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Hi there,
I have website data including [Unique ID] and [Login Date]. I want to group my data by checking how many times a unique user logged in over a month, and categorising the count by:
'Not engaged' = 0 logins
'Low engagement' = 1-3 logins
'Moderate engagement' = 4-6 logins
'High engagement' = >6 logins
How do I do this?
Solved! Go to Solution.
Hi Jemma,
Yes - you can have measures like "Average views per day" or "Average views per month" etc. all calculated from and in the same table.
To be accurate, you'd have to calculate this based on the total number of days/months/years a user has been 'active'. Do you have a "User created date" or something similar?
Matt
Assuming your [Unique ID] column refers to a user not an individual login to the site, you can achieve the desired result using the below steps:
Does that give you what you are after?
Happy to elaborate if you get stuck!
Matt
Hi Matt,
Yep this totally works, but I need engagement to be relative to time as well.
For example, someone engaged 7 times in a day that would be high engagement, but if it's 7 times in a year, this isn't high.
So, I can include date in the grouping, i've had a go at separate tables for engagement by day, month, year. I wondered if it was possible to do all this in one table, or as a dynamic measure?
Thanks! 🙂
Jemma
Hi Jemma,
Yes - you can have measures like "Average views per day" or "Average views per month" etc. all calculated from and in the same table.
To be accurate, you'd have to calculate this based on the total number of days/months/years a user has been 'active'. Do you have a "User created date" or something similar?
Matt
Ahhhh I totally see your point. Yes, I can pull in the User's registration date, and do the averages. You're a genius!
Thanks so much Matt!! 🙂
Jemma
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