I delivered this presentation in Dublin Web Summit in November 2014. The session aimed at helping startups to decide what and how to track. I covered why metrics matter and what every startup should measure at different stages of their lifecycle. The session also covered Analytics mistakes that startups must avoid and some Analytics best practices. Details can be found here: http://websummit.net/

1. Boost Your Growth Engine with
Analytics*
@buyukgokcesu
BoostingConversion.com
BoostingConversion.com
Cemal Buyukgokcesu
Analytics and Conversion Consultant

2. analytics

3. analyticsdigital analyticsanalytics insightsstartup analyticsdigital analyticsanalytics insights

4. analyticsdigital analyticsanalytics insights

5. analyticsdigital analyticsanalytics insightsstartup analyticsstartup analytics

6. 13%
11%
16%
60%
Entry Product view Add to basket Purchase Order status checking
Entry Product view Add to basket Purchase Order status checking
Entry Product view Add to basket Purchase Order status checking
% of product pages viewed per device

7. There are known knowns; there are things we
know we know (FACTS)
We also know there are known unknowns; that
is to say we know there are some things we do
not know (QUESTIONS)
There are also unknown unknowns; the ones
we don't know we don't know (EXPLORATION)

8. What makes a good metric for a
startup?
Comparative
A good metric should allow you to experiment, learn
and iterate with it.
Understandable Ratio or rate Actionable

9. Before choosing the right metric for
you...
Qualitative vs Quantitative
Leading vs Lagging
Correlated vs Causal
Vanity vs Actionable

12. What metrics to track?
- Metrics are “Business Type” dependent
- Metrics are “Stage of your startup’s
growth” dependent
Source: http://leananalyticsbook.com/one-metric-that-matters/

13. Pirate metrics by Dave McClure
(venture capitalist)
Source: http://www.slideshare.net/dmc500hats/startup-metrics-for-pirates-long-version

14. Empathy:
Get inside your target
market’s head and be sure
you are solving a problem
people care about in a way
someone will pay for
Lean Analytics Stages
by Alistair Croll and Benjamin Yoskovitz

15. Product/Market Fit Question
“How would you feel if you could no longer use [your
product]?”
Measure results on a scale, and define the success
Eg. At least 40% of users should say “Very disappointed”

16. Example metrics to track:
- Daily/weekly active users
- Bounce rate
- Length of time it takes someone
to become inactive
- # of inactive users that are
reactivated when sent an email
- Features users engage and
spend time with
- Features users ignore
Stickiness comes from a good
product
- Don’t look for rapid growth
- Focus is around retention
and engagement metrics
- Segment metrics by cohort

17. A segment is a group
that shares some
common characteristics
eg.
Visitors using firefox
browser have
significantly fewer
engagement

18. Total Users Average
Churn Rate
January 1.000 24%
February 2.000 23%
March 3.000 23%
April 4.000 21%
May 5.000 18%
Average Churn Rate
of Cohort Users
18%
17%
16%
13%
8%
Cohort Analysis compares similar
groups over time

19. We are all
delusional
Virality: Focus on user
acquisition and growth
- but keep an eye on your
stickiness too

20. NPS = % Promoters - % Detractors
One question survey:
“How likely is it you would recommend my
product to a friend or colleague?”

21. Some examples of leading indicators
of engaged users
Facebook: User reaching 7 friends
within 10 days of signing up
Zynga: Day 1 retention - if someone
comes back a day after signing up for
a game
Source: http://www.richardprice.io/post/34652740246/growth-hacking-leading-indicators-of-engaged-users

22. Some examples of leading indicators
of engaged users
Dropbox: When users put at least one file in
one Dropbox folder on one device
Twitter: Following a certain number of people,
and a certain percentage of those people
following the user back
LinkedIn: User getting to X connections in Y
days
Source: http://www.richardprice.io/post/34652740246/growth-hacking-leading-indicators-of-engaged-users

23. Example metrics to track:
- Customer lifetime value
- Revenue per customer
- Click-through Rate
- Conversion rate
- Cart size
- Checkout abandonment rate
- Customer acquisition cost
- Months to customer breakeven
- Cancellation rate

24. Source: http://www.kaushik.net/avinash/best-web-metrics-kpis-small-medium-large-business/

25. Cancellation rate
=
Percentage number of customers
who cancel in any given month
compared to total (paying)
customers

26. # months = 1 / cancellation rate
LTV = monthly revenue / cancellation rate
Customer lifetime value (LTV)
=
Monthly revenue
x
# months in lifetime

27. If user’s monthly revenue €20 a month
and cancellation rate is 10% a month
LTV = monthly revenue / cancellation rate
LTV = €20 / 10% = €200
Remember:
Short term cancellation rates are much higher than long term

28. Time to customer breakeven:
How long a customer takes to pay
you back?
$27 Customer lifetime value
11 Months from activation to departure
$2.45 Average revenue per customer per month
$14 Cost to acquire a customer
5.7 Months to customer breakeven

29. Find the
One Metric That
Matters
Pick a single metric
that’s incredibly
important for the
step you’re currently
working through in
your startup
Source: http://www.kaushik.net/avinash/lean-analytics-cycle-metrics-hypothesis-experiment-act/

32. Purpose of analytics
To find your way to the right product and market before the money
runs out
A good metric
A good metric is comparative, understandable, ratio or rate,
actionable
Segments, cohorts, tests
Use segments, analyze cohorts, make testing part of your DNA
Before deciding on metrics to track
Confirm your “Business Type” and “Stage of your startup’s growth”
Focus on one metric
Find your One Metric That Matters

33. Thanks!
@buyukgokcesu
BoostingConversion.com
BoostingConversion.com
Cemal Buyukgokcesu
Analytics and Conversion Consultant