Any suggestions for a dashboard about conversion blockers on website?

[Data_Dude_Dolan]

Curious if anybody has any ideas as to what to include in a dashboard about conversion blockers on a website? Any helpful metrics/segments that help to illuminate issues on a website. All suggestions and tips are much appreciated!

[RobertBlakeley]

I translate  "Conversion Blocker" into Usability in my head. (Slow page loading, Broken link, Misspelling, Large Images, Outdated documents, Too many links, Low word-count, 404 pages, Poor call to action, etc. Too many to list, and what's matters depends on your business model.

We monitor our key metrics overall (PV, Time Spent on Page, Page Velocity, etc) for changes. We set up anomaly detection based alerts based on those. We also monitor a few simple items overall for sudden changes such as 404 pages for site platform issues. Outside of Adobe, we use tools to monitor things like server response times.

Mostly we evaluate "conversion blockers" when updating individual pieces of the site through testing, e.g. a/b or before and after evaluations, based on specific business goals.

[kayawalton · Accepted solution]

It depends a lot on how you define conversion because that would then determine what the blockers or obstacles can be. I would look at overall goals first and think about potential obstacles that may be a problem and create visualizations to support or debunk if that is happening on your website. OR if you don't have any clue on the latter, I would start with the ideal user path toward meeting your goal and create a fallout visualization that follows that path. If you see that there is significant fallout within a certain step or two, you can use that to dive deeper in what is potentially causing that fallout.

This may not apply to your organization, but here's an example of how we think about conversion blockers, how to identify them, and how to address them using AA:

We consider media completion as an important conversion for our websites, so we set up dimensions and metrics around that metric that will help us identify whether there are factors that prevent visitors from watching our videos as much as possible.

We set up metrics (media plays, media completion, total watched time), event triggers when a visitor reaches a certain milestone of the video (50%, 90%), and calculated metrics (avg time watched, avg % watched). For dimensions, we wanted to be able to see video name, but we also set up ways to roll up by certain variables like show name, video length, etc.

To identify conversion blockers, we usually start with overall metrics and look at average time watched or average % watched. If those numbers are relatively low, we would start to apply segments to see what factors may be causing these low KPIs. Those event triggers are also great if we see a pattern in the overall metrics. For example, for one show, we saw a consistent drop-off at the 10% mark and realized that a lot of people did not like the intro to the show. 

Some of the way we use AA to determine media completion blockers:

• We had Workspace projects where our video producers can see overall metrics. 
• We also create a fallout that starts with media play and follows video milestones until completion. They can apply segments using dropdowns to see this fallout for certain shows, for desktop vs. mobile users, for certain devices, etc. 
• We break down media plays and media completion using a heatmap broken down by day and times. 

Hopefully this helps you think about what specific conversions you may have and how to translate measuring that and its blockers on AA/CJA. If you have specific examples, we are always happy to help you brainstorm some ways to translate those into visualizations or projects in AA/CJA.