An example of our work

This example is based on real cases that we've worked with.

Suppose that you want to find out people's reactions to your products or services. One common approach is to use a Likert scale like the one below, which has five categories, ranging from strongly dislike to strongly like.

The limitations of this approach are well known in standard survey best practice. Among other things, it seriously limits the ways in which you can analyse your findings.

A more powerful way of asking the same question is to re-phrase it as two questions. In the example below, we've used two lines, one running from don't like to strongly like, and the other running from don't dislike to strongly dislike.

With this method, you ask the participant to make a mark at the point on each line corresponding to how they feel. For instance, if they don't much like the product or service, they would make a mark near the don't like end of the line; similarly, if they don't particularly dislike it, they would make a mark near the don't dislike end of the line.

This method gives you some powerful advantages when you analyse the results.

In one of our studies, we looked at perceptions of home pages on websites. We found that there were several ways in which a website could be rated as in the middle of a single scale. Those ways have big implications for an organisation's decisions.


The picture below shows this approach applied to three imaginary products. All three had average ratings on a previous survey with old-style Likert scales.

Product A had average ratings because nobody had strong feelings about it either way; it was boring, but harmlesss. It needs to have something good added.

Product B had average ratings because of the "Marmite effect". People either loved it or hated it, and the two sets of numbers had balanced each other out in the previous survey. It needs to be treated as a cult product.

Product C had average ratings because everyone both loved it and hated it at the same time. Again, those ratings had cancelled each other out. It needs to have bad features removed.

This example shows how a subtle change in approach can give much more powerful insights, with very practical implications.