Talk on "Engagement and Reality" given at http://www.rstats.nyc/ 2015-04-24.

1. engagement & reality
chris.wiggins@columbia.edu
chris.wiggins@nytimes.com
@chrishwiggins
this talk: bit.ly/nyt-engagement

2. 1851 1996

3. example:
millions of views per hour2015

4. data science: the web
is your “online presence”

5. data science: the web
is a microscope

6. data science: the web
is an experimental tool

7. data science: the web
is an optimization tool

8. news: 20th century
church state

9. news: 21st century
church state
engineering

10. news: 21st century
church state
engineering

11. supervised learning, e.g.,
“the funnel”
innovation report, 2014

12. interpreting supervised learningsupercoolstuff
collaboration w/b. chen

13. interpreting supervised learningsupercoolstuff

14. optimization & learning, e.g.,
popular mechanics, 2015

15. getting to know the readers
daeil kim, cf. bit.ly/nyt-engagement

16. audiences matter

17. audiences matter
innovation report, 2014

18. R.I.P. good times
this talk: bit.ly/nyt-engagement

19. “a startup is a temporary organization in search of a
repeatable and scalable business model” —Steve Blank
this talk: bit.ly/nyt-engagement

20. every publisher is now a startup
this talk: bit.ly/nyt-engagement

21. what else is there besides clicks?

22. what else is there besides clicks?
this talk: bit.ly/nyt-engagement

23. what else is there besides clicks?
this talk: bit.ly/nyt-engagement

24. “engagement”: examples
if your biz model is clicks,
engagement=clicks
if your biz model is sharing,
engagement=sharing
if your biz model is time on page,
engagement=time on page
if your biz model is subscription…?

25. “engagement”: examples
if your biz model is clicks,
engagement=clicks
if your biz model is sharing,
engagement=sharing
if your biz model is time on page,
engagement=time on page
if your biz model is subscription…?

26. “engagement”: examples
if your biz model is clicks,
engagement=clicks
if your biz model is sharing,
engagement=sharing
if your biz model is time on page,
engagement=time on page
if your biz model is subscription…?

27. “engagement”: examples
if your biz model is clicks,
engagement=clicks
if your biz model is sharing,
engagement=sharing
if your biz model is time on page,
engagement=time on page
if your biz model is subscription…?

28. WWND?

29. WWND?
what would $NFLX do?

30. from “data scientists @ work”
-Caitlin Smallwood
VP, Science and Algorithms at Netflix
this talk: bit.ly/nyt-engagement

31. from “data scientists @ work”
-Caitlin Smallwood
VP, Science and Algorithms at Netflix
this talk: bit.ly/nyt-engagement

32. WWND?
if your biz model is subscription,
machine learning can help:
Balance predictive power for true KPI
(retention) with
1. interpretability
2. should be
• easy to measure,
• quick to measure,
• or both

33. ML can help!
“engagement” is hard to define. you choose:
1. poetry
2. philosophy
3. science
Wbinan of f2) which predicts 1)

34. ML can help!
“engagement” is hard to define. you choose:
1. poetry
2. philosophy
3. science
WE CHOSE SCIENCE:
• find 1) reality: KPI, preferably units of USD
• find 2) interpretable and observable features
• learn combination of 2) which predicts 1)

35. chris.wiggins@columbia.edu
chris.wiggins@nytimes.com
@chrishwiggins
this talk: bit.ly/nyt-engagement
ghost of science past

36. chris.wiggins@columbia.edu
chris.wiggins@nytimes.com
@chrishwiggins
this talk: bit.ly/nyt-engagement
we’re hiring!