Conjoint analysis

What it is

Conjoint analysis is a form of quantitative research offering powerful insight into customer preferences, from a simple set of questions.

Participants (usually potential customers or service users) are asked to choose between a couple of packages - or in our case, service variants. This process is repeated several times with different variants.

The participants’ choices are fed through a computer, for a rich picture of preferences in terms of the service’s underlying qualities (for example time of day, cost, and speed). The results are more accurate than if the participant had ranked the qualities separately (without thinking of them in the context of complete services). The ideal service mix is magically revealed, even though it probably won’t have been one that the participant actually saw and ranked.

What you get

Conjoint analysis ranks people’s preferences within each quality (for example, for the quality “time of day”, morning may be preferred to afternoon). But it also reveals the relative importance of the qualities themselves - for example, time of day may play a lesser role in customers’ decision-making processes than speed.

Yellow, not red. Cheap, not expensive. But most importantly, large, not small.

It’s also possible to produce data showing where the biggest changes in sensitivity are, for a given quality. For example, people might object more to a jump from low to medium price, than from medium to high.

When to use it

An obvious prerequisite is that the qualities you’d like to test (the aspects and components of your service) must be known. Towards the beginning of a project (in the identify phase), conjoint analysis can be used to highlight areas in need of the most creative focus.

The technique is also useful later in a project when ideas have started to gel - during the build phase. It can validate the potential popularity of a service before production, shedding light on features to keep or reject, or how best to bundle them. 

Lastly, conjoint analysis can help pinpoint which aspects of a service to emphasise in terms of marketing, and at what price point to launch the service.