Funnel friction analysis

Transcript

Hi, this is Patrick McLachlan, and I’m a Group Product Manager on the Adobe Analytics team. I’m here today to show you the friction view on the funnel analysis in Adobe Product Analytics. This view helps me isolate friction in the critical user journeys of my product, compare conversion rates between steps, and see the whole context of journeys of my product. Let’s get started. In the friction view, I want to see how well users are making their way through my product. I can enter in the key events of this journey in the query panel on the left. These can be any events that we’ve stitched together at the person level, so we can even look at actions that happened after my purchase workflow, like returns. I can apply and compare segments that my team uses across Customer Journey Analytics or Adobe Product Analytics. The insight, chart, and table below are filling in about my funnel, so I can see the conversion rate and drop-off rate at any given step. I can also change how we’re computing conversion rates versus the previous step instead of versus the first. Now, when I’m looking at this, I’m seeing the drop-off rate at each step compared to the previous one. From each one of these, I can save a segment for further analysis or to take action elsewhere in the experience cloud. I can zoom into one segment and then apply a time comparison to see how these rates have changed compared to last year. From this view, I can save and share to my colleagues to help bring product data to more throughout my organization. Thanks and have fun playing with the data.

Transcript

Hi, this is Connor Lamoureux, and I’m a software developer on the analytics engineering team. In this video, I’ll show you the funnel comparison feature in Adobe Product Analytics.

The funnel view helps you understand where there’s friction within key user journeys in the experience. But what if your journey is imperfectly linear or there are multiple paths to success? The comparison capability allows you to compare multiple events in a single funnel step, so you can compare several journeys side by side to see which leads to the highest conversion rate. This is useful in their step options, or an AB experiment is being run within the funnel. In this example, we’ll be looking at a video streaming platform will determine what user journey results in more videos being started and completed, which are key engagement indicators for a product.

Let’s start by adding two steps in our funnel. View my category list and searches.

Search is just one way users can find videos to watch. So let’s add a comparison of this step. When we select the menu next to the searches step and click the compare option. We’ll see that the searches step becomes indented. It’s now a comparison step. By clicking add a step, we’ll compare searching for a video with finding a video from a user saved list. Now you can see that an additional bar has been created for each funnel. Step on the bar chart, creating two journeys for side by side comparison.

Each bar shows the funnel path for one of our comparison steps. The first bar in each step shows the path for searches, and the second bar shows the path for view. My list.

Let’s add media starts and completes. To complete the full funnel view, we want to measure.

With the full path concluded. We can see the finding videos through our second comparison step. View my list results in a lower percentage of users completing a video. We can also see right away on step two that a much lower number of users find videos this way compared to searching.

By hovering over this last bar, we can see which comparison step is being used and some more detailed information about the converted users. As a product team, this highlights an opportunity for us to invest in the discoverability of search to encourage more users down this path.

Let’s look at our chart settings so we can see the conversion rate from the previous step rather than the first step.

This gives us some additional information when comparing our two steps. We can see that while fewer users are finding videos using their list, users that view videos from their list are much more likely to finish the video.

We can add up to three comparison steps on a single step. Let’s add a third option to this analysis. We’ll compare these two paths with users who find videos from their favorites.

Now our chart will have three bars for each step, allowing us to compare the three journeys side by side. It looks like searches and favorites both have strong conversion rates, but when viewing conversion from the previous step, favorite users complete their videos at a slightly higher rate. This would make sense since they are their favorites after all.

Down below the chart, a table provides data for each of the paths. The first column of the table shows the funnel path name, followed by the total conversion rate for each. This gives a clear view into its journey. Leads to a more successful conversion rate for your users.

This has been an overview of the funnel comparison feature in Adobe Product Analytics. I hope this comes in handy the next time you need to analyze a critical product journey in your user experience.