Return on Investment (ROI) analysis is normally thought of as something that only businesses do in trying to work out how to make cost-effective decisions. In fact, ROI is something that normal consumers think about a great deal, albeit in an informal capacity. In fact, understanding how consumers make these judgement calls is very useful to know.

When business think of ROI, they think of the investment and return in financial terms. This is convenient because they are comparing like for like, so all the data can be pumped through spreadsheets and models. Consumers, on the other hand, don’t have it so easy. Their investment is made up of perceived time and effort, as well as cash payment. And they don’t know how much time and effort is required until after the act, so they are constantly having to keep track of the “feel” or “scent” of an experience.

Throughout the entire duration of an experience, users will weigh up the perceived effort against the perceived reward. This is a balancing act: so long as they believe the reward will outweigh the effort, your site gets the green light. As soon as the balance tips towards more effort than reward, they hit a tipping point: a “screw this!” moment, when they decide it’s not worth their bother and give up.

What’s interesting here is the scarcity of the information that consumers use to make their judgements. Sometimes a site just doesn’t feel credible, and this can be down to a cheap logo or dodgy typography. Other times, if you have a little tussle with a tricky form, it’s enough to make you give up and leave. It’s the same when you buy a second hand car. You look for rust in the wheel arches, listen for odd sounds when test driving, but ultimately you have to make generalisation, based on a few sparse facts – i.e. “Based on what I’ve experienced so far, is it worth seeing this through?”

This is why designers have to be obsessive perfectionists. Small flaws in a UI are the equivalent of rust-spots, squeaks or scratches on a second-hand car. They tell a story for what the user can expect in the future.