Hey everyone,
I’m working on a project to track how often people interact with our platform. I’m using a spreadsheet to do this, but I’m running into a problem.
The tricky part is that the list of users changes each week. Some people might not have any interactions, so they don’t show up. And we also get new users.
I need a way to compare data from different weeks, matching up the names when possible. Has anyone done something like this before? Any tips on formulas or methods that could help?
The goal is to see how user behavior changes over time. I’ve tried a few things, but I can’t quite get it right.
Thanks for any help you can give!
I’ve tackled similar challenges in my work, and I found that creating a master list of all users can be incredibly helpful. Here’s what I did:
First, I made a separate sheet with a comprehensive list of all users who’ve ever interacted with the platform. Then, I used VLOOKUP or INDEX-MATCH (depending on my mood that day) to pull data for each user from the weekly sheets into this master sheet.
For weeks where a user had no activity, the cells would just show as blank or zero. This way, you can easily track a user’s engagement over time, even if they’re inactive some weeks.
To analyze trends, I added columns for calculating week-over-week changes and running averages. It takes some setup, but once it’s done, updating weekly is a breeze.
Hope this helps! Let me know if you want more details on the formulas I used.
have u tried using vlookup or index-match? those can help match names across diff sheets. another option is pivot tables - they’re great for summarizing data over time. might take some trial n error but could work for ur project. good luck!
I’ve found that using Google Sheets with its QUERY function can be quite effective for this kind of tracking. You can set up a master sheet that pulls data from individual weekly sheets using QUERY. This allows you to aggregate all user data in one place, even if they don’t appear every week.
For comparing across weeks, I’d suggest using conditional formatting to highlight changes in engagement levels. This gives a quick visual representation of how user behavior is shifting over time.
One crucial tip: maintain a unique identifier for each user, like an email or user ID. This ensures accurate tracking even if usernames change. Also, consider using data validation to maintain consistency in data entry across sheets.
Remember to regularly back up your data and periodically review your tracking system to ensure it’s still meeting your needs as your platform evolves.