Return on UX

Reading time: 2 minutes

A 12-year study by of 1,500 websites revealed that all but 45 failed their user experience measures. Failures due to poor text legibility, task flow and use of space topped the list. Thankfully though, such issues are fairly easy to correct. The field of this study included a wide range to include business-to-consumer (B2C) sites, business-to-business (B2B) sites, intranets, and employee portals across many different industries and countries.

The evaluation measured 25 criteria points, where each website could score anywhere from -2 to +2 on each of the 25 criteria, resulting in a max score of +50. Any score 25 or over was considered passing. The average score ended up being ONLY a 1.1! Yes a one-point-one. Yikes!

This is a debated topic, that being how much can just five users really tell you about usability issues. Jakob Nielsen asserted back in 2000 that after about five users the laws of diminishing returns apply in regards to discovering more usability problems, but that you could pretty much find all there was to find after just 15 users.


But others contend that this just isn’t case. While acknowledging that six participants will be sufficient enough to drive a useful iterative design and development process, Rich Molich from DialogDesign argues that the number of usability problems in a typical website is usually so large that an ordinary usability study has no hope of uncovering more than a fraction, no where near 85%, of the existing issues. Molich even goes as far as to say there’s no measurable difference in the quality of the results from usability tests compared to the results of expert reviews.

Numerous industry studies have shown that for every $1 spent on UX, the return is anywhere from $2 all the way up to $100. If you believe the studies, then how could you not invest in UX resources? So why do so many companies still take it for granted and underestimate the value a good user experience brings? Forrester Research shows that a strong customer experience increases a customer’s willingness to purchase by 14.4%, reduces their likelihood of switching to a competitor by 15.8%, and increases their probability of making a positive recommendation by 16.6%.

According to Barry Boehm and Victor R. Basili, the cost of finding and fixing a software problem after delivery is often 100 times more expensive than doing so during the requirements and design phase. Furthermore, they state that 40-50% of effort is spent on avoidable rework, and of that avoidable rework, 80% of it comes from just 20% of the issues.

Here’s the full one-piece infographic: