Phase 1: Qualitative research
Everything starts with qualitative research, which is the foundation of successful Human-Centric Segmentation. The qualitative research identifies segmentation factors, which are not purely invented by the organisation itself. Therefore, the factors are based on the customers’ actual motives, values and thoughts.
Phase 2. Data acquisition
Segmentation data is obtained by letting customers rank the segmentation factors (e.g. values and motives) relative to each other. The resulting data is of high quality because customers have to prioritise their values by making compromises. Otherwise you might end up with useless data where customers assess everything to be equally important.
Phase 3. Mathematical and qualitative data-analysis
At Hellon, we have developed a specific mathematical algorithm to segment the factor data. The algorithm outputs the outlines of Human-Centric Segments, which are defined by customer values and behaviour. Finally, service designers take these outlines and colour and flesh them with qualitative insights into fully featured Human-Centric Segments.
The key takeaways:
It is not possible to reliably identify the values, motivations and behaviour of customers using demographic data. You have to look at customers from inside to understand how they think. In our experience so far, the demographic data within our Human-Centric Segments sometimes resemble random noise.
Start with qualitative research to identify the factors for segmentation.
Customers have to prioritize their values by making compromises to obtain high-quality segmentation data.