Presenting at the qual analysis workshop at the AMSRS Summer School confirmed my belief that qual analysis is a hot topic in research
- The term 'analysis' covers a broad range of activities during a qual research project, and is not necessarily a distinct stage as it is in quant.
- The industry needs to work harder to create a more consistent analysis vocabulary.
- Most of us felt that the analysis should be conducted, at least in part, by people who were actually there during data collection.
(Workshop delegates will know the significance of the above three-part list......)
At Susan Bell Research, the three reasons why we always analyse our qual data are:
1. Transparency and accountability. As qual research changes, different types of clients are starting to expect higher standards of transparency and accountability. We are happy to show our clients the basis for our conclusions and recommendations.
2. Get more out of the data. We look for the words people use, the metaphors they choose subconsciously, the assumptions they make about shared social values ..No moderator can be aware of the all of these while conducting a group or interview.
3. Building a model out of the data. Many clients want us to do more than simply describe consumers' perceptions and beliefs; they want us to explain the impact that these perceptions and beliefs will have on their product or service, and they want some kind of conceptual model to help them predict how people will behave in the future. These conceptual models could not be built without the analysis that underpins them.
The idea is to reduce the 'noise' and clutter, to make sense of it, so you end up with less.
