Ideally's regression model is visualised in the Drivers tab offering a driver diagnosis of top verbatim themes.
What is a regression model?
A regression model is a statistical technique used to understand how multiple factors (independent variables) influence a single outcome (dependent variable). It helps predict or explain changes in the outcome based on various inputs.
How does Ideally use regression models?
At Ideally, we use regression models to connect respondents’ feedback about a concept or message (themes identified in open-ended responses) to two key selected metrics.
These relationships are visualised in the Drivers tab, where each “bubble” represents a theme. The bubble’s position shows how strongly it influences the selected metrics.
How our regression model works
Purpose: Highlights the connection between feedback themes and the selected metric scores.
Coefficients: Each theme is assigned a coefficient, indicating how much it impacts these scores when mentioned.
Data requirements for accuracy
Regression models require sufficient responses to ensure reliable results.
No direct segment filtering: Demographic or other segmentation filters can’t be directly applied to regression model results ie. our Drivers tab.
Exploration via Verbatim Explorer: To explore subgroup differences, use the Verbatim Explorer tool to analyse open-ended responses.
By examining these results, you can pinpoint which elements of your concept or message resonate most strongly, guiding you towards more effective product designs, messaging, and strategies.