Today’s Web interfaces are all about the Flash (literally). Smooth charting, cool effects, callouts to references — ways to try and simplify complex data collections.
Problem-solving and diagnosis requires a far deeper dive than the flashiest interface could ever provide, because it comes down to the numbers. The actual measurements that make up the flashy chart. If you look at the data used by a professional trader and a someone at home looking at stock charts, there is a substantial difference.

When you get down to that level of analysis, the interface becomes irrelevant. Any analyst worth her or his salary (or salt – same thing) can tell you more from a spreadsheet full of relevant numbers than they can from any pretty graphic. This is true in any field.

When do traders or Web performance analysts use pretty charts? When they have to explain complex issues to non-technical or non-specialist audiences. When these analysts work on solving the sticky problems faced in the everyday world, they always fall back on the numbers.

Web performance data consists of the same few components, regardless of which company is providing the data. In effect, beyond a few key pieces of information about how the measurement data is captured, all Web performance data is the same.

Just because the components that make up the data are the same does not guarantee that the data from two different providers is of the same quality. In an imaginary system, Web performance data from all the major providers could flow into a centralized repository and be transformed using an XSLT or some other mangler so that it would be indistinguishable in most cases to tell which firm was the source.

But a skilled analyst would quickly learn to recognize the data that can be trusted. That would be the data that quickly and accurately represented the issues he was trying to diagnose. The data that flowed with the known patterns of the Web site.

The data that helped him do his job more effectively.

In the end, a pretty interface can go a long way to hide the quality of the data that is being represented. A shiny gloss on poor data does not make it better data. It is critical that the data that underlies that pretty chart is able to live up to the quality demands of the people who use it every day.

Selling the interface is selling the brand. Trust in the data builds the reputation.
Which one sold you when you chose your Web performance measurement provider?