2. Percent of businesses that fail
Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 9 Year 10
71%69%66%63%60%55%50%44%36%25%
http://www.statisticbrain.com/startup-failure-by-industry/
3. Still operating after 4 years
Finance Insurance and Real Estate
Education and Health
Agriculture
Services
Wholesale
Mining
Manufacturing
Construction
Retail
Transportation Communication and Utilities
Information 37%
45%
47%
47%
49%
51%
54%
55%
56%
56%
58%
http://www.statisticbrain.com/startup-failure-by-industry/
4. Don’t sell what you can make. Make what you can sell.
Kevin Costner is a lousy entrepreneur.
7. 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.
8. Most startups don’t know what they’ll
be when they grow up.
Hotmail
was a
database
company
Flickr
was going to
be an MMO
Twitter
was a
podcasting
company
Autodesk
made
desktop
automation
Paypal
first built for
Palmpilots
Freshbooks
was invoicing
for a web
design firm
Wikipedia
was to be
written by
experts only
Mitel
was a
lawnmower
company
16. A good metric is:
Understandable
If you’re busy
explaining the
data, you won’t
be busy acting
on it.
Comparative
Comparison is
context.
A ratio or rate
The only way to
measure
change and roll
up the tension
between two
metrics (MPH)
Behavior
changing
What will you
do differently
based on the
results you
collect?
18. Metrics help you know yourself.
Acquisition
Hybrid
Loyalty
70%
of retailers
20%
of retailers
10%
of retailers
You are
just like
Customers that
buy >1x in 90d
Once
2-2.5
per year
>2.5
per year
Your customers
will buy from you
Then you are
in this mode
1-15%
15-30%
>30%
Low acquisition
cost, high checkout
Increasing return
rates, market share
Loyalty, selection,
inventory size
Focus on
(Thanks to Kevin Hillstrom for this.)
19. MayAprMarFeb
Slicing and dicing data
Jan
0
5,000
Activeusers
Cohort:
Comparison of
similar groups
along a timeline.
(this is the April cohort)
A/B test:
Changing one thing
(i.e. color) and
measuring the
result (i.e. revenue.)
Multivariate
analysis
Changing several
things at once to
see which correlates
with a result.
☀
☁
☀
☁
Segment:
Cross-sectional
comparison of all
people divided by
some attribute (age,
gender, etc.)
☀
☁
21. January February March April May
Rev/customer $5.00 $4.50 $4.33 $4.25 $4.50
Is this company
growing or stagnating?
Cohort 1 2 3 4 5
January $5 $3 $2 $1 $0.5
February $6 $4 $2 $1
March $7 $6 $5
April $8 $7
May $9
How about
this one?
22. Cohort 1 2 3 4 5
January $5 $3 $2 $1 $0.5
February $6 $4 $2 $1
March $7 $6 $5
April $8 $7
May $9
Averages $7 $5 $3 $1 $0.5
Look at the
same data
in cohorts
24. Eric’s three engines of growth
Virality
Make people
invite friends.
How many they
tell, how fast they
tell them.
Price
Spend money to
get customers.
Customers are
worth more than
they cost.
Stickiness
Keep people
coming back.
Approach
Get customers
faster than you
lose them.
Math that
matters
25. Dave’s Pirate Metrics
AARRR
Acquisition
How do your users become aware of you?
SEO, SEM, widgets, email, PR, campaigns, blogs ...
Activation
Do drive-by visitors subscribe, use, etc?
Features, design, tone, compensation, affirmation ...
Retention
Does a one-time user become engaged?
Notifications, alerts, reminders, emails, updates...
Revenue
Do you make money from user activity?
Transactions, clicks, subscriptions, DLC, analytics...
Referral
Do users promote your product?
Email, widgets, campaigns, likes, RTs, affiliates...
26. Stage
EMPATHY
I’ve found a real, poorly-met need that a
reachable market faces.
STICKINESS
I’ve figured out how to solve the problem in a
way they will keep using and pay for.
VIRALITY
I’ve found ways to get them to tell their friends,
either intrinsically or through incentives.
REVENUE
The users and features fuel growth organically
and artificially.
SCALE
I’ve found a sustainable, scalable business with
the right margins in a healthy ecosystem.
Gate
Thefivestages
27. Six business model archetypes.
E-commerce SaaS Media
Mobile
app
User-gen
content
2-sided
market
The business you’re in
28. (Which means eye
charts like these.)
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 DissatisfiedTrial Over
29. Model + Stage = One Metric That Matters.
One Metric
That Matters.
The business you’re in
E-Com SaaS Mobile 2-Sided Media UCG
Empathy
Stickiness
Virality
Revenue
Scale
Thestageyou’reat
41. Baseline:
5-7% growth a week
“A good growth rate during YC
is 5-7% a week,” he says. “If
you can hit 10% a week you're
doing exceptionally well. If you
can only manage 1%, it's a sign
you haven't yet figured out
what you're doing.” At revenue
stage, measure growth in
revenue. Before that, measure
growth in active users.
Paul Graham, Y Combinator
• Are there enough people who really care
enough to sustain a 5% growth rate?
• Don’t strive for a 5% growth at the expense
of really understanding your customers
and building a meaningful solution
• Once you’re a pre-revenue startup at or
near product/market fit, you should have
5% growth of active users each week
• Once you’re generating revenues, they
should grow at 5% a week
42. It’s oxygen
You need customers to keep learning
It’s a substitute for solvency
PhotobyPaulMilleronFlickr.https://www.flickr.com/photos/94674772@N03/8788576498
43. Baseline:
10% visitor engagement/day
Fred Wilson’s social ratios
30% of users/month use web or mobile app
10% of users/day use web or mobile app
1% of users/day use it concurrently
44. Baseline:
2-5% monthly churn
• The best SaaS get 1.5% - 3% a month. They have multiple Ph.D’s
on the job.
• Get below a 5% monthly churn rate before you know you’ve got a
business that’s ready to grow (Mark MacLeod) and around 2%
before you really step on the gas (David Skok)
• Last-ditch appeals and reactivation can have a big impact.
Facebook’s “don’t leave” reduces attrition by 7%.
45. Baseline:
Calculating customer lifetime
25%
monthly churn
100/25=4
The average
customer lasts
4 months
5%
monthly churn
100/5=20
The average
customer lasts
20 months
2%
monthly churn
100/2=50
The average
customer lasts
50 months
46. Baseline:
CAC under 1/3 of CLV
• CLV is wrong. CAC Is probably wrong, too.
• Time kills all plans: It’ll take a long time to find
out whether your churn and revenue projections
are right
• Cashflow: You’re basically “loaning” the
customer money between acquisition and CLV.
• It keeps you honest: Limiting yourself to a
CAC of only a third of your CLV will forces you
to verify costs sooner.
Lifetime of 20 mo.
$30/mo. per
customer
$600 CLV
$200 CAC
Now segment
those users!
1/3 spend
47. Who is worth more?
Today
A
Lifetime:
$200
Roberto Medri, Etsy
B
Lifetime:
$200
Visits
49. 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 linePick a KPI
50. Do AirBnB hosts
get more business
if their property is
professionally
photographed?
51. Gut instinct (hypothesis)
Professional photography helps AirBnB’s business
Candidate solution (MVP)
20 field photographers posing as employees
Measure the results
Compare photographed listings to a control group
Make a decision
Launch photography as a new feature for all hosts
55. 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 linePick a KPI
56. “Gee, those
houses that do
well look really
nice.”
Maybe it’s the
camera.
“Computer: What
do all the
highly rented
houses have in
common?”
Camera model.
With data:
find a commonality
Without data: make a
good guess
57. Landing page design A/B testing
Cohort analysis General analytics
URL shortening
Funnel analytics
Influencer Marketing
Publisher analytics
SaaS analytics
Gaming analytics
User interaction Customer satisfaction KPI dashboardsUser segmentation
User analytics Spying on users
58. When you’re a startup
your goal is to find a sustainable,
repeatable business model.
When you’re a big company
your goal is to perpetuate one.
59. In a startup, the purpose of analytics is
to iterate to product/market fit
before the money runs out.
60. In a big company,
analytics replaces opinion with fact.
64. “The most important figures that one
needs for management are unknown
or unknowable, but successful
management must nevertheless take
account of them.”
Lloyd S. Nelson
65. Pic by Twodolla on Flickr. http://www.flickr.com/photos/twodolla/3168857844