Customer data analysis
Objective vs. "satisfaction"
All Typeform Responses
Typeform Responses vs. Customers
Predicting whether Typeform filler will buy the product
ntree_limit is deprecated, use `iteration_range` or model slicing instead.
Accuracy of the model 0.71 Recall of the model 0.25
Majority In Each Goal alternative
0 Get metabolically healthier Very Disappointed Lose weight Very Disappointed Find the right foods for me Somewhat Disappointed Stabilize blood sugar Very Disappointed Boost energy levels Somewhat Disappointed Improve sleep Not Disappointed Optimize fasting Somewhat Disappointed Find the right meal timing Very Disappointed Optimize athletic performance Not Disappointed Get rid of food cravings Somewhat Disappointed Eliminate brain fog Not Disappointed Increase productivity Not Disappointed Reduce stress Somewhat Disappointed
Segments with majority of happy customers: Get metabolically healthier Very Disappointed Lose weight Very Disappointed Stabilize blood sugar Very Disappointed Find the right meal timing Very Disappointed Name: 0, dtype: object
Typeform Responses vs. Very Disappointed Users
df_goals_comp = plot_comparison(np.r_[12:25])
Majority In Each Product Group
0 Apple watch Very Disappointed MyFitnessPal Very Disappointed Fitbit Very Disappointed Oura ring Somewhat Disappointed Strava Somewhat Disappointed Withings scale Somewhat Disappointed Whoop Not Disappointed Lifesum Somewhat Disappointed None Not Disappointed Cronometer Somewhat Disappointed Nutrisense Very Disappointed Levels Somewhat Disappointed
Usage of other wearables vs. "satisfaction"
df_products_comp = plot_comparison()