Lean Analytics 
440 pages in 15 minutes
Ben Yoskovitz
byosko@gmail.com
@byosko
Pretty good feedback…
But you can’t please everyone…
The core of Lean is
iteration
Unfortunately,
we’re all liars.
(go ahead, admit it, it’s OK)
Everyone’s idea is the
best right?!
People love !
this part!!
(but that’s not always !
a good thing)!
This is where things
fall apart.!
No data, no learning.!
Analytics is the measurement of
movement towards business goals.
Pick one metric that matters to
your business right now.
The metric will change over time,
but right now you need to FOCUS.
A good metric is:
Understandable
If you’re busy explaining
the data, you won’t be
busy acting on it.
Comparable
Usually comparing a
metric over time. (e.g.
DAU, WAU, MAU)
Ratio or Rate
Turn your comparable
metrics into ratios. (e.g.
DAU/MAU; Signups/
Retention)
Behavior Changing
You know how you’ll
change your business
based on what the
metric tells you.
If a metric
won’t
change
how you
behave…
it’s a bad
metric.
Lean Analytics Stages
What stage are you really at?
Lean Analytics Stages
 “Gates” needed to move forward!
Empathy
Stickiness
Virality
Revenue
Scale
You’ve found a real, poorly-met need that a sizeable market
faces.
You’ve figured out how to solve the problem in a way they
will adopt, keep using (and pay for).
Your users and features fuel growth organically and
artificially.
You’ve found a sustainable, scalable business with the right
margins in a healthy ecosystem.
What stage are you really at?
Lean Analytics Stages
 “Gates” needed to move forward!
Empathy
Stickiness
Virality
Revenue
Scale
You’ve found a real, poorly-met need that a sizeable market
faces.
You’ve figured out how to solve the problem in a way they
will adopt, keep using (and pay for).
Your users and features fuel growth organically and
artificially.
You’ve found a sustainable, scalable business with the right
margins in a healthy ecosystem.
Most startups fail at this stage!
Business Models
The SaaS Customer
Lifecycle
Customer Acquisition Cost
paid
 direct
 search
 wom
 inherent virality
VISITOR
Freemium/trial offer
Enrollment
User
Disengaged User
Cancel
Freemium
churn
Engaged User
Free user
disengagement
Reactivate
Cancel
Trial abandonment rate
Invite Others
Paying Customer
Reactivation rate
Paid
conversion
FORMER USERS
User Lifetime Value
Reactivate
FORMER CUSTOMERS
Customer Lifetime Value
Viral coefficient
Viral rate
Resolution
Support data
Account Cancelled
 Billing Info Exp.
Paid Churn Rate
Tiering
Capacity Limit
Upselling
rate
 Upselling
Disengaged
 Dissatisfied
Trial Over
WineExpress A/B test
A
 B
WineExpress Results
•  41% increase in revenue per
customer! (People bought a lot
more product.)!
•  Conversion also went up, but
was secondary in importance.!
Remember the definition of
analytics?!
B
Lean Analytics Cycle
Lean Analytics Cycle
Draw a new line!
Pivot or!
give up!
Try again!
Success!!
Did we move the
needle?!
Measure the
results!
Make changes in
production!
Design a test!
Hypothesis!
With data:!
find a
commonality!
Without data:
make a good
guess!
Find a potential
improvement!
Draw a line!Pick a OMTM!
Once, a leader convinced others!
in the absence of data.!
Now, a leader knows what
questions to ask.!
Thank you
Ben Yoskovitz!
byosko@gmail.com!
@byosko!
Alistair Croll!
acroll@gmail.com!
@acroll!

Lean Analytics - Ben Yoskovitz, Co-author, Lean Analytics & VP Product, VarageSale

  • 1.
    Lean Analytics 440pages in 15 minutes Ben Yoskovitz byosko@gmail.com @byosko
  • 2.
  • 3.
    But you can’tplease everyone…
  • 4.
    The core ofLean is iteration
  • 5.
    Unfortunately, we’re all liars.
(goahead, admit it, it’s OK)
  • 6.
    Everyone’s idea isthe best right?! People love ! this part!! (but that’s not always ! a good thing)! This is where things fall apart.! No data, no learning.!
  • 7.
    Analytics is themeasurement of movement towards business goals.
  • 8.
    Pick one metricthat matters to your business right now.
  • 9.
    The metric willchange over time, but right now you need to FOCUS.
  • 10.
    A good metricis: Understandable If you’re busy explaining the data, you won’t be busy acting on it. Comparable Usually comparing a metric over time. (e.g. DAU, WAU, MAU) Ratio or Rate Turn your comparable metrics into ratios. (e.g. DAU/MAU; Signups/ Retention) Behavior Changing You know how you’ll change your business based on what the metric tells you.
  • 11.
    If a metric won’t change howyou behave… it’s a bad metric.
  • 12.
  • 13.
    What stage areyou really at? Lean Analytics Stages “Gates” needed to move forward! Empathy Stickiness Virality Revenue Scale You’ve found a real, poorly-met need that a sizeable market faces. You’ve figured out how to solve the problem in a way they will adopt, keep using (and pay for). Your users and features fuel growth organically and artificially. You’ve found a sustainable, scalable business with the right margins in a healthy ecosystem.
  • 14.
    What stage areyou really at? Lean Analytics Stages “Gates” needed to move forward! Empathy Stickiness Virality Revenue Scale You’ve found a real, poorly-met need that a sizeable market faces. You’ve figured out how to solve the problem in a way they will adopt, keep using (and pay for). Your users and features fuel growth organically and artificially. You’ve found a sustainable, scalable business with the right margins in a healthy ecosystem. Most startups fail at this stage!
  • 15.
  • 16.
    The SaaS Customer Lifecycle CustomerAcquisition Cost paid direct search wom inherent virality VISITOR Freemium/trial offer Enrollment User Disengaged User Cancel Freemium churn Engaged User Free user disengagement Reactivate Cancel Trial abandonment rate Invite Others Paying Customer Reactivation rate Paid conversion FORMER USERS User Lifetime Value Reactivate FORMER CUSTOMERS Customer Lifetime Value Viral coefficient Viral rate Resolution Support data Account Cancelled Billing Info Exp. Paid Churn Rate Tiering Capacity Limit Upselling rate Upselling Disengaged Dissatisfied Trial Over
  • 17.
  • 18.
    WineExpress Results •  41%increase in revenue per customer! (People bought a lot more product.)! •  Conversion also went up, but was secondary in importance.! Remember the definition of analytics?! B
  • 19.
  • 20.
    Lean Analytics Cycle Drawa new line! Pivot or! give up! Try again! Success!! Did we move the needle?! Measure the results! Make changes in production! Design a test! Hypothesis! With data:! find a commonality! Without data: make a good guess! Find a potential improvement! Draw a line!Pick a OMTM!
  • 21.
    Once, a leaderconvinced others! in the absence of data.!
  • 22.
    Now, a leaderknows what questions to ask.!
  • 23.