Analysis of survey open ends for Airline Executive Club, powered by strat7.ai
Testing key hypotheses and benchmarking performance for a leading UK restaurant brand.
An airline club wanted to analyse 50,000+ open ends across two surveys to understand the main themes of conversation on their NPS score and Suggestions for Improvements. These themes would tag conversations on a new monthly survey tracker. This would help to detect shifts in consumer sentiment and understand the differences in responses across subgroups in the survey.
A machine learning model helped to identify the initial topics of conversation in these open ends. We then iteratively built a topic model framework with the client to ensure that the topics would be future proofed when applied to future survey waves. These topics were analysed against the structured survey fields to deepen the insights – e.g. analysing the ‘Lounge Access’ topic area by Age and Persona.
By leveraging the open-ended responses as a business asset, we were able to uncover the main themes of conversation and track these over time, connecting these to the reaction to company announcements and industry wide events.
Our proprietary strat7.ai Topic Profiler tool help to deliver ongoing monthly insights to the Insights Team.
Using strat7.ai, we extracted 40,000 mentions and rapidly created a searchable data dictionary of shows to search through the unstructured text.
Global Head of Consumer Analytics & Insights | Decision Sciences, Diageo