The respondent is asked to perform a specific observation task, and to tell you aloud, spontaneously and in real time, what they’re thinking. This procedure captures unconscious, reflexive response before they have are edited by the conscious mind, which can potentially distort their value. Here’s an example.

The respondent has been asked to examine a bottle of wine closely, and to “think aloud” about it. The subject is “choosing a good value wine to go with a meal”. The session needs to recorded – even a skilled shorthand expert won’t be able to keep sufficiently detailed, accurate notes. Here’s what might be said in response to the wine bottle:

“My first impression is that it’s quite a good wine… quite expensive, that’s from the label, because it has, em, quite an old fashioned, em, hand-drawing illustration. It’s got shiny raised print for the name, and there’s quite a lot of gold on the label, but then when I look at the top, it’s got a metal screw top and, em, it’s been a bit bashed about, so I’m not sure it’s as good as I thought it was at first. …. It’s obviously a red wine, by the colour of the bottle, because it’s dark…. It contains sulphites… So I would try it but I wouldn’t have a very high expectation of it.”

This is a fairly typical example: sometimes it’s clear what the respondent means, but sometimes it isn’t. You can use other methods, such as Laddering, to elicit further detail of individual points of observation that need further understanding.

Analysis
There are various ways of analysing think-aloud results. Common ways include:

• Which features do the respondents mention?
• Which features do the respondents mention first?
• How often do different respondents use the same wording as each other?
• How many of the features are new and unexpected?
• How many of the features involve subjective versus objective features?
• How many of the features involve intrinsic versus extrinsic features?

.

Quantitative analysis

• How many features do respondents use – few, or many?
• How much do respondents say – much, or little?
• How many respondents mention the same features?

• Which features are important to respondents and why: for strategic marketing
• Which features the experts are spotting which the non-experts don’t spot: for risk assessment