Tag: RUM

Real User Measurement – A tool for the whole business

The latest trend A key tool in web performance measurement is the drive to implement the use of Real User Measurement (RUM) in 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.

[UPDATE: I work for Akamai focusing on the mPulse RUM tool.]

The key for organizations is realizing that RUM is complementary to Synthetic Measurements. The two work together when identifying and solving tricky external web performance issues that can be missed by using a single measurement perspective.

The best way to adopt RUM is to use the dimensions already in place to segment and analyze visitors in traditional web analytics tools. The time and effort used in this effort can inform RUM configuration by determining:

  • Unique customer populations – registered users, loyalty program levels, etc
  • Geography
  • Browser and Device
  • Pages and site categories visited
  • Etc.

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. Limiting this 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.

The Business users who fed their web analytics data into the setup of RUM need to see the benefit of their efforts. 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 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 dialect 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?”.

Overcoming the Momentum of Traditional Web Performance

When I asked if traditional Web performance still mattered, the post generated a flurry of comments and questions that I haven’t seen in in a long time.

After some reflection and discussions with people who have been tackling this problem for longer than I have, the answer is yes, it does matter. However, synthetic Web performance measurement will not matter the way it does now. The synthetic approach will decrease in importance within fully evolved companies, organizations that have strong cultures of Web performance.

In these organizations, the questions change as the approach becomes foundational and integral to the operation of the online business. Ways of examining competition and performance improvement evolve, and the focus moves – from the perspective of We have a problem to one of of Our customers / visitors have a problem.

The shift is fundamental and critical. For as long as I have been in the business, synthetic measurements have served as a proxy for customer experience. But unless you get into the browser, out to where and how the customer uses the online application, the margin of error will remain large.

The customer is not an operational issue. There is no technical fix for perceived performance.

There is no easy solution for evolving the experience of performance.

Web Performance: The Rise of Browser Computing

The next generation of browser all tout that they are able to more effectively deliver on the concept of cloud computing and Web applications. That may be the case, but it changes the entire world of Web performance measurement and monitoring.

The Web performance focus for most firms is simple: How quickly can code/text/images/flash can be transferred to the desktop?

The question that needs to be asked now is: What effect does my content have on the browser and the underlying OS when it arrives at the desktop?

Emphasis is now put on the speed and efficiency of Web pages inside browsers. How much CPU/RAM does the browser consume? Are some popular pages more efficient than others? Does continuous use of a browser for 8-12 hours a day cripple a computers ability to do other tasks?

The performance measurement will include instrumenting of the browser. This will not be to capture the content performance, but the browser performance. Through extensions, plugins, accelerators, whatever browsers will be able to report the effect of long-term use of the health of the computer and how it degrades the perceived performance over time.

Many solutions for page-performance tracking have been implemented using JavaScript tags, etc. What would be interesting to many developer is to see the long-term effects of the Web on certain browsers. This information could be tagged with specific event markers, DOM events, plugin usage (Flash, Silverlight, Java), and other items that indicate what events truly effect the browser.

Most browsers provide users and developers tools to debug pages. But what if this data was made globally available? What would it tell us about the containers we use to interact with our world?

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