A market or customer segmentation can help you to better understand your target audience so you can tailor your messages and marketing activity by segment. Targeting your consumers merely by age and gender just doesn’t cut it anymore.

We design bespoke segmentation studies based on our client’s business objectives and their target audience. Taking a phased approach, we collect key behavioural and attitudinal data on the market and use this to identify distinct, homogenous groups via factor and cluster analysis.

Segments are profiled on psychographics, demographics, and behaviours – providing an in-depth understanding of each segment’s needs.

We often bring segments to life via qualitative profiling, vox pops or ‘meet the customer’ workshop exercises.

While MaxDiff allows us to determine the relative importance of a list of factors/product features, Conjoint adds another dimension by asking the respondent to rank various combinations of factors/product features to determine which ones add the most unique value to an overall product concept.

With conjoint, respondents are shown several concepts at one time (usually between 3-5) and asked to select the one option that they prefer.

This process is repeated several times (usually c.12 times), for different combinations of levels and attributes.

In addition, after respondents have chosen their preferred option we can ask if they would actually proceed with this option.

MaxDiff is used to identify the relative importance of different factors, or the relative appeal of different product features that can help businesses make better informed decisions.

While ‘typical’ ranking questions are relatively simple in concept, they can pose significant barriers to respondents in that:

• They are required to evaluate every choice at the same time.
• Their interpretation of scales may differ from others (scale use bias).
• MaxDiff, also known as ‘best-worst scaling’, offers a more robust approach for obtaining importance scores for multiple items.
• MaxDiff shares much in common with conjoint analysis, however it is easier to use and applicable to a wider variety of research situations.

With MaxDiff, respondents are shown a subset of the possible items in the exercise and are asked to indicate the best and worst items (or most and least important).

MaxDiff questions are typically simple to understand, so respondents with a variety of educational and cultural backgrounds can provide reliable data. Since respondents make choices rather than expressing strength of preference using a numeric scale, there is no opportunity for scale use bias.

Essentially, MaxDiff enables more complex survey questions to be asked without passing on this complexity to the respondent – ensuring respondent fatigue is minimalized, while delivering more accurate results, so there is no need to sacrifice the integrity of the research!