This document discusses metrics and analytics for startups. It begins by defining metrics and analytics, and explains why they are important for startups to test hypotheses and understand experimental results. It then discusses types of metrics like marketing, product, customer and pricing metrics. The document emphasizes the importance of focusing on one key metric that matters most for the business, like reducing shopping cart abandonment or improving subscription conversion rates. Finally, it notes metrics should be tailored to the specific business model, like e-commerce, SaaS, marketplaces or mobile apps.

1. Metrics that Matter
Poornima Vijayashanker
EIR @ 500 Startups
April 30, 2014
1

2. • What are metrics and analytics
• Methods of collecting metrics
• Types of metrics
• One metric that matters
Agenda
2

3. What are metrics?
3

4. A business metric is any type of
measurement used to gauge some
quantifiable component of a company’s
performance such as ROI, churn rate, etc.
“
”
4

5. “
”
Analytics is the discovery and
communication of meaningful
patterns in data.
5

6. Why do we need
analytics & metrics?
6

7. Uncertainty.
7

8. A startup is an
experiment.
8

9. Experiments needs a
hypothesis & results!
9

10. Vanity metrics.
10

11. Almost anything you read on
TechCrunch.
11

12. We send out 10M emails daily!
We received 1M likes overnight!
”“
“ ”
12

13. What are good
metrics?
13

14. 1. Comparative
2. Understandable
3. Ratio
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15. What will I do differently based on
this information?
- Lean Analytics
”
“
15

16. Total sign ups - Vanity Metric
vs.
Total active user - Actionable Metric
16

17. Qualitative vs. Quantitative
17

18. Sometimes
you have to
pick up the
phone!
18

19. KPIs: Key Performance Indicator
19

20. Leading vs. Lagging
20

21. Cohort
A/B
Multivariate
Similar groups over time.
Lots of data.
Testing all variables at once.
21

22. January February March April May
Total
Customers
1,000 2,000 3,000 4,000 5,000
Avg Revenue
Per Customer
$5.00 $4.50 $4.33 $4.25 $4.50
Figure 2-1 from Lean Analytics.
Average revenue for 5 months as we add features, and
refine product.
22

23. What is this data
telling us?
23

24. Cohort Analysis
Month of UseMonth of UseMonth of UseMonth of UseMonth of Use
Cohort 1 2 3 4 5
January $5.00 $3.00 $2.00 $1.00 $0.50
February $6.00 $4.00 $2.00 $1.00
March $7.00 $6.00 $5.00
April $8.00 $7.00
May $9.00
Averages $7.00 $5.00 $3.00 $1.00 $0.50
Figure 2-3 from Lean Analytics.
Cohort Analysis of revenue data. Horizontal axis
are cohorts (e.g. January cohort).
Spending
less
initially.
Spending
increases.
24

25. AARRR
25

26. Marketing
Metrics
Product
Metrics
Customer
Metrics
Pricing
Metrics
26

27. Marketing
Metrics
Product
Metrics
Customer
Metrics
Pricing
Metrics
27

28. website
Need to figure out appropriate metric for each.
e-mail campaigns
offline
social media
Market Channels
28

29. Possible Reach in Channel
Actual Reach
Sign Up for Trial
Active
Paying
Long Term Paying
Funnel per Channel
29

30. Marketing
Metrics
Product
Metrics
Customer
Metrics
Pricing
Metrics
30

31. Sign up for product
Try out product
Actively use product
Convert to Paid
Refer more users
Funnel for Product
31

32. Funnel depends on type of product.
32

33. Services that are used constantly but with a
specific purpose.
Daily
33

34. Frequently used products with a number of use
cases.
Daily
34

35. Less frequently used product with a specific use
case.
Yearly? Possibly monthly.
35

36. Frequency of use (engagement),
use case, and appeal impact
adoption.
36

37. What features trigger
conversions?
37

38. How can you create an
experience that will
set off those triggers?
38

39. 39

40. 1. Understand place of features in your product.
2. Look at the frequency of their usage.
3. Does one feature lead to the usage of another?
4. How might you constrain a user’s experience or provide a certain
workflow to adopt Feature X?
5. Can issues reported or enhancements requested be monetized?
40

41. Marketing
Metrics
Product
Metrics
Customer
Metrics
Pricing
Metrics
41

42. •# of customers
•Recency
•Retention Rate (churn rate)
•LTV (lifetime value)
•Customer Acquisition Costs
•Customer Profitability
•Net Promoter Score
42

43. •Prospects
•First-time Buyers
•Early Repeat Buyers
•Core Customers
•Core Defectors
43

44. One metric that matters.
44

45. • Most important question you have.
• Draw a line.
• Focuses entire company.
• Encourages a culture of experimentation & small
failures.
45

46. • How many new customers do you need?
• How many new customers per week (per
acquisition channel) do you think define a level of
success?
• Level of success being that which gets you to
the next stage.
46

47. Take a snapshot today!
Marketing & product.
47

48. $0 $1K
$5K $10K
$10K $100K
Marketing activities change.
Customer costs change.
48

49. Appendix.
49

50. • What are metrics and analytics
• Methods of collecting metrics
• Types of metrics
• One metric that matters
Review
50

51. • E-Commerce Site
• Get to shopping cart.
• Reduce abandonment!
• SaaS
• Monthly subscription
• Conversion v. cancellation rate
• Marketplace
• transaction fee
• connecting buyers & sellers
• Mobile App
• discovery
• in-app purchases
• upgrading to paid app
• Media
• engagement with content
Metrics based on business model
51