Embed Size (px)
Citation preview
Analyzing Analysts
Dustin McIntosh
Mode Analytics
Understanding the Queriers Behind the Queries
Goal: Understand user base and how they interact with the product
NovicesPower Users
● Who are the users?
● Which SQL errors do they make?
● How can we make users' experience better?
● Why do users churn?
● Can we personalize product response for different users?
Goal: Understand user base and how they interact with the product
● Who are the users?
● Which SQL errors do they make?
● How can we make users' experience better?
● Why do users churn?
● Can we personalize product response for different users?
NovicesPower Users
Time
Churn – Are users getting frustrated?
Successfulquery
SQLerror
Churn – Are users getting frustrated?
Churn – Are users getting frustrated?
No!
Churning Users = Tutorial Users
Recommendation: prompt tutorial users to connect their own data at tutorial conclusion
Can we personalize product response for different users?
Expert?
Novice?New User
Classifying Experts vs. Novices
Bag of SQL
keywords
Formatting based:
– White space
– Parentheses
Keyword diversity
Is it an Error?
Error type
Random Forest
Bag of SQL
keywords
Formatting based:
– White space
– Parentheses
Keyword diversity
Is it an Error?
Error type
Random Forest
AUC = 0.66
Classifying Experts vs. Novices
The Differences Between Experts and Novices
Summary
● Who are the users?
● Which SQL errors do they make?
● How can we make users' experience better?
● Do users churn out of frustration?
● Can we personalize product response for different users?
Expert?
Novice?
Dustin McIntosh
EFavDB.com
Extra Slides
What errors do they make?
Recommendation: prominently display or auto-correct table/column names
Top-heavy nature of SQL
Non-tutorial users also not getting frustrated
All churned users Churned users that have connected their own data
Correlations of the Features
Compare Using top 5 features
All features
Top 5 features
Histograms of important features
novicesexperts
