To remember, the explanatory sequential design, think of qual explaining quant. In this study we used a new set of 16 participants you can also use a subset of participants from the first survey phase and dig deeper into any interesting patterns. This enabled us to look more closely into trends we observed in the larger sample. We then recruited a new set of 16 participants for 1-on-1 sessions in which participants interacted with the sites used earlier and discussed their attitudes toward those sites. After statistical analysis and cross-tabbing on experience levels to gauge brand attitudes, we came up with topics to further explore. Explanatory Sequential DesignĪn explanatory sequential design emphasizes quantitative analysis, which we follow with interviews or observation (qualitative measures) to help explain the quant findings.įor example, we conducted a large comparative branding study with an internet retailer on attitudes toward the shopping experience on five mobile websites. While you can combine qualitative and quantitative methods at various points-data collection or data analysis, for example-we typically use the following three research designs (also called topologies). In fact, there’s a journal dedicated to mixed-method research, aptly named, The Journal of Mixed Method Research.Ĭustomer research lends itself well to the triangulating that a mixed-methods approach offers: identifying areas of convergence among methods to, in turn, increase the usefulness and validity of the findings. Mixing qualitative and quantitative methods is neither new nor controversial. While it might seem unorthodox to mix seemingly different fields, it turns out to be a common practice. You can often optimize customer research with a mix of the two. You needn’t think of this as an either-or situation. We often talk of qualitative OR quantitative research.
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