Optimizing Existing Survey Data and Using Visualization
Posted by | Fuld & Company
A retail brand spending millions on market research was not using the data to its fullest potential. In limiting their analyses to the survey agencies’ published results and summaries, many insights that the data could potentially reveal were being missed. Realizing this, the brand sought to revisit its previous research datasets in order to gain additional insights and greater analytics flexibility.
Objective
To provide business users with the ability to visualize, explore, and leverage past survey data to its fullest potential, and with the flexibility to utilize the data for insights related to their unique business challenges.
Approach
- Survey questionnaires and responses from the past year were analyzed; key survey discussion themes and previously unidentified or unreported insights were identified.
- Survey findings were summarized, supporting or contradicting evidence for business hypotheses were identified.
- Discussions were held with the client and survey agencies to capture any context necessary to interpret the results.
- A coherent storyline incorporating key takeaways was created, and a filtered set of research priorities was identified as next steps.
- Relevant data slicers and drill-downs for different target audiences (end-users) were identified; a dashboard was designed to support storytelling and insights exploration.
Results
- Past studies were leveraged to gain insights into five primary themes and 12 sub-themes.
- The scope of future research studies was reduced by identifying key gaps in the business visibility of customers.
- Annual marketing spend was reduced by $160K by recycling datasets from recent past studies to address current business questions.
Tools
Tags: case study, Consumer Products & Retail, Data analytics, Market Research
