Seven Deadly Web Analytics Sins    1    2    3    4    5    6    7

By John Marshall

Analytics and the 3D Technicolor Report

Presenting data for the purpose of persuading others within your organization to take action is probably one of the hardest tasks within the world of web analytics. Sure, you can segment, compare and calculate ROI, but when it comes time to persuade the rest of the team to fix that non-performing campaign, go back to an older version of the web site that nobody internally likes (but, it performed better) or change the shopping cart process, you're faced with the daunting task of proving the why and how.

It's Not What You Say, It's How You Say It
Your ability to persuade largely depends on the visual presentation of rational data in an easy-to-understand format that even those who get a rash from looking at spreadsheets can understand. But most web analytics tools don't make your job easy—rather, in a feeble attempt to make the data look 'pretty', they miss the mark by making it unnecessarily hard to understand.

It comes down to this: Data must be clear first, pretty second.

The most common culprit of unclear data presentation is the 3D pie chart...you know, the PowerPoint staple:

Can you easily tell which is the second largest segment without having to read the numbers? The red segment seems the biggest because it's the most prominent color, and more significantly, it has an additional block of color visible on the leading edge because of the 3D effect. To figure out which is the second largest, our brain needs to add up and compare the surface area of each slice of the pie and then conclude which is the second largest slice. We have to work extra hard to subtract the 3-dimensional area—and even then, the chart is STILL hard to interpret because of the distortion introduced by the perspective. For example, segment R6 appears to be half the size of R4...but it isn't.

Let the Numbers Speak for Themselves
In the end, using 3D adornments on graphs only muddies the waters. The compelling force we have to make the data look pretty doesn't affect the facts. Keep your goal of successfully bringing about change based on the facts. To do this, you need to convey the facts clearly and concisely, not dressed up in a 3D rainbow of colors.

ClickTracks' Visual Guiding Light
During the design and development process at ClickTracks, we're constantly generating new ideas that require unique ways to show data. We've gradually come up with a set of data display principles:

1. Show segments: All reports should be segmentable, with the same metric visible across all segments simultaneously, on the same screen. Comparing segments is the most important thing.
   
   
2. Careful with colors: Using colors to represent a value is a mistake. For example 'yellow' is not higher, lower, better or worse than 'green'. Our brains see different colors as having different meanings (red = warning) but not different values.
   
   On the other hand using shades of the same color does convey values. Hence ClickTracks uses different shades of blue to indicate keyword effectiveness, but never uses the 'heatmap' technique of multiple colors. This is the same reasons maps use shades of brown to indicate altitude and shades of blue to show ocean depth.
   
   
3. Buh-bye 3D: 3D adornments do nothing but get in the way. We just say 'no' when it comes to three dimensions on our reports.

While I wish we could take total credit for this, I must instead give credit to Edward Tufte. We're huge fans of his book and lectures. He's well known in academic circles, less so in business. If you need to create persuasive data presentations, I highly recommend you buy and read his books.

So now you've become wise to the sin of simple visitor counts, understand why search term popularity should be unpopular, can pinpoint fatal funnel flaws, no longer suffer from data overload, recognize the benefits of tracking trends over time, look past top ten lists AND understand the basics about presenting data clearly, you've reached the end of our Seven Deadly Web Analytics Sins series.

Seven Deadly Web Analytics Sins    1    2    3    4    5    6    7