Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference

L
Lean AnalyticsStartup accelerator
Lean Analytics 
Lean Startup Conference 
December, 2015 
@acroll
Some housekeeping.
Kevin Costner is a lousy entrepreneur. 
Don’t sell what you can make. Make what you can sell.
The core of Lean 
is iteration.
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
Waterfall, agile, and lean 
(Why the old ways don’t work.)
Waterfall approach 
You know the problem and the solution.
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Known set of 
requirements 
Known ways to satisfy 
them 
Spec Build Test Launch
Agile methodologies 
Know the problem, find the solution
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Known set of 
requirements 
Unclear how to satisfy 
them 
Problem Build Test Viable? Launch 
statement 
Sprints 
Adjust 
Unknown set of
Lean approach 
First, know that you don’t know.
Product/market 
hypothesis Trial startup 
Possible problem 
space 
Product/ 
market 
hypothesis 
Trial startup 
Product/ 
market 
hypothesis 
Trial startup 
Trial startup 
Product/market 
hypothesis 
You are 
here 
PIVOT
Why now? 
First: High rate of change of digital 
technologies & channels.
Arbitron and radio data
Times a song in “heavy 
rotation” is played daily 
30 
15 
0 
6 26 
2007 2012
For modern media this means 
cycle time shock. 
Circulation, annually Clicks, instantaneously 
Letters to the editor, weekly Hashtags, always
Why now? 
Second: It’s no longer about whether 
you can build it—it’s about whether 
anyone will care.
The Attention Economy 
“What information consumes 
is rather obvious: it consumes 
the attention of its recipients. 
Hence a wealth of information 
creates a poverty of attention, and a 
need to allocate that attention efficiently 
among the overabundance of 
information sources that might 
consume it.” 
(Computers, Communications and the Public Interest, pages 40-41, 
Herbert Simon Martin Greenberger, ed., The Johns Hopkins Press, 1971.)
Lit motors tests the risky part
Unfortunately, 
we’re all liars.
Everyone’s idea is 
the best right? 
People love 
this part! 
(but that’s not always 
a good thing) 
No data, no 
learning. 
This is where 
things fall apart.
Analytics can help.
Analytics is the measurement of 
movement towards your business 
goals.
In a startup, the purpose of analytics is 
to iterate to product/market fit 
before the money runs out.
I have two kids. 
At least one of them is a girl.
What are the chances 
the other is a boy?
BB BG 
GB GG
2 of 3 (66%) are boys. 
GB GG BG
Some fundamentals. 
Analytics, performance, aggregation, and the right metrics
Fundamental: 
Web analytics and the long funnel. 
(This is not a web analytics workshop.)
A simplistic view of web analytics 
ATTENTION ENGAGEMENT CONVERSION 
NEW 
VISITORS 
GROWTH 
LOSS 
BOUNCE 
RATE 
CONVERSION 
RATE 
x TIME 
GOAL 
VALUE 
ON 
SITE 
PAGES 
PER 
VISIT 
NUMBER 
OF VISITS 
SEARCHES 
TWEETS 
MENTIONS 
ADS SEEN
Visits 
Shopping cart 
Payment options 
Conversions
Visits 
Shopping cart 
Payment options 
Conversions 
KPIs 
Bounce 
Conversion
Unpaid search Community mentions 
Visits 
Shopping cart 
Payment options 
Conversions 
Email campaign Banner ad 
•Google PageRank 
•Sessions-to-clicks 
ratio 
•Cost of ads 
(CPM) 
•Clickthrough 
rate 
? •Open rate 
•Opt-out rate
Repurposing 
(spread to other 
communities) 
Amplification 
(virality and 
message spread) 
Seed (starting 
community) 
Reach 
(impressions) 
Visits 
Shopping cart 
Payment options 
Conversions
Viral message spread 
Reach 
(impressions) 
Visits 
Shopping cart 
Payment options 
Conversions 
Emphasis on getting 
viral ratio above 1 
(Retweeting, Fan, Email 
forward, Reddit upvote, 
other loops)
Megablogger proponents 
Seed (starting 
community) 
Reach 
(impressions) 
Visits 
Shopping cart 
Payment options 
Conversions 
Emphasis on 
convincing highly-followed, 
highly acted-upon 
seed group to 
spread the word.
A call to action 
Reach 
(impressions) 
Visits 
Shopping cart 
Payment options 
Conversions 
Emphasis on 
maximizing 
impression-to-click 
ratio within 
the community
Long funnel: Beers for Canada 
700,000s 
1,642 
150 
RT 
32 
7 
10 
15 
x $100 
x $20 
x $7 
Seed ratio: 20 
35,000:1 
Followers 
Visitors: 
0.23% 
Conversions: 
1.95% 
2 Repurposing 
Amplification: 2.9% 
Revenues: 
Average: $39.54 
Median: $20 
Total: $1,005 
2,000
Fundamental: 
You should care about performance.
Downtime costs 
Amazon offline ($1M/h) 
Amazon loses nearly $1M/hour if down (NYT, 2008) 
1 hour of network downtime costs $42,000 (Gartner, 2003) 
Network downtime ($42K/h) 
22h outage at eBay cost $2M ($90,909/h) (Internetnews, 1999) 
eBay offline ($90K/h) 
Financial company down ($100K/h) 
53.2% of finance companies lose over $100,000/hour (nextslm.org) 
Let’s say $50K/h if you’re serious.
Availability % Downtime/year Loss @$50K/h 
90% 36.5 days $43,800,000 
95% 18.25 days $21,900,000 
98% 7.30 days $8,760,000 
99% 3.65 days $4,380,000 
99.5% 1.83 days $2,196,000 
99.8% 17.52 hours $876,000 
99.9% 8.76 hours $438,000 
99.95% 4.38 hours $219,000 
99.99% 52.6 minutes $43,833 
99.999% 5.26 minutes $4,383 
99.9999% 31.5 seconds $438 
Less than 1h/ 
year 
Less than a 
minute/year
You really don’t want web users to call 
you. 
US$12 
US$10 
US$7 
US$5 
US$2 
US$0 
$5.50 
$3.00 
$0.24 $0.45 
Web self-service IVR Email Live phone 
Low Average High 
BiT Group White Paper: “Web Self-Service Lowers Call Center Costs and 
Improves Customer Service” 
Cost estimates
The login page Function 
will have a total latency Metric 
of under 4 seconds Target 
with a cached browser copy User situation 
from any US branch office Testing point 
95% of the time Percentile 
weekdays, 8AM ET to 6M PST Time window 
by synth test at 5m intervals Collection type
10% 
visitors 
7.5% 
of 5% 
Percent 2.5% 
0% 
0-2s 2-4s 4-6s 6-8s 8s + 
Average page load time across visit that commented on a post
Fundamental: 
What makes a good metric?
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?
The 
simplest 
rule 
If a metric won’t change how 
you behave, it’s a 
bad 
metric. 
h"p://www.flickr.com/photos/circasassy/7858155676/
Metrics help you know yourself. 
Acquisition 
Hybrid 
Loyalty 
You are 
just like 
70% 
of retailers 
20% 
of retailers 
10% 
of retailers 
Customers that 
buy >1x in 90d 
Your customers 
will buy from you 
Once 
2-2.5 
per year 
>2.5 
per year 
Then you are 
in this mode 
1-15% 
15-30% 
>30% 
Focus on 
Low acquisition 
cost, high checkout 
Increasing return 
rates, market share 
Loyalty, selection, 
inventory size 
(Thanks to Kevin Hillstrom for this.)
Qualitative 
Unstructured, anecdotal, 
revealing, hard to 
aggregate, often too 
positive & reassuring. 
Warm and fuzzy. 
Quantitative 
Numbers and stats. 
Hard facts, less insight, 
easier to analyze; often 
sour and disappointing. 
Cold and hard.
Exploratory 
Speculative. Tries to find 
unexpected or 
interesting insights. 
Source of unfair 
advantages. 
Cool. 
Reporting 
Predictable. Keeps you 
abreast of the normal, 
day-to-day operations. 
Can be managed by 
exception. 
Necessary.
Rumsfeld on Analytics 
Things we 
know 
don’t 
know 
(Or rather, Avinash Kaushik channeling Rumsfeld) 
we know Are facts which may be wrong and 
should be checked against data. 
we don’t 
know 
Are questions we can answer by 
reporting, which we should baseline 
& automate. 
we know 
Are intuition which we should 
quantify and teach to improve 
effectiveness, efficiency. 
we don’t 
know 
Are exploration which is where 
unfair advantage and interesting 
epiphanies live.
Slicing and dicing data 
Feb Mar Apr May 
5,000 
Active users 
0 
Jan 
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.) 
☀ 
☁
Which of these two companies 
is doing better?
January February March April May 
Is this company Rev/customer $5.00 $4.50 $4.33 $4.25 $4.50 
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?
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
Lagging 
Historical. Shows you 
how you’re doing; 
reports the news. 
Example: sales. 
Explaining the 
past. 
Leading 
Forward-looking. 
Number today that 
predicts tomorrow; 
reports the news. 
Example: pipeline. 
Predicting the 
future.
Some examples 
A Facebook user reaching 7 friends within 10 days of signing up 
(Chamath Palihapitiya) 
If someone comes back to Zynga a day after signing up for a game, 
they’ll probably become an engaged, paying user (Nabeel Hyatt) 
A Dropbox user who puts at least one file in one folder on one device 
(ChenLi Wang) 
Twitter user following a certain number of people, and a certain 
percentage of those people following the user back (Josh Elman) 
A LinkedIn user getting to X connections in Y days (Elliot Schmukler) 
(From the 2012 Growth Hacking conference. http://growthhackersconference.com/)
Which means it’s time to talk 
about correlation.
10000 
1000 
100 
10 
1 
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec 
Ice cream consumption Drownings
Correlated 
Two variables that are 
related (but may be 
dependent on 
something else.) 
Ice cream & 
drowning. 
Causal 
An independent variable 
that directly impacts a 
dependent one. 
Summertime & 
drowning.
A leading, causal metric 
is a superpower. 
h"p://www.flickr.com/photos/bloke_with_camera/401812833/sizes/o/in/photostream/
Why is Nigerian spam so badly 
written?
Experienced scammers expect a “strike rate” of 1 or 2 replies per 1,000 messages 
emailed; they expect to land 2 or 3 “Mugu” (fools) each week. 
One scammer boasted “When you get a reply it’s 70% sure you’ll get the money” 
“By sending an email that repels all but the most gullible,” says [Microsoft Researcher 
Corman] Herley, “the scammer gets the most promising marks to self-select, and tilts 
the true to false positive ratio in his favor.” 
This would be horribly 
inefficient since 
humans are involved. 
Good language (10% conversion) 
Not-gullible (.07% conversion) 
Aunshul Rege of Rutgers University, USA in 2009 
1000 emails 
Bad language (0.1% conversion) 
1-2 responses 
Gullible (70% conversion) 
1 fool and their money, parted. 
1000 emails 
100 responses 
1 fool and their money, parted.
Turns out the word “Nigeria” is the best 
way to identify promising prospects.
Nigerian spammers 
really understand their target market. 
They see past vanity metrics.
Fundamental: 
Be careful rolling things up.
http://upload.wikimedia.org/wikipedia/commons/0/0e/Count-von-count.jpg
0 10 20 30 40 50 60 70 80 90 
Age 
20 
Count 
0 
Average age = 10
200 
0 2 4 6 8 10 12 14 16 18 
Page load time (in seconds) 
# of requests 
0 
20 
Average latency = 5s 
95th percentile latency = 19s
KISS
“It can scarcely be denied 
that the supreme goal of all theory is 
to make the irreducible basic elements 
as simple and as few as possible without 
having to surrender the adequate 
representation of a single datum of 
experience.” 
http://media.photobucket.com/image/einstein/derekabril/einstein_010.png
“As simple as possible, 
but no simpler.” 
*(FYI, this is irony.)
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Login 
Checkout 
Invite
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Login 
Checkout 
Invite 
Average 4s 
Average 6s 
Average 9s
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Login 
Checkout 
Invite 
Average 
95% 
4s 
8s 
Average 
95% 
6s 
10s 
Average 
95% 
9s 
12s
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Login 
Checkout 
Invite 
Average 
95% 
Mode 
4s 
8s 
2s 
Average 
95% 
Mode 
6s 
10s 
5s 
Average 
95% 
Mode 
9s 
12s 
1s
Login 
Checkout 
Invite 
Aggregate? 
Average 
95% 
Mode 
4s 
8s 
2s 
Average 
95% 
Mode 
6s 
10s 
5s 
Average 
95% 
Mode 
9s 
12s 
1s 
Average 
95% 
Mode 
6s 
12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 5s
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Login: 
<=4s 
740 260
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Total samples 1000 
Below threshold 740 
Login: 
<=4s Percent below 
target threshold 74% 
740 260
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Login: 
<=4s 
Checkout: 
<=5s 
Invite: 
<=8s 
Total samples 1000 
Below threshold 740 
Percent below 
target threshold 74% 
Total samples 1000 
Below threshold 370 
Percent below 
target threshold 37% 
Total samples 1000 
Below threshold 610 
Percent below 
target threshold 61% 
740 260 
370 630 
610 390
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Login: 
<=4s 
Checkout: 
<=5s 
Invite: 
<=8s 
Aggregate? 
Total samples 1000 
Below threshold 740 
Percent below 
target threshold 74% 
Total samples 1000 
Below threshold 370 
Percent below 
target threshold 37% 
Total samples 1000 
Below threshold 610 
Percent below 
target threshold 61% 
740 260 
370 630 
610 390 
Total samples 3000 
Below threshold 1720 
Percent below 
target threshold 57%
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Login: 
<=4s 
Checkout: 
<=5s 
Invite: 
<=8s 
Total samples 1000 
Below threshold 740 
Percent below 
target threshold 74% 
Total samples 400 
Below threshold 148 
Percent below 
target threshold 37% 
Total samples 600 
Below threshold 366 
Percent below 
target threshold 61% 
740 260 
370 630 
610 390 
Total samples 2000 
Below threshold 1254 
Percent below 
target threshold 63% 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Weight 1 
Weight 5 
Weight 2 
Login: 
<=4s 
Checkout: 
<=5s 
Invite: 
<=8s 
Total samples 1000 
Below threshold 740 
Total samples 400 
Below threshold 148 
Total samples 600 
Below threshold 366 
740 260 
370 630 
610 390
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
Total requests 
inside target 
Login page 740/1000 
Checkout page 148/400 
Invite process 366/600
Total requests 
inside target 
Login page 740/1000 
Checkout page 148/400 
Invite process 366/600 
Weight 
1 
52 
Weighted 
740/1000 
740/2000 
732/1200 
2212/4200 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s
Total requests 
inside target 
Login page 740/1000 
Checkout page 148/400 
Invite process 366/600 
Weight 
1 
52 
Weighted 
740/1000 
740/2000 
732/1200 
Total score 2212/4200 
53% 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s 
1s 2s 3s 4s 5s 6s 7s 8s 9s 10s 11s 12s
The Lean Analytics framework.
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
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...
Gate 
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. 
The five stages
Empathy stage: 
Localmind hacks Twitter 
Needed to find out if a core assumption—strangers answering 
questions—was valid. 
Ran Twitter experiment instead of writing code 
Asked senders of geolocated Tweets from Times Square random 
questions; counted response rate 
Conclusion: high enough to proceed
LikeBright’s mechanical turk 
Used Mechanical Turk, Google Voice to speak w/ 
100 single women; paid $2. The interviews 
lasted typically around 10-15 minutes. 
Simple interview script with open-ended 
questions, since he was digging into the problem 
validation stage of his startup. 
Founder Nick Soman: “I was amazed at the 
feedback I got. We were able to speak with one 
hundred single women that met our criteria in 
four hours on one evening.” 
Went back to TechStars and got accepted. 
LikeBright’s website is now live with a 50% 
female user base, and recently raised a round of 
funding. 
“Since that first foray into interviewing customers, 
I’ve probably spoken with over a thousand 
people through Mechanical Turk,”
How to avoid leading the witness 
Avoid biased wording, preconceptions, or 
a giveaway appearance. Word your 
surveys carefully to be neutral. 
Get them to purchase. Ask them to pay. Demand real 
introductions. Or ask them “how many of your friends would say 
Ask “why” several times. Leave lingering, uncomfortable pauses 
in the conversation and let them fill them. 
Don’t tip your hand 
Make the question real 
Keep digging 
Look for other clues Have a colleague make notes of when they react, or of their body 
language.
Stickiness stage: 
qidiq streamlines invites 
Survey owner adds recipient to group 
Survey owner asks question 
Recipient reads survey question 
Recipient responds to question 
Recipient sees survey results 
(Later, if needed…) 
Recipient visits site; no password! 
Recipient does password recovery 
One-time link sent to email 
Recipient creates password 
Recipient can edit profile, etc. 
Survey owner adds recipient to group 
Survey owner asks question 
Recipient gets invite 
Recipient installs mobile app 
Recipient creates account, profile 
Recipient can edit profile, etc. 
Recipient reads survey question 
Recipient responds to question 
Recipient sees survey results 
10-25% RESPONSE RATE 
70-90% RESPONSE RATE
1200 
1000 
800 
600 
400 
200 
0 
January February 
1 2 3 4 5 6 7 8 9 
Days since last engagement 
25000 
20000 
15000 
10000 
5000 
0 
Disengaged 
(>10 days) 
Number of users 
A better approach to engagement 
This is a 
good thing.
Virality stage: Timehop focuses 
on content sharing 
Focused on percent of daily active users that share their content 
Aiming for 20-30% of DAU sharing 
“All that matters now is virality. Everything else—be 
it press, publicity stunts or something else—is like 
pushing a rock up a mountain: it will never scale. 
But being viral will.” 
- Jonathan Wegener, co-founder
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Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
v ≠ 1, pt = δp0 (1 – vt+1) / (1 – v) + p0 
http://robert.zubek.net/blog/2008/01/30/viral-coefficient-calculation/ 
Viral coefficient
Or simpler 
x - > 1 
Users Viral 
coefficient 
Churn & 
abandonment
How to calculate it 
First calculate the invitation rate, 
which is the number of invites 
sent divided by the number of 
users you have. 
Then calculate the acceptance 
rate, which is the number of 
signups or enrollments divided by 
the number of invites. 
Then multiply the two together. 
Your 2,000 customers have sent 
out 5,000 invitations during their 
lifetime on your site. 
Your invitation rate is 2.5. 
For every ten invitations received, 
one gets clicked. 
Your acceptance rate is 0.1. 
Multiply the two, and you have 
your viral coefficient: 0.25. Every 
customer you add will add an 
addition 25% of a customer.
Revenue stage: Backupify’s 
Customer Acquisition Payback 
Initially focused on site visitors 
Then focused on trials 
Then switched to signups 
Today, MRR 
In early 2010, CAC was $243 and ARPU was only $39 
Pivoted to target business users 
CLV-to-CAC today is 5-6x 
Now they track Customer Acquisition Payback 
Target is less than 12 months
Scale stage: 
Incremental order cost 
Marginal costs 
Fixed costs
Six business model archetypes. 
E-commerce SaaS Mobile Media 
app 
User-gen 
content 
2-sided 
market 
The business you’re in
(Which means eye 
charts like these.) 
Customer Acquisition Cost 
paid direct search wom inherent 
virality 
VISITOR 
Freemium/trial offer 
Enrollment 
User 
Disengaged User 
Freemium 
churn 
Cancel 
Engaged User 
Free user 
disengagement 
Reactivate 
Trial abandonment 
Cancel 
rate 
Invite Others 
Upselling 
rate Upselling 
Paying Customer 
Reactivation 
rate 
Paid 
conversion 
FORMER USERS 
User Lifetime Value 
Reactivate 
Capacity Limit 
Support data 
FORMER CUSTOMERS 
Customer Lifetime Value 
Viral coefficient 
Viral rate 
Resolution 
Account Cancelled Billing Info Exp. 
Paid Churn Rate 
Tiering 
Trial Over Disengaged Dissatisfied
Model + Stage = One Metric That Matters. 
The business you’re in 
E-Com SaaS Mobile 2-Sided Media UCG 
One Metric 
That Matters. 
Empathy 
Stickiness 
Virality 
Revenue 
Scale 
The stage you’re at
Really? Just one?
Yes, one.
In a startup, focus is hard to achieve.
Having only one metric 
addresses this problem.
www.theeastsiderla.com
Moz cuts down on metrics 
SaaS-based SEO toolkit in the scale stage. Focused on net adds. 
Was a marketing campaign successful? 
Were customer complaints lowered? 
Was a product upgrade valuable? 
Net adds up: 
Can we acquire more valuable customers? 
What product features can increase engagement? 
Can we improve customer support? 
Net adds flat: 
Are the new customers not the right segment? 
Did a marketing campaign fail? 
Did a product upgrade fail somehow? 
Is customer support falling apart? 
Net adds down:
Metrics are like squeeze toys. 
http://www.flickr.com/photos/connortarter/4791605202/
Empathy 
Stickiness 
Virality 
Revenue 
Scale 
E-commerce 
Mobile 
app 
User-gen 
content 
SaaS Media 
2-sided 
market 
Interviews; qualitative results; quantitative scoring; surveys 
Loyalty, 
conversion 
CAC, shares, 
reactivation 
(Money from transactions) 
Transaction, 
CLV 
Affiliates, 
white-label 
Engagement, 
churn 
Inherent 
virality, CAC 
(Money from active users) 
Upselling, 
CAC, CLV 
API, magic #, 
mktplace 
Content, 
spam 
Invites, 
sharing 
(Money from ad clicks) 
Ads, 
donations 
Analytics, 
user data 
Inventory, 
listings 
SEM, sharing 
Transactions, 
commission 
Other 
verticals 
Downloads, 
churn, virality 
WoM, app 
ratings, CAC 
CLV, 
ARPDAU 
Spinoffs, 
publishers 
Traffic, visits, 
returns 
Content 
virality, SEM 
CPE, affiliate 
%, eyeballs 
Syndication, 
licenses
Better: bit.ly/BigLeanTable
Drawing some lines in the sand.
A company loses a quarter of its 
customers every year. 
Is this good or bad?
Not knowing what normal is 
makes you do stupid things.
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
Baseline: 
10% visitor engagement/day 
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 
Fred Wilson’s social ratios
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%.
Baseline: 
Calculating customer lifetime 
25% 
5% 
monthly churn 
monthly churn 
100/25=4 
100/5=20 
The average 
The average 
customer lasts 
customer lasts 
4 months 
20 months 
2% 
monthly churn 
100/2=50 
The average 
customer lasts 
50 months
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 
1/3 spend 
$200 CAC 
Now segment 
those users!
Who is worth more? 
A Lifetime: 
B Lifetime: 
Today 
$200 
$200 
Roberto Medri, Etsy 
Visits
Baseline: 
35% of mobile users engaged by day 90 
Day one 
Day 30 
Day 60 
100% 
54% 
43% 
Day 90 
35% 
October, 2012 study of 200,000 apps by Flurry 
In recent years, third-month engagement has increased 
from 25% to 35%, but frequency of use has dropped from 
6.7 uses a week to 3.7 a week. 
Smartphone Tablet 
Uses per week 12.9 times 9.5 times 
Duration of use 4.1m 8.2m
(Varies widely by 
product category)
Etsy 
• Online store for creative types, founded 2005 
• $525M Gross Merchandise Sales in 2011, with 
19,000,000 members and 800,000 active 
shops offering 15,000,000 items for sale 
• 1.4B pageviews per month ~2M iPhone app 
downloads 
• Thin revenues: Etsy makes only $0.20 or 3.5% 
margin 
• Heavy focus on Customer Lifetime Value (buyer 
and seller) 
• Actually residual lifetime value; they take this 
pretty seriously.
Etsy 
• The best customers to target are 
• Recent high-profile customers 
• Old-time best customers about to 
churn or just churned 
• Tiered campaigns 
• Bronze/silver customers: reinforcement, 
nudges 
• Gold customers: premium services 
• Platinum customers: recognition 
• What they watch: 
• Growth of individual product categories 
• Time to first sale by a user 
• Average order value 
• Percentage of visits that convert to a 
sale 
• Percentage of return buyers 
• Distinct sellers within a product 
category 
• Time-to-first-sale and average order 
value by product category 
Roberto Medri, Etsy
DuProprio/Comfree 
• Large for-sale-by-owner marketplace 
• Founded in 1997, 17,000 properties and 5M visits a month 
• $900 per listing, plus value-added tools & services 
• Leading goal is to create subscriptions 
• Launched seller-side logins; then client accounts 
• Rule of thumb: 1,000 visits equals 1 subscription 
• Three business objectives: 
• Convince sellers to list their property on the site; 
• Convince buyers to register for property match notifications; 
• Sell the properties. 
KPI evolution 
Static traffic 
Visitor to listing ratio 
List-to-sold ratio 
Click-throughs, search 
results
YPG 
• Large directory publishing & local marketing w/420K customers, 
2,500 employees, and $1,2B/y in revenue 
• Focus on public API for listings (1.5M geo-coded listings for 
location apps) 
• Initially slow to embrace API, but in 2013 have tripled investment 
• Lets the company find a partner or developer and have a 
functional prototype in hours, testing in days, and launching in 
weeks. 
KPI evolution 
Soft: Signups, SDK, 
downloads 
App usage, deals 
signed 
API calls generated 
API-generated revenue
The Lean Analytics cycle
Pick a KPI Draw a line 
Draw a new line 
Pivot or 
give up 
Try again 
Success! 
Did we move the 
needle? 
Measure 
the results 
Design a test 
Make changes 
in production 
Find a potential 
improvement 
With data: 
find a 
commonality 
Without data: 
make a good 
guess 
Hypothesis
Do AirBnB hosts 
get more business 
if their property is 
professionally 
photographed?
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
5,000 shoots per month 
by February 2012
Hang on a second.
SRSLY? 
Gut instinct (hypothesis) 
Professional photography helps AirBnB’s business
Pick a KPI Draw a line 
Draw a new line 
Pivot or 
give up 
Try again 
Success! 
Did we move the 
needle? 
Measure 
the results 
Design a test 
Make changes 
in production 
Find a potential 
improvement 
With data: 
find a 
commonality 
Without data: 
make a good 
guess 
Hypothesis
“Gee, those 
houses that do 
well look really 
nice.” 
Maybe it’s the 
camera. 
With data: 
find a commonality 
“Computer: What 
do all the 
highly rented 
houses have in 
common?” 
Camera model. 
Without data: make a 
good guess
Circle of Moms: Not enough engagement 
• Too few people were 
actually using the 
product 
• Less than 20% of any 
circles had any activity 
after their initial creation 
• A few million monthly 
uniques from 10M 
registered users, but no 
sustained traction 
• They found moms were far more engaged 
• Their messages to one another were on average 50% longer 
• They were 115% more likely to attach a picture to a post they wrote 
• They were 110% more likely to engage in a threaded (i.e. deep) 
conversation 
• Circle owners’ friends were 50% more likely to engage with the circle 
• They were 75% more likely to click on Facebook notifications 
• They were 180% more likely to click on Facebook news feed items 
• They were 60% more likely to accept invitations to the app 
• Pivoted to the new market, including a name change 
• By late 2009, 4.5M users and strong engagement 
• Sold to Sugar, inc. in early 2012
Landing page design A/B testing 
Cohort analysis General analytics 
URL shortening 
Funnel analytics 
Influencer Marketing 
Publisher analytics 
SaaS analytics 
Gaming analytics 
User analytics Spying on users 
User interaction Customer User segmentation satisfaction KPI dashboards
Consider a media company
Valuable, hard 
Paid revenue 
sources 
Word of mouth; 
public support 
Why clickbait is 
on its way out 
Simple to count 
Icky, easy 
What do you 
want visitors to 
do? 
The changing face of 
engagement 
Ignore 
Back away 
Bounce 
One-time 
Lurk 
Stay silent 
Hoard 
Criticise 
Take 
Abandon 
Cancel 
Upgrade 
Renew 
Subscribe 
Create 
Endorse 
Share 
Respond 
Interact 
Explore 
Stay 
See 
Click Downgrade
The tools media can use 
Editorial decisions 
Pagerank/reputation 
Followers/subscribers 
Topic chosen 
Format (quiz, story, etc.) 
Tone (controversy, etc.) 
Headline, imagery 
Timing, platform 
Long-term, sustainable 
Short-term, transient
Modern media’s 
new gauntlet 
Click 
See 
Stay 
Explore 
Interact 
Respond 
Share 
Endorse 
Create 
Subscribe 
Renew 
Upgrade 
Editorial decisions 
Pagerank/reputation 
Followers/subscribers 
Topic chosen 
Format (quiz, story, etc.) 
Tone (controversy, etc.) 
Headline, imagery 
Timing, platform 
From here 
(cats and 
royalty) 
To here 
(an informed 
electorate and 
citizen approval)
Some non-tech examples.
I lied. Everyone is a tech company.
Cost of experiments: down. Cost of attention: way up. 
http://www.flickr.com/photos/puuikibeach/4789015423 http://www.flickr.com/photos/elcapitanbsc/3936927326
Let’s pick on restaurants 
for a while.
Empathy: find the need 
Before opening, the owner first learns about the diners in her 
area, their desires, what foods aren’t available, and trends in 
eating. 
Key metrics: Popular items; 
frequent questions; before/after 
dining patterns. 
Reference: Emerging need.
Stickiness: confirm the need is met. 
She develops a menu and tests it out with consumers, 
making frequent adjustments until tables are full and patrons 
return regularly. She’s giving things away, asking diners what 
they think. Variance and uncertain inventory make costs high. 
Key metrics: Customer loyalty; 
recommendations; referrals; 
endorsements; inventory turnover. 
Reference: Business idea.
Virality: will it spread? 
She starts loyalty programs to bring frequent diners back, or 
to encourage people to share with their friends. She engages 
on Yelp and Foursquare. 
Key metrics: Customer loyalty; 
recommendations; referrals; 
endorsements. 
Reference: Business positioning
Revenue: prove the business viability 
With virality kicked off, she works on margins—fewer free 
meals, tighter controls on costs, more standardization. She 
focuses on the price of acquiring new customers. 
Key metrics: Acquisition cost, 
revenue per cover, capacity, 
turnover. 
Reference: Business model.
Scale: prove it’s a market 
Knowing she can run a profitable business, she funnels 
revenues into marketing and promotion. She reaches out to 
food reviewers, travel magazines, and radio stations. She 
launches a second restaurant, or a franchise. 
Key metrics: Franchise health; 
repeatability; problems escalated; 
variance; franchise revenues. 
Reference: Business plan.
A line in the sand 
Labor costs 
Gross revenue 
30% 
24% 
20% 
Too costly? 
Just right 
Understaffed? 
=
A leading indicator 
50 reservations 
at 5PM 
250 covers 
that night 
(Varies by 
restaurant. 
McDonalds 
≠ Fat Duck.) 
http://www.flickr.com/photos/mysticcountry/3567440970 http://www.flickr.com/photos/avlxyz/4889656453
http://www.flickr.com/photos/southbeachcars/6892880699 
Restaurant MVP
Is tip amount a leading indicator of long-term 
revenue?
Why does every table get the same 
menu?
Is tipping even a good idea? 
Customers like 
Servers like tipping 
tipping because it puts 
because it means their 
them in the driver’s 
talent is rewarded. As a 
seat. As a diner, you 
great server, you get 
control your 
paid more than your 
experience, using the 
peers, because you are 
power of your tip to 
a better worker. 
make sure your server 
works hard for you. 
Owners like tipping 
because it means they 
don’t have to pay for 
managers to closely 
supervise their servers. 
With customers using 
tips to enforce good 
service, owners can be 
confident that servers 
will do their best work. 
Is this true? How would you know? 
Jay Porter founded the Linkery, San Diego's leading farm-to-table restaurant.
The truth about tips 
Customers don’t vary tips much according to service. 
Tipped servers are rewarded for maximizing the number of guests 
they serve, even though that degrades service quality. 
Servers learn to profile guests, focusing on stereotypes while giving 
women, ethnic minorities, the elderly and those from foreign 
countries bad experiences 
When a server is punished, the server can keep that information to 
himself. The message never makes it to a manager, and the problem 
is never addressed.
The truth about tips 
Sharp increase in business over the first two months of the 
new system: 
Servers’ total pay rose to about $22/hour 
Most of the cooks started making about $12-14 
depending on experience 
The dishwashers about $10 
http://jayporter.com/dispatches/observations-from-a-tipless-restaurant-part-1-overview/
Is purple ink better? 
http://tippingresearch.com/uploads/managing_tips.pdf
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Stalking 
customers 
is pretty 
easy. 
http://targetmycustomers.appspot.com http://tippingresearch.com/uploads/managing_tips.pdf
Growth hacking 
(is a word you should hate but will hear a lot about.)
Growth hacking, demystified. 
Find 
correlation 
Test 
causality 
Optimize the 
causal factor 
Pick a metric 
to change
http://blog.justgiving.com/nine-reasons-why-social-and-mobile-are-the-future-of-fundraising/ 
Is social action a leading 
indicator of donation?
http://blog.justgiving.com/nine-reasons-why-social-and-mobile-are-the-future-of-fundraising/ 
Is mobile use?
Guerrilla 
marketing 
Data-driven 
learning 
GROWTH 
HACKING 
Subversiveness
The growth hack 
•Growth hacking is simply what marketing should have been 
doing, but it fell in love with Don Draper and opinions along the 
way 
•Optimize a factor you think is correlated with growth
AirBnB and Craigslist
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
What if you’re an Intrapreneur?
Business model vs. 
company stage 
Early stage Big/incumbent 
Company size/age 
B2B 
Target 
market 
B2C 
More formal decisions 
Less WoM 
Slower cycle time 
More legacy constraints 
It is way too easy to 
mix these up. 
Intrapreneurs
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.
Intrapreneur: 
Someone working to produce 
disruptive change in an organization 
that has already found a sustainable, 
repeatable business model.
In a startup, the purpose of analytics is 
to iterate to product/market fit 
before the money runs out.
In a big company, 
analytics replaces opinion with fact.
(Before we get into Lean Analytics, 2 key lessons.) 
Lesson one: 
Companies die because they fail to 
move to new business models.
Cost per MB 
$1 
$10 
$100 
$1000 
Clay Christensen, The Innovator’s Dilemma 
Time 
14” 
Mainframe 
8” 
Minicomputer 
5.25” 
Desktop 
3.5” 
Notebook
Technologies 
outstrip what 
the market 
needs, driven 
by feedback 
from the 
“best” 
current 
customer. 
$1 
$10 
$100 
$1000 
Clay Christensen, The Innovator’s Dilemma 
8” 5.25” 
Time 
High end 
customer 
Low end 
customer
The new 
market has 
different criteria 
for success, 
which are 
uninteresting to 
incumbents. 
$1 
$10 
$100 
$1000 
Clay Christensen, The Innovator’s Dilemma 
Time 
Storage 
capacity 
Portability
Sometimes 
this has 
unintended 
consequences 
$1 
$10 
$100 
$1000 
Clay Christensen, The Innovator’s Dilemma 
Smaller disc size means less vibration 
impact, leading to greater density, 
increasing storage capacity 
Time
Three kinds of innovation 
Sustain/core 
(optimizing for more of the same) 
Innovate/adjacent 
(introduce nearby product, 
market, or method) 
Disrupt/transformative 
(Fundamentally changing 
the business model) 
Improve along 
current metrics... 
...or alter 
the rate of 
improvement 
Switch to a new 
value model 
Change the business 
model entirely
Lesson two: 
The difference between a rogue agent 
and a special operative is permission.
It’s different when you’re big.
If big firms 
can’t innovate, 
it’s this guy’s 
fault.
When product and market are known, 
companies compete on how they do 
things.
To get the incremental cost to zero, 
companies competed on scale. 
(Literally, an economy of scale)
Scale comes from process, IP, org 
chart, capitalization. 
All of these assume the future will be 
like the past, only more so.
If a startup is an organization designed 
to search for a sustainable, repeatable 
business model, then an established 
company is an organization designed 
to perpetuate one.
Technology has radically changed the 
incremental cost of businesses.
Software is eating the world. 
http://www.flickr.com/photos/ebolasmallpox/3733059220/
An economic order quantity 
of one. 
Crafted Mass-produced 
Automated Digital 
Quantity Few Many Some One 
Cost High Low Medium Free 
Lead time Small Large Medium None 
Self-service Medium None Some Lots 
Customization High None Some Lots 
This is why 
software is 
eating the 
world. 
• Cloud computing 
• Social media 
• 3D printing 
• Per-customer 
analysis 
• Mobile tracking 
• Etc...
Sustainable competitive advantage allows for 
inertia and power to build up along the lines of 
an existing business model, which will soon die. 
Instead, seek transient competitive 
advantage. 
Rita Gunther McGrath, The End of Competitive Advantage
Scale is now a liability. Compete on 
cycle time.
CW&T make a pen
http://www.flickr.com/photos/art_es_anna/288880795/
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Optimizing the probable means 
discounting the possible.
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
This isn’t about a lack of resources.
http://www.flickr.com/photos/maladjusted/5207565912
Blockbuster had a lot going for it.
Plenty of inventory, of course. 
But that matters less than...
...market intelligence, 
customers, existing 
payment approval, 
and customer 
history.
The problem was framing: 
Blockbuster thought it was in the video 
store management business. Netflix 
realized it was in the entertainment 
delivery business.
YOU ARE 
HERE
LOCAL 
MAXIMUM 
YOU ARE 
HERE 
OPTIMIZATION 
OF CURRENT 
METRICS
YOU ARE 
HERE 
GLOBAL 
INNOVATION MAXIMUM 
WITH NEW 
RULES
YOU ARE 
HERE 
SHORT-TERM INVESTORS 
HATE GOING DOWNHILL
First mover advantage happens 
long before the market emerges. 
• $1B invested in Nook 
• $475M operating loss 
in April 2013 
• CEO gone
Constraints slow things down 
vs.
Capital cycles don’t fit the short, iterative 
nature of startup uncertainty 
12 month budgeting cycle; annual plan. Future based on past. 
Agile, scrum, lean iterations. Today’s model. No evidence about the future. 
Project 
Project 
Project 
Project 
Project 
Project 
Project 
Project 
Project 
Project 
Project 
Project 
(Requires budget insulation)
Everything to lose: 
Why big companies need innovation.
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
F500 Life 
Expectancy 
(http://csinvesting.org/2012/01/06/fortune-500-extinction/) 
75 
years 15 
years 
1950 ... 2010 
Growth by entering 
a new business 95 % fail 
Corporate 
Strategy Board 
99 % fail 
Clay 
Christensen
mikemace.com 
The slow 
death of 
a market 
leader. 
“Time to enter 
the mainstream. 
Cut prices.” 
“Let’s cut 
prices to 
accelerate 
our growth.” 
“We may miss the quarter. 
Let’s do a price promotion.” 
“That wasn’t 
supposed to 
happen. We’ll 
have to lay 
some people 
off. 
Revenue over time 
This is what most 
managers track. 
Note that sales keep 
rising (making you 
feel safe) until you 
run off the edge of 
the cliff. 
The adoption curve 
Here’s where you 
actually are, but you 
don’t know it 
because you can’t 
draw the curve until 
after the market 
saturates. 
Early 
adopters 
Late 
adopters 
Gross margin 
percent 
Declining profit 
per unit (gross 
margin) is actually 
your best signal of 
trouble.
In other words, if your job is change you 
have your work cut out for you.
A dose of pragmatism
Many models for enterprise innovation 
Core Adjacent Transformative 
Do the same 
Nearby product, 
Start something 
thing better. 
market, or method. 
entirely new. 
Regional 
optimizations. 
Innovation, go-to-market 
strategies. 
Reinvent the 
business model. 
• Get there faster 
• Smaller batches 
• Solution, then testing 
• Increased accountability 
• Customer development 
• Test similar cases 
• Parallel deployment 
• Analytics & cycle time 
• Fail fast 
• Skunkworks/R&D 
• Focus on the search 
• Ignore the current 
model & margins
Another way to look at it 
Core Adjacent Transformative 
Know the problem 
(customers tell you it) 
Know the solution 
(customers/regulations/ 
norms dictate it.) 
Know the problem 
(market analysis) 
Don’t know the solution 
(non-obvious innovation 
confers competitive 
advantage.) 
Don’t know the problem 
(just an emerging need/ 
change) 
Don’t know the solution. 
Waterfall: 
Execution 
matters 
Agile/scrum: 
Iteration 
matters 
Lean Startup: 
Discovery 
matters
The Three Horizons 
Core Adjacent Transformative 
Those core businesses most 
readily identified with the company 
name and those that provide the 
greatest profits and cash flow. 
Maximize remaining value. 
Emerging opportunities, including 
rising entrepreneurial ventures 
likely to generate substantial 
profits in the future but that could 
require considerable investment. 
Ideas for profitable growth down the 
road—for instance, small ventures 
such as research projects, pilot 
programs, or minority stakes in new 
businesses. 
Horizon 1 improves the 
current business operations 
in the next 12 months. 
Horizon 2 extends the 
business into new products, 
markets, or methods in the 
next 3 years. 
Horizon 3 changes the 
industry you’re in and your 
value network in the next 6 
years. 
http://www.mckinsey.com/insights/strategy/enduring_ideas_the_three_horizons_of_growth
Lean applies. Startup may not. 
Core Adjacent Transformative 
Lean methodologies. 
Lean 
startup
Experiment with product, market, 
and method.
Method 
(new “how”) 3 kinds of 
innovation 
Product 
(new “what”) 
Market 
(new “who”)
Product 
(new “what”) 
Market 
(new “who”) 
Method 
(new “how”) 
Startup 
Distribution 
innovation 
Market 
diversification 
Core 
More things to more people for more money 
more often more efficiently. (Zyman) 
Innovative 
Change what you sell, or who 
you sell to, or how you sell it. 
Transformative 
Fundamentally change business and value 
proposition. Rebrand & cannibalize. 
Channel 
expansion Disruptive 
Create what wasn’t possible, based on 
massive societal or technical change.
Engine as a service
Engine as a service 
http://www.nasa.gov/images/content/365835main_airplane_noise_qtd2_3024x2016.jpg
“Efficiency is tied to 
analytics. We’ll still look 
for new materials, or for 
the physics of devices, 
but the analytics ... is 
what’s really untapped.”
Business 
optimization 
(five mores) 
Current 
state 
Product, 
market, 
method 
innovation 
Business 
model 
innovation 
You can convince 
executives of this 
because some of it 
is familiar. 
This terrifies them 
because it eats the 
current business. 
A three-maxima model 
of enterprise innovation
Improvement Adjacency Remodeling 
Do the same, 
Explore what’s 
only better. 
nearby quickly 
Try out new 
business models 
Lean approaches apply, but the metrics vary widely. 
Sustain/ 
core 
Innovate/ 
adjacent 
Disrupt/ 
transformative
Sustaining Adjacent Disruptive 
Next year’s car Electric car, 
same dealer 
On-demand, app-based 
car service
Sustaining 
innovation 
is about 
more of 
the same. 
(says Sergio Zyman) 
More things 
To more people 
For more money 
More often 
Inventory increase 
Gifting, wish lists 
Highly viral offering 
Low incremental order costs 
Maximum shopping cart 
Price skimming/tiering 
Loyal customer base that returns 
Demand prediction, notification 
More efficiently Supply chain optimization 
Per-transaction cost reduction
Blizzard extends the 
lifespan of WOW 
Early 
adopters 
Rapid 
growth 
Market 
saturation 
The infamous S-curve 
(Product lifecycle, Bass diffusion curve, etc.)
Blizzard extends the 
lifespan of WOW
Blizzard extends the 
lifespan of WOW 
Fixing this: sustaining growth with novelty 
Product & market innovation 
(“New & improved!”)
Blizzard extends the 
lifespan of WOW 
WOW 
Wrath of 
the Lich King 
Burning 
Crusade 
Mists of 
Cataclysm Pandaria
Most of your 
innovation will 
be adjacent or 
sustaining. 
Question marks! 
(low market share, 
high growth rate) 
May be the next big thing. 
Consumes investment, but 
will require money to 
increase market share. 
Stars! 
(high growth rate, 
high market share) 
What everyone wants. As 
market invariably stops 
growing, should become 
cash cows. 
Dogs! 
(low market share, 
low growth rate) 
Barely breaks even, may 
be a distraction from better 
opportunities. Sell off or 
shut down. 
Pivot to 
increase growth 
rate through 
disruption 
Cash cows! 
(high market share, 
low growth rate) 
Boring sources of cash, to 
be milked but not worth 
additional investment. 
Growth rate 
Pivot to 
increase 
market 
share 
through 
virality, 
attention 
Market share 
Pivot to 
redefine problem/ 
solution through 
empathy 
Milk with 
revenue 
optimization as 
growth slows 
If you don’t like 
this, go launch 
a startup.
Software, experimentation, and 
iterative cycles of learning help you 
get to the local maximum better and 
faster. That’s a good thing. 
But it’s not the only thing.
Adjacent innovation is about changing 
one part of the model in a way that 
alters the value network.
Amazon Web Services and the 
server value network 
Server computing 
• Density 
• GHz 
• Heat 
• MIPS 
Cloud computing 
• Instances 
• Objects 
• Spinup time 
• Scaleout 
Capex, financing, 
TCO, ROI 
Opex, demand, time 
to result 
CIO, enterprise IT CTO, coder, app owner, 
line of business, startup 
Value 
criteria 
Money 
Buyer
Adjacent product 
to the same 
market in the 
same way
Selling the same product to an 
adjacent market in the same 
way. 
Of P&G’s 38 brands, only 19 were sold in Asia as of 2011 
Market expansion is seldom selling the same thing to new people. In 
Asia, P&G needed to 
Align pricing with novelty (prestige, mass-tige, over-the-counter) 
Change consumer expectations (moving from dilutes to 
concentrates) 
Adjust positioning and ingredients such as white fungus, ginseng, 
and the parasitic cordyceps
Selling the same product to the same 
market in a new way. 
The biggest innovation in 
logistics of the 20th century. 
http://www.flickr.com/photos/photohome_uk/1494590209
Changing the method of 
C2C classifieds 
A blend of who, what, how 
Classified C2C sales (same 
“what”) 
Strictly for Japanese women 
(targeted “how”) 
New how (phone is capture, 
display, payment, transaction) 
Did 100 interviews w/target 
users before launch 
Key insight: Japanese women 
sell their entire wardrobe 
twice in their lives 
5,000 and 10,000 sales in first 
month 
10% commission fee 
Average price of items is 
pretty low, at around 2,000 to 
3,000 yen (or $22 to $34) 
Not an auction: seller decides 
price 
Mobile-only model 
Phone is payment, storefront, 
and even a way for sellers to 
build their catalog 
http://www.sffashtech.com/2012/10/10/a-free-market-fashion-app-exclusively-for-women-japan/
Selling the same product to the 
same market in a new way.
(At this point, observant Intrapreneurs 
should be asking, should P&G be in 
the house cleaning business? 
And that would be transformative.)
Transformative innovation is about 
taking a leap, changing more than one 
dimension simultaneously in search of 
a new business model.
If sustaining, incremental innovation 
produces linear growth, then 
disruptive, transformative innovation 
produces exponential growth.
Transformative isolation: 
Skunkworks
Transformative 
incubation: 
Metlife Infinity
Transformative incubation: 
Taser evidence.com 
Significant market 
850K full-time law enforcement officers in the 
US; 700K state/local; 525K patrol officers 
130M incident reports/y. 70M new incidents; 
200K involve use of force 
Only 31% of local police agencies keep 
computer files on use-of-force incidents 
Strong product benefits 
Exonerates the officer 96% of the time. 
47% percent increase in charges and 
summons (2007) 
Patrol officers spend 15-25% of their time 
writing incident reports, recorded evidence 
reduces this by 22%, meaning 50m more on 
patrol 
Challenges 
New business model 
Pricing unclear 
SaaS offering 
Compliance and governance 
Unions, regulation, chain of evidence 
Changing the current model (radio is 
everything)
When it’s you vs. the world. 
(A bagful of tricks from agitators in companies of all sizes.)
The Lean Analytics lifecycle of an Intrapreneur 
Beforehand Get buy-in Political fallout 
Empathy Find problems; don’t test demand. 
Skip the business case, do analytics 
Entitled, aggrieved 
customers 
Stickiness Know your real minimum based on 
expectations, regulations 
Hidden “must haves”, 
feature creep 
Virality Build inherent virality in from the 
start; attention is the new currency 
Luddites who don’t 
understand sharing 
Revenue Consider the ecosystem, channels, 
and established agreements 
Channel conflict, 
resistance, contracts 
Scale Hand the baton to others gracefully Hating what happens 
to your baby
The Zero Overhead principle 
A central theme to this new wave of innovation is the 
application of core product tenets from the consumer space 
to the enterprise. 
In particular, a universal lesson that I keep sharing with all 
entrepreneurs building for the enterprise is the Zero 
Overhead Principle: no feature may add training costs to 
the user. 
DJ Patil
The job of an intrapreneur is to 
identify an adjacent market, product, 
or method that conforms to 
organizational filters. 
It is not to improve the current 
product, market, or method.
Also: a pariah. 
Successful innovators share certain attributes. 
Bad listener: Wilfully ignore feedback from your best customers. 
Cannibal: If successful, destroying existing revenue streams. 
Job killer: Automation & lower margins are your favorite tools. 
Security risk: Advocate of transparency, open data, communities. 
Narcissist: Worry constantly about how you’ll get attention. 
Slum lord: Sell to those with less money, deviants, and weirdos.
The six habits of highly unrealistic leaders 
Bad leaders: 
Filtered information 
Selective hearing 
Wishful thinking 
Fear 
Emotional overinvestment, 
Unrealistic expectations from 
capital markets 
Good Intrapreneurs: 
Access to the real information 
Go where the data takes you 
Set aside your assumptions 
Embrace uncertainty 
Surgical detachment 
Have high standards with low 
expectations 
Confronting Reality (Crown Business), Larry Bossidy and Ram Charan
Know what 
kind of 
innovation 
you’re 
after. 
New 
Current 
Market development: 
Sell existing products 
to new markets, 
segments, uses. 
Export & license. 
Startup: 
New products for new 
markets. New rules, 
business units, 
organizational 
structure. Innovation. 
Current New 
Market 
Product 
Penetrate: 
Increase revenues, 
market share, product 
quality, brand 
differentiation. 
Marketing. 
Product 
development: 
Invent new products 
for your market. R&D, 
enhancements. 
Acquisition. 
Based on H. Igor Ansoff’s matrix 
Increased risk of political fallout (and great success!)
Use outliers and missed searches to 
hunt for good ideas & adjacencies 
1/8 men have an incontinence issue. 1/3 
women do. 
When search results show a significant 
number of men searching, this suggests the 
adjacent (male) market is underserved. 
(Multi-billion-dollar hygiene product company)
Frame it like a study 
Product creation is almost 
accidental. 
Unlike a VC or startup, when 
the initiative fails the 
organization still learns. 
http://www.flickr.com/photos/creative_tools/8544475139
When in doubt, collect data 
From tackling the FTA rate to 
visualizing the criminal justice 
supply chain.
Use data to create a taste for 
data 
Sitting on Billions of rows of 
transactional data 
David Boyle ran 1M online surveys 
Once the value was obvious to 
management, got license to dig.
Smart Badge 
4” e-ink display with 
name and specialty. 
Badge scans barcode and 
gets specs; checks 
inventory; enters data on a 
touch screen. 
Data Exhaust 
Today: Workers see their own 
productivity. 
Coming soon: comparing 
yourself to 400,000 other 
employees. 
Ultimately: Learning what 
(and who) works well. 
Tesco connects 
its workforce
Don’t just collect data, 
chase it.
Understand hidden 
constraints 
That pencil story is a myth. 
Graphite is conductive and 
explosive. The Minimum 
Viable Product is Viable for a 
reason.
Know what has to 
be built in-house 
SAP integration 
Employment law
http://www.flickr.com/photos/bootbearwdc/1243690099/ 
Think subversively.
Everything’s an excuse to experiment
Find other ways 
to collect data; 
everything is an 
experiment.
Run it as a consulting business first. 
(Just don’t get addicted to it. Your goal is to 
learn and overcome integration challenges and 
find the 20% of features that 80% of the market 
will pay for.)
Convince your boss she asked for this 
Draw a line 
in the sand Pick a KPI 
Draw a new line 
Pivot or 
give up 
Try again 
Success! 
Did we move 
the needle? 
Measure 
the results 
Design a test 
Make changes 
in production 
Find a 
potential 
improvement 
With data: 
find a 
commonality 
Without 
data: make a 
good guess 
Hypothesis
Focus on the desired behavior, not just 
the information. 
26% increase in towel 
re-use with an appeal 
to social norms; 33% 
increase when tied to 
the specific room. 
http://www.psychologytoday.com/blog/yes/ 
200808/changing-minds-and-changing-towels 
The effectiveness of energy 
conservation “nudges” depends on 
an individual’s political ideology ... 
Conservatives who learn that their 
consumption is less than their 
neighbors’ “boomerang” whereas 
liberals reduce their consumption. 
Energy Conservation “Nudges” and Environmentalist 
Ideology: Evidence from a Randomized Residential Electricity 
Field Experiment - Costa & Kahn 2011
Slaughter a sacred cow: 
Prove a long-held assumption is 
wrong and you’ve got people’s 
attention. 
Know what you’ll do with it ahead of 
time.
Take baby steps.
Netflix
Tesla 
http://www.hdwallpapersinn.com/wp-content/uploads/2012/12/600-tesla.jpg
Twitter’s 140-character 
limit isn’t arbitrary. It’s 
constrained by the size 
http://i.i.cbsi.com/cnwk.1d/i/tim/2011/11/18/ 
sms_screen_twitter_activity_stream_270x405.png
Figure out how to translate it back to a 
simple model that fits the company’s 
existing value model. 
If your company dies, this is why.
Intrapreneurs often have to use proxies 
Stage Startup metrics Intrapreneur metrics 
Empathy 
Customers interviewed (needs & 
solutions), assumptions quantified, 
TAM, monetization possibility 
Non-customers interviewed; 
assumptions quantified, constraints 
identified, TAM, disruption potential 
Stickiness Churn, engagement Support tickets, integration time, call 
center data, delays 
Virality Viral coefficient, viral cycle time Net Promoter Score, referrals, case 
study willingness 
Revenue Attention, engagement 
Billable activity; signed LOIs; pilot 
programs; after-development 
profitability 
Scale Automation Contribution, training costs, licensing
When you have support. 
(What companies like P&G, Cognizant, GE, and Motorola do with a 
formal innovation program.)
Do you really have permission? 
What resources do you have? 
Staff, budget, unfettered access to customers? 
What scope of change can you make? 
Pricing, product, channel, branding?
2011 MIT study of 179 large publicly traded firms 
Companies that use data-driven 
analytics instead of intuition have 
5%-6% higher productivity and 
profits than competitors. 
Brynjolfsson, Erik, Lorin Hitt, and Heekyung Kim. "Strength in Numbers: How Does Data-Driven 
Decisionmaking Affect Firm Performance?." Available at SSRN 1819486 (2011).
The fundamental shift 
Ask 
question 
Define 
schema 
Collect 
data 
Answer 
question 
Refine 
problem 
Collect 
data 
Ask 
question 
Emergent 
schema 
Explore 
data 
Answer 
question 
“Collect first; ask questions later.”
What kind of mandate do you have?
Step one: Develop a portfolio approach.
Innovation portfolios at big companies 
Core Adjacent Transformative 
70% 20% 10% 
Investment 
10% 20% 70% 
Return
Organizations’ structures emerge as a way 
to optimize the current business model. 
Most innovations will come not from 
product or market, but from method— 
business model innovation. 
Innovation groups must exercise 
organizational amnesia at the outset. 
1. 
2. 
3.
Tomorrow’s company: Running parallel businesses 
Innovation Sustaining/core Adjacent Transformative/ 
disruptive 
Core action Optimizing/ 
improving Experimenting Searching/ 
inventing 
Focus on Known metrics Risk removal Assumption 
validation 
Which will live Within current 
business unit 
Incubated, then 
integrated 
As new/separate 
entities 
Problem is Known Known Unknown 
Solution is Known Unknown Unknown
Step one: Frame your problems.
(See also: Christensen’s Jobs to be done.)
Step two: Define your gates and filters. 
These may lead to myopia. 
They are also your unfair advantages.
The 3 stages of the 
Emerging Business Office 
Generation makes increasing 
investments in companies 
4 pillars: Capturing, 
connecting, deciding, and 
acting on data 
Market sizing 
3 horizons & timeframes 
Science: 3-5y 
Development: 1-2y 
Preparation: <12m 
“A startup could take 
a year to talk to as 
many customers as we 
Exploration proves out both 
the tech and business model 
do in a week.” 
Challenge the assumptions. 
“Am I hitting my milestones?” 
and “Are my assumptions 
still valid?” 
Rapid prototyping. Focus on 
risk and uncertainty: which 
things don’t we know how to 
do? 
Adoption means customer 
buying in 
External partner; validate 
across multiple constituents 
to ensure it’s a scalable 
business model. 
Use customer base as an 
advantage. C-level 
conversations almost 
immediately. 
6-8 Generate projects 
What’s the value proposition? 
Why are we going to make money? 
Why Motorola? 
4 Explore projects 
Number of dangling assumptions 
Rate at which it’s growing/sinking 
Very deep with small sample size 
6-8 Adopt projects 
Casting a wider net 
Go-to-market metrics 
Funnel size and market segments
Step three: Secure funding, resources, and 
executive backing.
Reinvesting 
For every $100 they cut, Metlife reinvests $66 in new projects.
Step four: Generate new ideas.
Find non-obvious adjacencies 
LIGH 
T 
ELECTRICAL 
GENERATOR 
SOFTWARE TO 
CUT DOWN 
TREES BETTER 
MRI MACHINE 
POWER GRID 
PLANE ENGINE 
REQUIRES 
TRAIN ENGINE WIND TURBINE 
NEEDS 
AN 
WHICH 
FEEDS A 
HAS A 
TURBINE 
LIKE A 
TURNED 
AROUND 
BECOMES A 
SPINS & 
VIBRATES 
LIKE AN 
AND 
LOOKS 
LIKE A
Build an ecosystem 
Canada’s largest directory 
publishing and local 
marketing services company 
1.5M listings from 420K 
SMB & national customers 
Revenues >$1.2B 
2,500 employees 
Created third-party listing API 
Took 8-10 mo (2009-10) to 
get approval 
API payoff happened 2y later 
Yahoo replaced Canadian 
digital properties search 
with the YellowAPI 
Improved SEO, Comscore 
Functional prototype in 
hours, testing in days, and 
launching in weeks. 
Faster time to partnerships 
Budgets tripled in 2013 
KPI evolution 
Soft: Signups, 
SDK, downloads 
App usage, 
deals signed 
API calls 
generated 
API-generated 
revenue
Three sources of innovation 
Top-down: Areas where business heads see market trends but white spaces in our offerings. Maybe we 
can fill this white space. 
Bottoms-up 
160,000 associates worldwide use an app called Spark; if viable we put it in front of the EBA 
leadership meeting 
Sparktank meeting—should we put $100-$150K to go and find a first customer. 
Outside-in 
M&A easier when there is an EBA structure exists because it specializes in integration with the 
existing organizaton we bring them into the EBA and help them match 
Innovation/investment team backs a few people who have a good idea and can use the 
infrastructure, channel, etc.
Five common models for 
transformative innovation 
All employ different 
models at different times. 
Acquisition 
Collaboration 
Isolation 
Incubation 
Integration 
Buy promising startups 
Crowdsource, work with 
universities, suppliers, etc. 
Create a separate group 
with different conditions 
Internal startup ecosystem; 
LoB are “investors” 
The LoB does innovation 
internally
Step five: Test by doing: Experimentation 
beats projection.
Focus on 
the model, 
not the 
plan 
Demand 
People per day on sidewalk 
Percent that buy a glass 
Daily customers 
Revenue 
Price per cup 
Cost of Goods 
Cost per cup 
Profit per cup 
Daily profit 
Amt 
200 
10% 
20 
$5 
$1 
$4 
$80 
Growth 
4% 
5% 
-2% 
Wk 1 
204 
15% 
31 43 56 
$5 $5 $5 
.98 
Wk 2 
216 
20% 
.96 
Wk 3 
225 
25% 
.94 
$156 
30.6 
$216 
41.5 
$281 
52.8 
4.02 4.04 4.06 
125 175 228
A business plan is just what happens 
when you drag the business model to 
the right.
Designing an experiment 
Problem, solution, and result hypothesis 
Test strategy (PoC, survey, interviews, kickstarter, prototype, A/B, etc.) 
Cohort & segment to be tested 
Metric or assumption being tested 
Timebox or total for test 
Action you’ll take if you pass or fail
Step six: Know what happens afterwards
Qualcomm’s initial 
innovation model 
http://blogs.berkeley.edu/2013/01/28/ 
designing-a-corporate-entrepreneurship- 
program-a-qualcomm- 
case-study-part-1-of-2/ 
Hypothesis Experiment Implement 
Idea generation 
and selection 
Boot camp Idea 
advancement 
Ideas 
Existing models 
New 
models 
Open 
innovation 
Tech 
feasibility 
Biz 
feasibility 
Boot 
camp 
decision Implement 
End user/partner 
desirability 
Action 
s 
Option 
value 
Strategic 
value 
Exit 
value 
Company crowd storm Small team designs & 
decision 
conducts experiments 
Company extracts value
Qualcomm’s updated model 
Criteria 
Fully open to all 
employees 
Ideas implemented 
by existing 
business/R&D units 
Efficient way to 
bubble-up best 
ideas (and their 
champions) to the 
timely attention of 
top execs 
Hypothesis Experiment Implement 
Idea generation 
and selection 
Boot camp 
(3 mo, part time) 
CEO 
open call 
Innovator 
challenges 
Idea mgmt. 
system 
Discover Network 
Accelerate 
Pitch to exec team 
Self-forming 
teams 
Filters 
Contextual education 
Mentorship 
Micro-seed funding 
Program staff support 
BU sponsor home 
Employee 
team 
BU 
Sponsor 
Program team 
Value extraction 
Future option value 
Strategic value 
Exit value
Qualcomm’s innovation model: 
What was missing 
Hypothesis Experiment Implement 
POC 
Idea generation 
and selection 
Boot 
camp 
Idea 
advancement 
Ideas 
Existing models 
New 
models 
Open 
innovation 
Tech 
feasibility 
Biz 
sustain-ability 
Boot 
camp 
decision Implement 
End user/partner 
desirability 
Action 
s 
Option 
value 
Strategic 
value 
Exit 
value 
Company crowd storm Small team designs & 
decision 
conducts experiments 
Company extracts value 
POC 
decision 
Unclear what 
happened to 
founders 
Needed a 
middle PoC 
decision 
Sustainability, 
not feasibility
Step seven: Rinse, repeat.
The Lean Analytics lifecycle of an Intrapreneur 
Beforehand Get buy-in Political fallout 
Empathy Find problems; don’t test demand. 
Skip the business case, do analytics 
Entitled, aggrieved 
customers 
Stickiness Know your real minimum based on 
expectations, regulations 
Hidden “must haves”, 
feature creep 
Virality Build inherent virality in from the 
start; attention is the new currency 
Luddites who don’t 
understand sharing 
Revenue Consider the ecosystem, channels, 
and established agreements 
Channel conflict, 
resistance, contracts 
Scale Hand the baton to others gracefully Hating what happens 
to your baby
Metrics for innovation portfolios.
Core metrics 
Metrics that matter 
• Return on investment 
• Total cost of ownership 
• Trouble tickets/issues 
• Training time 
• Comparing to others 
Business plan. 
Assume it will work. 
But the market will change by the 
time you’ve built it. 
Example: Online parking 
tickets
Adjacent metrics 
Metrics that matter 
• Questions answered 
• Virality & word of mouth 
• Early adopter stickiness 
• Regulation 
• Total addressable market 
Business model. 
Assume it will fail. 
Your ultimate use case won’t be 
what you think it is today. 
Example: Mr. Clean 
Magic Eraser
Transformative metrics 
Metrics that matter 
• People I’ve talked to 
• Prototype creation speed 
• Assumptions validated 
• Problems uncovered 
• Technical feasibility 
• Hidden constraints 
Business idea. 
Assume it is possible. 
You hope it will have the 
consequences you want but 
aren’t sure how. 
Example: Headcam 
recordings of all officers
The Emerging Business 
Accelerator 
Three Horizons model 
Horizon one is traditional services such 
as app dev (SAP, Oracle) 
Horizon two are offerings that aren’t 
quite as big and mainstream, not used 
by everyone, but have good traction. 
Smaller revenue contribution (IT 
infrastructure, vertically focused BPO). 
Also includes some strategy/tactics 
Horizon three is about identifying ideas 
that are worth investing in, allocating 
investment, and incubating them 
through our own practices. 
Projects “graduate” into a lower horizon 
20 ventures today, in 1 of 3 dimensions 
Innovation along 3 dimensions 
New markets: Either traditional 
offering in a new place i.e. Latin 
America, Can’t simply do labor 
arbitrage. Can also be a new 
vertical such as government. 
New technologies: Social, mobile, 
analytics, cloud, Internet of 
Things. 
New delivery models (“products”): 
Platforms, recurring revenues, 
building products to enable 
vertical business processes. 
Explore-to-graduate criteria 
Explore phase are looking for a 
first customer 
Early startup are looking for early-stage 
customers. 
Late-stage startup are trying to 
show they can deliver for multiple 
customers; have a business 
model 
Growth phase has true P&L. 
They’re past the cashflow 
breakeven. 
We’re saying, “we know enough 
about price they will pay and how 
many people will want, and what it 
costs, so we know margin.” If they 
can deliver against this we 
graduate.
Portfolio metrics 
“Do we need to 
meet more often?” 
is a metric.” 
Number in the pipeline; is it growing? 
How many are crazy vs. real business ideas? 
Ideas funded; ideas that were a waste; ideas needing iteration 
# of meetings, qualitative feedback, pivots 
Have we convinced someone to sign on for something? 
Number of proposals issued; pipeline 
Satisfied delivery, on budget; trouble tickets; delays; escalation; referenceability 
Profitable independent of costs like development? 
Ideas 
Quality 
Funding 
Exploration 
Solution fit 
Demand 
Product fit 
Profitability 
Cashflow B/E 0% overall profitability, beginning to repay initial investment 
Graduation Making money overall
Key points to clarify in an 
innovation program 
Hypothesis Experimentation Implementation 
• Articulate problems 
• Define the right filters 
• Get ideas from many 
sources 
• Confirm funding (money, 
people, customer access) 
• Agree on analytical 
framework 
• Balance market, product, 
& method adjacencies 
• Prioritize riskiest 
assumptions 
• Time-box assessment 
stages 
• Test technology, demand, 
and business feasibility 
• MVP, prototype, pilot, or 
science as appropriate for 
type of innovation 
• Temporary incubator 
• Find a home or building 
one 
• Keep innovators involved 
• Merge metrics with 
existing business KPIs 
• Synchronize innovation 
cycles with enterprise 
cycles (budget, etc.) 
Portfolio metrics; Gates and KPIs for each stage; mix of core, adjacent, and 
disruptive innovation.
Goals, constraints, context 
Sourcing Filtering 
Core Integration 
Adjacent 
Disruptive 
(how to decide?) 
Adoption by 
existing line of 
business. 
Independence 
Creation of a new 
line of business. 
Cross-pollinate 
to current 
managers 
Evaluation of the innovation program itself 
Socializin 
g 
Test/ 
validate 
w/current 
customers 
Grow 
as a 
distinct 
business 
Top-down 
Bottom-up 
Outside-in 
R&D M&A
Some tools and traps
Build a message map. 
1. Understand the stages a buyer goes through 2. Create benefits; mitigate objections 3. Target the message to the stage the audience is at
Everyone in the world 
A. I need a car 
I should buy 
B. a car 
It should be 
C. a hybrid 
I should buy 
D. a Honda Civic
Everyone in the world 
A. I need a car 
People who want to drive 
I should buy 
B. a car 
Prospective car buyers 
It should be 
C. a hybrid 
People looking for a hybrid 
I should buy 
D. a Honda Civic 
Honda Civic Hybrid owners
“Isn’t it time you got out of the 
city?” campaign showing how cars 
make nature accessible & ridiculing 
urban hipsters. 
Ads showing how cars are needed 
any time (pregnancy, errands, urgent 
business) and how a car is a 
“personal assistant.” 
Urgency (“every time you drive a 
non-hybrid car you kill the planet a 
little”) and testimonials from buyers 
who’ve saved money. 
Honda branding ads and model-specific 
promotions. 
Follow-up satisfaction campaign to 
encourage buyers to tell their friends 
Everyone in the world 
A. I need a car 
People who want to drive 
“I need a vehicle to get 
around, be productive, and 
enjoy my life.” 
I should buy 
B. a car 
Prospective car buyers 
“I want to own a car because it’s 
convenient; it’s a personal 
relationship; I don’t trust others.” 
It should be 
C. a hybrid 
People looking for a hybrid 
“I want to save money and fuel. I 
also care about the environment 
and want to be seen as ‘green’.” 
I should buy 
D. a Honda Civic 
Honda Civic Hybrid owners
Everyone in the world 
People who want to drive 
“I need a vehicle to get 
around, be productive, and 
enjoy my life.” 
Prospective car buyers 
“I want to own a car because it’s 
convenient; it’s a personal 
relationship; I don’t trust others.” 
People looking for a hybrid 
“I want to save money and fuel. I 
also care about the environment 
and want to be seen as ‘green’.” 
Honda Civic Hybrid owners 
Those who don’t need cars 
• I’m too young to drive 
• I’m too old to drive 
• I can walk or take public 
transit 
Car users who won’t buy 
• It’s too expensive for me 
• I will use a shared car service 
• It’ll get stolen 
Those who won’t buy hybrids 
• Hybrids are gutless 
• Batteries are toxic & explosive 
• In the end it costs more than 
it saves 
I will buy another brand 
• I buy domestic 
• I’ve always driven a VW 
• Toyotas are reliable 
• I want something prestigious 
A. I need a car 
I should buy 
B. a car 
It should be 
C. a hybrid 
I should buy 
D. a Honda Civic
Everyone in the world 
People who want to drive 
“I need a vehicle to get 
around, be productive, and 
enjoy my life.” 
Prospective car buyers 
“I want to own a car because it’s 
convenient; it’s a personal 
relationship; I don’t trust others.” 
People looking for a hybrid 
“I want to save money and fuel. I 
also care about the environment 
and want to be seen as ‘green’.” 
Honda Civic Hybrid owners 
Those who don’t need cars 
• I’m too young to drive 
• I’m too old to drive 
• I can walk or take public 
transit 
Car users who won’t buy 
• It’s too expensive for me 
• I will use a shared car service 
• It’ll get stolen 
Those who won’t buy hybrids 
• Hybrids are gutless 
• Batteries are toxic & explosive 
• In the end it costs more than 
it saves 
I will buy another brand 
• I buy domestic 
• I’ve always driven a VW 
• Toyotas are reliable 
• I want something prestigious 
Sponsor a driving school 
“Give the gift of driving” 
campaign for grandparents. 
PR on dangers of commuting, 
pedestrian deaths 
Financing, cashback 
Sell to carshares; 
underscore their limitations 
Theft warranty, tracking 
services, high-end locks 
Independent tests, 
standard metrics (0-60 in X) 
Lab research, studies 
ROI calculator; 
replacement programs 
Prove Honda hires US workers 
“Time to leave Germany” ads 
Spontaneous accel. stories 
Premium brand (Acura) 
A. I need a car 
I should buy 
B. a car 
It should be 
C. a hybrid 
I should buy 
D. a Honda Civic
“Isn’t it time you got out of the 
city?” campaign showing how cars 
make nature accessible & ridiculing 
urban hipsters. 
Ads showing how cars are needed 
any time (pregnancy, errands, urgent 
business) and how a car is a 
“personal assistant.” 
Urgency (“every time you drive a 
non-hybrid car you kill the planet a 
little”) and testimonials from buyers 
who’ve saved money. 
Honda branding ads and model-specific 
promotions. 
Follow-up satisfaction campaign to 
encourage buyers to tell their friends 
Everyone in the world 
People who want to drive 
“I need a vehicle to get 
around, be productive, and 
enjoy my life.” 
Prospective car buyers 
“I want to own a car because it’s 
convenient; it’s a personal 
relationship; I don’t trust others.” 
People looking for a hybrid 
“I want to save money and fuel. I 
also care about the environment 
and want to be seen as ‘green’.” 
Honda Civic Hybrid owners 
Those who don’t need cars 
• I’m too young to drive 
• I’m too old to drive 
• I can walk or take public 
transit 
Car users who won’t buy 
• It’s too expensive for me 
• I will use a shared car service 
• It’ll get stolen 
Those who won’t buy hybrids 
• Hybrids are gutless 
• Batteries are toxic & explosive 
• In the end it costs more than 
it saves 
I will buy another brand 
• I buy domestic 
• I’ve always driven a VW 
• Toyotas are reliable 
• I want something prestigious 
Sponsor a driving school 
“Give the gift of driving” 
campaign for grandparents. 
PR on dangers of commuting, 
pedestrian deaths 
Financing, cashback 
Sell to carshares; 
underscore their limitations 
Theft warranty, tracking 
services, high-end locks 
Independent tests, 
standard metrics (0-60 in X) 
Lab research, studies 
ROI calculator; 
replacement programs 
Prove Honda hires US workers 
“Time to leave Germany” ads 
Spontaneous accel. stories 
Premium brand (Acura) 
A. I need a car 
I should buy 
B. a car 
It should be 
C. a hybrid 
I should buy 
D. a Honda Civic
The good news: 
The harsh light of data changes everything.
Big 
Lots of information, in 
flight and at rest. 
Fast Reliable 
Storage and retrieval 
in short timeframes. 
High availability in 
replication, consistency, 
and recoverability 
(Pick 
any two) 
Big Data’s 
iron triangle
Some tools and traps
The three threes 
Three 
assumptions 
What big bets are you making? 
•“People will answer questions” 
•“Organizers are frustrated with how to run conferences” 
•“We'll make money from parents” 
•“Amazon is reliable enough for our users.” 
Three actions 
to take 
What are you doing to make these assumptions happen (or 
identify they’re wrong and change course?) 
•Product enhancements 
•Marketing strategies 
Three experiments 
to run 
•Feature tests 
•Continuous deployment 
•A/B testing 
•Customer survey
The three threes 
Three 
assumptions 
Three actions 
to take 
Three experiments 
to run 
Monthly 
Weekly 
Daily 
Board, investors, 
founders 
Executive team 
Employees 
Strategy 
Tactics 
Execution
The three threes 
Three 
assumptions 
Three actions 
to take 
Three experiments 
to run 
Get more 
people 
Increase 
answer % 
Test better 
questions 
Change 
the UI 
Test 
timings 
Question 
s from 
Many people will 
answer questions
The problem-solution canvas 
CURRENT STATUS 
The Goal is to Learn 
• List key metrics you’re 
tracking, where they’re at, and 
compare with last few weeks 
• How are things trending? 
LAST WEEK’S LESSONS LEARNED 
AND ACCOMPLISHMENTS) 
• What did you learn last week? 
• What was accomplished? 
• On track: YES / NO?
The problem-solution canvas 
HYPOTHESIZED SOLUTIONS 
• List possible solutions that you’ll start 
working on next week. Rank them. 
• Why do you believe each solution will 
help you solve or complete solve the 
problem? 
METRICS / PROOF + GOALS 
Problem #1 (put name here) 
• Metrics you’ll use to measure whether 
or not the solutions are doing what you 
hoped (solving the problem) 
• List proof (qualitative) you’ll use as well 
• Define goals for the metric 
HYPOTHESIZED SOLUTIONS 
• List possible solutions that you’ll start 
working on next week. Rank them. 
• Why do you believe each solution will 
METRICS / PROOF + GOALS 
• Metrics you’ll use to measure whether 
or not the solutions are doing what you 
hoped (solving the problem) 
Problem #2 (put name here)
“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
Pic by Twodolla on Flickr. http://www.flickr.com/photos/twodolla/3168857844
ARCHIMEDES 
HAD TAKEN 
BATHS BEFORE.
Once, a leader convinced others 
in the absence of data.
Now, a leader knows 
what questions to ask.
Ben Yoskovitz 
byosko@gmail.com 
@byosko 
Alistair Croll 
acroll@gmail.com 
@acroll
Workshop: Systems diagrams 
and NCARB’s business
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
The mobile app! 
customer lifecycle! 
Ratings 
Reviews 
Search 
Leaderboards 
Purchases 
App store! 
App sales 
Downloads 
Installs 
Play 
Disengagement 
Reactivation 
Uninstallation 
Disengagement 
Account" 
creation 
Virality 
Downloads," 
Gross revenue 
ARPU 
Activation 
Churn, CLV 
In-app" 
purchases 
Legitimate 
Incentivized 
Fraudulent 
Ratings!
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Traction graphs 
Your business model 
The stage you’re at 
Your one metric 
... change often if 
you’re doing it right. 
So how do you track 
that over time?
Traction graphs 
Jan Feb Mar Apr May Jun 
Signups 
Conversion 
Churn 
per day 
rate 
rate 
Viral 
coefficient 
This axis changes for 
each metric
Traction graphs 
Jan Feb Mar Apr May Jun 
Signups 
Conversion 
Churn 
per day 
rate 
rate 
Viral 
coefficient 
0%
Use vanity to get to 
meaningful metrics 
Your goal is to produce 
outcomes 
If the outcomes require 
action, and vanity motivates 
actors, use it 
But show how the vanity 
metric is a leading indicator of 
the real one 
Web traffic 
Activation 
x 
Revenue 
Cart 
Size 
Conversion 
rate
Thinking Backwards: 
The Solution/Problem approach 
Mitigation & 
execution Act & measure 
Rob Van Haastrecht & Martin Scheepbouwer 
Identify a clear, 
known goal 
Get on same 
page with 
relevant facts 
Agree on goal 
KPIs 
Outline 
possible 
solutions 
Proposed 
solutions 
List assumptions 
(causes, actions, 
costs, risks) 
Agree on how 
to test/analyze 
them 
Answer/test 
them (MVP, 
etc.) 
See where 
uncertainty 
exists 
Validation 
& testing 
Estimate ability 
to mitigate 
risks (SWOT) 
Choose next 
best action 
(CxO) 
Staff team 
based on goal 
audacity 
results
Key points 
Intrapreneurship is about adjacent or transformative innovation 
Sustaining innovation focuses on the Five Mores, within the 
current product, market, method, and business model. 
Adjacent innovation may come from a new product, market, or 
method, but the same business model 
Disruptive innovation has different customers, KPIs, and models 
The difference between a rogue agent and a special operative is 
permission 
Portfolios need sourcing, filters, metrics, and socializing 
Balancing isolation and integration, R&D and M&A is contentious
Ben Yoskovitz 
byosko@gmail.com 
@byosko 
Alistair Croll 
acroll@gmail.com 
@acroll
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