much for taking a look and creating a sample flow!
The logic of the flow you have provided makes perfect sense. I am struggling to see if it worked as actual data set is massive, but your flow is behaving as I wanted so I am in the clear. I'll keep this method in mind as it is very useful.
Again, thank you so much for your help!
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