A high level discussion of web analytics.

1. Analytics for
Developers
and Developing for Analytics

2. About Me
2006-2011: Educated Accounting & Finance
2011-Present: Reeducated Marketing & Operations
Twitter: @trent_hauck
Work: @AlightAnalytics
Other:
Contribute (now and then) to Pandas
& StatsModels

3. Two Parts
Analytics(more)
Development
(less)

4. Why should you care?

5. “In God we
trust; all
others must
bring data.”

6. To do analytics you
need x

7. Where x
is data collection...

8. Site Analytics Should
be a 1st Class Citizen
of Development

9. Collect More Than
You Need Now

10. Now Some GA Code
<script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-31465642-1']);
_gaq.push(['_setDomainName', 'trenthauck.com']);
_gaq.push(['_setAllowLinker', true]);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') +
'.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
})();
</script>

11. Next Steps
Events
_gaq.push(['_trackEvent', 'Cat', 'Act', ‘Label’]);
Custom Variables
_gaq.push(['_setCustomVar', 1, ‘key’, ‘value’, 1])

12. Where x
is data analysis...

13. Differences in Data
Small Data == Math Problem
Big Data == Engineering Problem

14. The Math Problem

15. Descriptive Stats
(please compute these)
Max, Min
Quartiles
Mean
Variance
Mode

16. Web Stats are Easy
A user converts or not... what
are the changes of that?
p or q (=1-p)
3 users convert or not... what are
the changes of that?
p^3 or (p^2)q or p(q^2) or q^3

17. Hypothetical Worlds
Trials = 100, Size = 100, p = .1

18. Back to real world
Stats: p-bar = .08, SE = 0.027

19. So then AB Testing
500 Trials A B
p 0.1 0.2
SE 0.01 0.01
95% CI .1 +/- .02 .2 +/- 0.02

20. The Engineering
Problem

21. Build Data Pipelines
• Repeatable Flows of Data
• Handles Initial Analysis For You
• Literate Programming

22. Programming For
Data Analysis
• Scripting good for Discovery
• Larger Jobs need Types
• Mapping high dimensional space to
lower dimensional space... then add

23. Where x
is visualization....

24. Visualization Types
•Distributions
•Comparisons
•Time Series
•Other (Match Domain)

25. Distributions
Single Variable: Histograms
Multiple Variables: Scatter plot

26. Comparisons
Categorical Variables

27. TimeSeries
X Axis is Time

28. Match Domain with
Analysis

29. Where x
is storytelling...

30. Storytelling

31. 3 Temporal Stages
1. What happened
2. What is happening
3. What will happen
(Plus a tease)

32. Start With the
Simple Stuff
Friday Saturday Sunday
40º 42º
(Why do I live
in KC)º

33. Build Up to
Complex Idea

34. Thanks...
Questions?