There’s such a depth in metrics that you can track for each part of a web experience, like session duration, time to first action, repeat interactions, new user activations, time to respond… the list goes on. A lot of teams get stuck on the basic ideas of conversion or “engagement”, but often don’t spend the time to determine what those actually mean in order to track them.
A lot of these interactions can also be measured through user testing and leading indicators like UX metrics. We focus on user outcomes such as improved first-click engagement, expected frequency of use, user sentiment, and feature desirability to predict the likelihood of visitors to react to a certain feature. Conducting this testing across multiple variations of a features design quickly clarifies which will have the greatest impact when launched on the site.
We think its important to establish what your leading indicators will be for early concept testing, and then which lagging indicators (site analytics) will show proof of those design decisions, before jumping into creation. This is the clearest path to proving the impact of design decisions right now.
@Bryan It’s succeeds in showing the depth of metrics that can be pulled for every single feature and element on a platform. We’re learning this as we get deeper into our client’s site analytics.
I thinks it’s weakness is less in the framework and more in the execution of it: getting teams to agree on one metric is hard enough, let alone a total of five on one feature. There’s probably scenarios in which using 3 out of 5 of the RAAEE metrics are good enough for teams just started to dips their toes into the data.
I keep coming back to the simplicity of Reach here. Too often we make the assumption that all users or visitors can see the feature, when in reality it might be buried or placed in an important view that few users navigate to on the regular.
Establishing up-front what is necessary to properly assess the effectiveness of the feature is so important.
Thanks for bringing this one back up @EricZ. Now that I revisit this, I realize it’s important to establish what product metrics prove the Reach or Attractiveness for an update.
For instance, I think the Visit Frequency performance metric would be great for establishing Reach by building an understanding of how many unique users interact with a feature compared to overall users. You can actually check out the this performance metric along with all the other UX Metrics in our newly launched Glare framework! https://glare.zurb.com/docs/ux-metrics/performance-metrics/visit-frequency
