Customer data analysis
Objective vs. "satisfaction"
All Typeform Responses
plot_most_common(most_commmon_goals)
Typeform Responses vs. Customers
plot_most_common(customer_most_common_goals)
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()