Hi guys! Anyone knows if there is a way to see average count of 1 specific event (how many times users did this event on average) for new users within the first 3 days since they signed-in into the app?Thank you!
Hi Lisa Sadchykova
I think it’s a bit tricky to chart out the average only for the first 3 days of new use since the chart interval and the new user condition interval will be hard to normalize on the chart.
One approach I can think of is to try narrowing down the new user interval clause and match it as closely to the chart interval to just limit the usage on the first 3 days. Here’s a demo chart wherein I’m trying to emulate this - https://app.amplitude.com/analytics/demo/chart/new/19a07omwHope this helps to some extent.
Hi, When I add a chart (widget) to my dashboard, and then go to the content and modify the chart (I user another type for exemple) and save, my dashboard doesn't reflect the latest modification. Would you by any chance know why ? Thank you
We implemented first party tracking using the basic JS SDK on the browser and pointing the payload to our servers like this: amplitude.init(AMPLITUDE_API_KEY, { serverUrl: serverUrl, autocapture: { attribution: { excludeReferrers: [/domain1\.com$/, /domain2\.com$/], }, formInteractions: false, fileDownloads: false, }, });…
My Android app is primarily a background app. Does Amplitude track events for such an app? Please let me know.
here is the referance graph: https://app.amplitude.com/analytics/demo/chart/new/363tk5og In this graph, retention is currently being calculated based on the next day, but I want to analyze it based on the previous day instead. Example: For July 27, we should compare retention against July 26, not July 28. * So for 1-day…
Hi everybody! I need your help with a client request: my client is used to analyze landing pages performance with the standard report from GA4 and I need to create something similar in Amplitude. What I already have: * session entries grouped by page URL * purchase event calculated as session totals grouped by page URL and…
