Let's get real, any monkey with a slide deck can fake hockey stick growth. In this Heavybit Speaker Series, Sean Byrnes talks about creating metrics and analytics for actual survivability, success and growth. Sean helps you operationalize your org-wide goals, cut through the BS of pedantic goal-setting exercises, and get s@#t done. Watch the talk here - http://heavybit.com/library/video/2015-08-18-sean-byrnes

1. Business Analytics
Sean Byrnes
http://outlier.ai
sean@outlier.ai
@sbyrnes
for
Developer Services

2. Who Am I?
FOUNDED
BLOG
from Yahoo!
seanonstartups.co

3. Every line is the perfect length if
you don’t measure it.
- Marty Rubin

4. Can Do:
• Measure performance
• Inform decisions
• Expose opportunities and
challenges
Cannot Do:
• Fix your problems
• Motivate people
• Run your company
What analytics…

5. Overview
• Key Performance Indicators
• Measurement & Tracking
• Selecting Tools
• Measuring Success

6. 1 // WHERE ARE WE GOING?
KPIs

7. What are your goals?

8. Vision
Goals
KPIs

9. Key Performance Indicators
(Not progress)

10. Vision
Goals
KPIs
Allow anyone, anywhere to have a
latte when they need it by using
drone delivery.
• Reach 100 deliveries per day in SF
• Reach 20,000 paying customers
• Launch in 3 more cities
• Total deliveries per day
• Total paying customers
• Cities with active customers

11. KPIs
OKRs
What do we
need to
track?
Where do
we need to
go?

12. There can be only one.
five.

14. The 5 KPIs
Acquisition! # of first time customers per day
Engagement! # of orders per customer per day
Retention! # of users ordering 30 days later
Revenue! Average revenue per order
Cost! Total cost per delivery

15. Bad KPIs!
• Unique website visitors
• Total downloads
• Total revenue
Good KPIs!
• Total purchases
• Conversion rate
• Profit

16. 2 // NUMBERS LIE
Measurement & Tracking

18. Interpretation Bias
Collection Bias

19. Interpretation Bias
Collection Bias

20. Visits
Leads
Trial
Sales
10,000
5,000 50%
500 5%
50 0.5%

21. Visits
Leads
Sales
100,000
5,000 5%
500 0.5%
50 0.05%
Trial

22. Avoiding Collection Bias
• Don’t collect EVERYTHING
• Clearly define data you collect
• Test data collection just like a feature

23. Interpretation Bias
Collection Bias

24. 0
50,000
100,000
150,000
200,000
250,000

25. 0
50,000
100,000
150,000
200,000
250,000

26. 0
50,000
100,000
150,000
200,000
250,000

27. 0
50,000
100,000
150,000
200,000
250,000

28. Avoiding Interpretation Bias
• Form conclusions from the data, not vice versa
• Seek out independent analysis
• Triangulate trends using multiple data sources

29. 3 // DON’T BUY 200 HAMMERS
Selecting Tools

30. Types of Business Intelligence
Sales/CRM!
Descriptive!
Analytics!
Event-Based!
Analytics!
Advertising!Billing!Financial
Accounting!
Customer
Support!
Ops!

31. What do you NEED?

32. Beware taxes on success
$0.01 Per 1,000 events
10 Events per session
3 Sessions per day per user
10,000 users
$90 per month
1.5M users
$13.5k per month

33. Vision > Metrics

34. Wait, what about growth?

35. Goal 4 (1000x)
Goal 3 (100x)
Goal 2 (10x)
Goal 1 (1x)

36. Review
• Choose 5 KPIs
• Make sure your metrics are accurate
• Use only the tools you need
• Your vision is the most important

37. Sean Byrnes
sean@outlier.ai
@sbyrnes http://outlier.ai