For good reasons, surveys are typically designed to cover key topics thoroughly by asking many questions. Yet, that also means the result is heaps of data, which makes it challenging to get to the core answers.
We help you summarise complex data via our data simplification tools – to reduce data noise, we create a few clear variables that tell the story or identify redundant variables that add no value.
Our arsenal of tools for data simplification includes:
- Factor Analysis – ideal for summarising quantitative scales. Creates new composite scores from underlying questions, which capture strongly correlated themes in the data. These can be interpreted and named based on their relationship with underlying questions.
- Hierarchical Clustering – can be used to create groups of question items, scales, or any other type of variables. Many items become a small number of groups, simplifying reporting.
- Index creation – it is easier to track a single index which summarises complex measures or to provide a simple input into other types of modelling. We created indices for measures, such as religious extremism, willingness to stay in a profession (for doctors), and positivity towards a brand.
- TURF Analysis – TURF stands for “Total Unduplicated Reach and Frequency Analysis”. TURF helps us find combinations (bundles) of options with maximum appeal across different groups. Our TURF simulator identifies the optimum bundles of different sizes and allows users to test their own bundles.