A common reference to the set of subjective responses a person has when using a product, system or service. Typically, satisfaction is measured with questions that have their responses on Likert scales, e.g. "How satisfied are you with this feature?" (1 = very dissatisfied, 7 = very satisfied).
Ordinary people in the real world think and operate within (what Herbert Simon (1957) described as) bounded rationality. Within such bounds, people use heuristics to "satisfice" - i.e. come to a solution that is "good enough" for their purposes (but may be non-optimal in many other ways).
Satisficing therefore describes the situation where people settle for a solution to a problem that is "good enough".
In terms of human problems solving, satisficing is actually an extremely rational strategy, in that looking for (i.e. searching a potentially huge problems space for) the "optimal" solution may be prohibitively expensive in terms of time or resources.
All communication involves a process of creation, transmission and reception of information. At each step in this process, the form of the information - the signal - is degraded, and extraneous information - noise - becomes added.
A signal-to-noise ratio is therefore a measure of the various proportions of relevant (qua easy to see or comprehend) to irrelevant (qua difficult to see or comprehend) information. The game of Chinese Whispers is a good example of the signal to noise ratio at work.
The goal of good design is to make the signal-to-noise ratio as low as possible, i.e. to maximise the signal and minimise the noise. Illustrtions might include:
- Maximise signal by keeping designs simple - white space is always good
- Minimise noise by removing extraneous elements.