Latency Analysis with Cohort Tables latency-analysis-with-cohort-tables

Transcript

Hi, this is Travis Sabin, product manager for Adobe Analytics and today we’re going to be digging into one of the new features in our new Cohort Table, the Latency Table feature. So, let’s say I work for a large apparel retailer and tracking product launch and its effectiveness is extremely critical to my business and let’s say I’ve got a product that has been underperforming in terms of online orders for new users. So, I’m gonna come in and build out my Cohort Table with my new users for visiting as the inclusion and coming back later and doing an online order for my product Amazing. Then I’m gonna change my granularity to be day to match my time period and I’m gonna build. Then I can see that I’ve got lots of new visitors coming but very few of them are actually coming in and making online orders for my Amazing product. So, I’m gonna come back and we’ve been working hard behind the scenes to update the product, give it some new stuff and release a new version of it out to the customers and we’re rebranding the Amazing product to something else and let’s say our launch date happened on January 3rd.

And so, now I’m gonna come in and I’m gonna change and activate my Latency Table setting so I can see how the post-launch activity of January 3rd is comparing to the pre-launch activity prior to that day. So, coming in, I can see leading up to this, I’ve had, like we saw before, not a lot of activity in my pre-launch event. But I can see after my inclusion event, I can see that the sales are starting to pick back up again and so, by using the Latency Table feature, I can quickly compare all of my pre-activity to my post-activity to see if I’m getting the kind of results that I’m aiming for with my product launch. This could be done with products, campaigns, many other event-based things that you wanna track the pre and post-activity, Latency Table is really, really good for handling that use case.