Release impact analysis

Learn how to use the release view in Customer Journey Analytics, which shows a comparison of how key indicators performed before and after a given date.

Transcript
Hi, this is Jen Lasser with Adobe Analytics Product Management. In this video, I’m going to show you the release impact analysis in Adobe Product Analytics. Release impact analysis enables me to measure the impact of feature releases or campaign launches on key success events by comparing performance before and after a critical date. Let’s say I just released some new capabilities on June 2nd that I hope will drive higher engagement with our My List page and starting media content. I can go ahead and select my key success events of Media Start and View My List. And I’ll also leave in any event to look at overall engagement. I’ll also select my release date of June 2nd. I can further filter my events if I’d like or filter for more specific set of users if I targeted my release. I’m able to select segments that were created in customer journey analytics or create new filters on the fly. After making those selections in the query rail, notice that I instantly get an answer in the form of a written insight, chart, and table. I can view a before and after average and percent difference for each key indicator. I can see that users viewed their list 13% more and started media 4% more on average than before, while overall engagement is relatively flat. Now I can also inspect the chart to see how each day compares to the average for the period. This helps me understand if there’s a certain window of time after the release that my users tend to be more engaged. Now I wonder if this release date impacted user adoption. I’ll go ahead and change my metric from events per user to percentage of users. From this view, I can see that my adopted user base increased 21% to the My List page and 5% for starting media content. Now if I want to repeat this analysis for a longer before and after period or a different release date, it’s as easy as making a new selection. And there we have it. No need to spend hours redeveloping this analysis. I know my users won’t adopt something the first day it’s released, and sometimes my releases roll out over several days. In this case, analyzing pre-post a specific date won’t meet my needs. This is where the first use impact view comes in handy. It allows me to see how first time use of a product feature rather than a point in time impacts my key indicators. Check out our first use impact analysis video for more details. I hope this video comes in handy the next time you need to measure the impact of a feature release or campaign launch.

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