The latest trend in web performance measurement is the drive to implement Real User Measurement (RUM) as a component of a web performance measurement strategy. As someone who cut their teeth on synthetic measurements using distributed robots and repeatable scripts, it took me a long time to see the light of RUM, but I am now a complete convert – I understand that the richness and completeness of RUM provides data that I was blocked from seeing with synthetic data.
They key for organizations now is to realize that RUM is not a replacement for Synthetic Measurements. In fact, the two are integral to each other for identifying and solving tricky external web performance issues that can be missed by using a single measurement perspective.
My view is that the best way to drive RUM collection is to shape the metrics in a manner similar to that you have chosen to segment and analyze your visitors using traditional web analytics. The time and effort used in this effort can inform RUM configuration by determining:
- Unique customer populations – registered users, loyalty program levels, etc
- Browser and Device
- Pages and site categories visited
This information needs to bleed through so that it can be linked directly to the components of the infrastructure and codebase that were used when the customer made their visit. But to limit this vast new data pool to the identification and solving of infrastructure, application, and operations issues isolates the information from a potentially huge population of hungry RUM consumers – the business side of any organization.
This side of the company, the side that fed their web analytics data into the setup of RUM, needs to now see the benefit of their efforts. By sharing RUM with the teams that use web analytics and aligning the two strategies, companies can directly tie detailed performance data to existing customer analytics. With this combination, they can begin to truly understand the effects of A/B testing, marketing campaigns, and performance changes on business success and health. But business users need a different language to understand the data that web performance professionals consume so naturally.
I don’t know what the language is, but developing it means taking the data into business teams and seeing how it works for them. What companies will likely find is that the data used by one group won’t be the same as for the other, but there will be enough shared characteristics to allow the group to share a dialectic of performance when speaking to each other.
This new audience presents the challenge of clearly presenting the data in a form that is easily consumed by business teams alongside existing analytics data. Providing yet another tool or interface will not drive adoption. Adoption will be driven be attaching RUM to the multi-billion dollar analytics industry so that the value of these critical metrics is easily understood by and made actionable to the business side of any organization.
So, as the proponents of RUM in web performance, the question we need to ask is not “Should we do this?”, but rather “Why aren’t we doing this already?”.