I’ve been working on a project where we’re trying to come up with a way to establish a visual design “clutter index.” The goal is to see if there is some threshold beyond which web page clutter impacts business metrics like conversion and click-through rates. The challenges are widespread of course, and mainly focused on the following 3 areas:
- The definition and measurement of clutter. There are a variety of ways to measure clutter on pages, ranging from the completely objective (e.g., % of white space on a page) to completely subjective (e.g., how do users rate the page on a clean vs. cluttered scale).
- The definition of conversion. Since some pages on an e-commerce web site are revenue-generating, and others aren’t, an important question is how you define conversion. For revenue-generating pages (e.g., pages with a “checkout now” button) this is easy — “Did the page result in a sale?” For other pages, like product information pages, this measure won’t work, so some other measure of engagement with the page becomes necessary.
- Controlling for other influencing factors. In conjunction with the first two points comes the problem of causality vs. correlation. Assuming you have your definitions of clutter and conversion nailed down, how can you be sure any changes you see in conversion is caused by clutter (causal relationship), and not some other factor you are not accounting for (there’s correlation but no causal relationship).