Galvanize Data Science Immersive Capstone Project Presentation - Summer 2015

1. Reddit
Churn
Analysis
Boaz Gurdin
Galvanize Data Science Immersive
August 2015

2. $ Acquisition
>
$ Retention

3. What factors predict whether a
new user will post again?

5. comments
1.7B
uncompressed
1TB

6. Pipeline
Filter'to
/r/Politics
Pivot'
comments'
to'users
Logistic'
regression
SQL

7. Features
Body of
First Comment
Responses to
First Comment
Time of
First Comment
word_count
long_post
is_response
(sentiment)
responses_total
has_long_response
has_short_response
responses_avg_word_ct
responses_ups_avg
(ups)
(has_ups)
(downs)
(has_downs)
date
time_of_day
day_of_week
day_of_year
() = Dropped due to
data quality issues

8. Features
Body of
First Comment
Responses to
First Comment
Time of
First Comment
word_count
long_post
is_response
(sentiment)
responses_total
has_long_response
has_short_response
responses_avg_word_ct
responses_ups_avg
(ups)
(has_ups)
(downs)
(has_downs)
date
time_of_day
day_of_week
day_of_year
() = Dropped due to
data quality issues
Included in
final model
=

9. Receiving a response is the strongest
predictor of commenting again
Users whose first comment in
/r/politics received at least
one response had 75% better
odds of commenting again
compared to users whose first
comment received no response
75% ꜛ
better odds of
commenting again

10. Receiving a response is the strongest
predictor of commenting again
Users whose first comment in
/r/politics received at least
one response had 75% better
odds of commenting again
compared to users whose first
comment received no response
75% ꜛ
52%'ꜛ
Response
<20 words
103%'ꜛ
Response
>20 words
better odds of
commenting again

11. Recommendation: A/B Tests
Moderators respond to
first-time commenters
Recommend active users
to respond to new users’
first comments
Product Levers
Operational Levers

12. Thanks!
Boaz Gurdin
boaz.gurdin@gmail.com
LinkedIn: BoazG
Twitter: @BoazGurdin
SlideShare: BoazGurdin
GitHub: BoazGurdin