Lean Analytics: Using Data to Build a Better Business Faster

Lean Analytics
Lean Startup conference
San Francisco, November 16 2015
@acroll

Don’t sell what you can make. Make what you can sell.
Kevin Costner is a lousy entrepreneur.

The core of Lean
is iteration.

Waterfall approach
You know the problem and the solution.

Known set of
requirements
Known ways to satisfy
them
Spec Build Test Launch

Agile methodologies
Know the problem, ﬁnd the solution

Known set of
requirements
Unclear how to satisfy
them
Build Test LaunchViable?Problem 
statement
Adjust
Sprints
Unknown set of
requirements

Lean approach
First, know that you don’t know.

Possible problem
space
Product/
market
hypothesis
Trial startup
Product/
market
hypothesis
Trial startup
Product/market
hypothesis
Trialstartup
Product/market
hypothesis
Trialstartup
You are
herePIVOT

Unfortunately,
we’re all liars.

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.

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

Gottfried von Leibniz
was a geek just like you.

First calculator

(stepped reckoner)
One of the ﬁrst
to recognize the
importance of
binary.
“I thought again
about my early plan
of a new language or
writing-system of
reason, which could
serve as a
communication tool
for all diﬀerent
nations..”

The best of all possible
worlds is the one in
which the fewest
starting conditions
produce the greatest
variety of outcomes.

Rethinking the fundamentals is how
you discover new models.

What’s the
biggest
problem 
in a hair
salon?

The empty chair.
Knowing this, how
might you change
the client/customer
relationship?

Finding the tipping points of markets.

“Using Cue, you can tell if someone
has the ‘ﬂu in 10 minutes.”
http://tiltthewindmill.com/when-can-becomes-must/

“Using Cue, you must tell if someone
has the ‘ﬂu in 10 minutes…
…or Johnny can’t come on the school trip.”

Quantifying the riskiest parts.

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,
Martin Greenberger, ed., The Johns Hopkins Press, 1971.)Herbert Simon

Lit motors tests the risky part

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.

Some fundamentals.
Analytics, performance, aggregation, and the right metrics

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
bad 
metric.
If a metric won’t change how
you behave, it’s a
h"p://www.ﬂickr.com/photos/circasassy/7858155676/

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.)

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
(Or rather, Avinash Kaushik channeling Rumsfeld)
Things we
know
don’t 
know
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.

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.)
☀
☁

Which of these two companies
is doing better?

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?

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.

1
10
100
1000
10000
Ice cream consumption Drownings
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec

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/

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)
Some examples
(From the 2012 Growth Hacking conference. http://growthhackersconference.com/)

Why is Nigerian spam so badly
written?

Aunshul Rege of Rutgers University, USA in 2009
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.”
1000 emails
1-2 responses
1 fool and their money, parted.
Bad language (0.1% conversion)
Gullible (70% conversion)
1000 emails
100 responses
1 fool and their money, parted.
Good language (10% conversion)
Not-gullible (.07% conversion)
This would be horribly
ineﬃcient since
humans are involved.

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.

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...

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

Six business model archetypes.
E-commerce SaaS Media
Mobile 
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
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

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

In a startup, focus is hard to achieve.

Having only one metric
addresses this problem.

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
SaaS Media
Mobile 
app
User-gen 
content
2-sided 
market
Interviews; qualitative results; quantitative scoring; surveys
Loyalty,
conversion
CAC, shares,
reactivation
Transaction,
CLV
Affiliates,
white-label
Engagement,
churn
Inherent
virality, CAC
Upselling,
CAC, CLV
API, magic #,
mktplace
Content,
spam
Invites,
sharing
Ads,
donations
Analytics,
user data
Inventory,
listings
SEM, sharing
Transactions,
commission
Other
verticals
(Money from transactions)
Downloads,
churn, virality
WoM, app
ratings, CAC
CLV,
ARPDAU
Spinoffs,
publishers
(Money from active users)
Traffic, visits,
returns
Content
virality, SEM
CPE, affiliate
%, eyeballs
Syndication,
licenses
(Money from ad clicks)

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
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

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% 
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

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

Who is worth more?
Today
A
Lifetime:
$200
Roberto Medri, Etsy
B
Lifetime:
$200
Visits

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

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

Gut instinct (hypothesis)
Professional photography helps AirBnB’s business
SRSLY?

“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

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 interaction Customer satisfaction KPI dashboardsUser segmentation
User analytics Spying on users

The mobile app!
customer lifecycle!
Ratings
Reviews
Search
Leaderboards
Purchases
Downloads
Installs
Play
Disengagement
Reactivation
Uninstallation
Disengagement
Account"
creation
Virality
Downloads,"
Gross revenue
ARPU
App sales
Activation
Churn, CLV
In-app"
purchases
Appstore!
Incentivized
Legitimate
Fraudulent
Ratings!

Intrapreneurship in large
organizations

(http://csinvesting.org/2012/01/06/fortune-500-extinction/)
F500 Life
Expectancy
Growth by entering
a new business 95 
% fail
Corporate
Strategy Board
99 
% fail
Clay
Christensen
75
years
15
years
1950 2010...

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.

Intrapreneurship:
The difference between a rogue agent
and a special operative is permission.

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.

In other words, if your job is change you
have your work cut out for you.

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
OPTIMIZATION 
OF CURRENT
METRICS

YOU ARE
HERE
GLOBAL 
MAXIMUMINNOVATION 
WITH NEW 
RULES

YOU ARE
HERE
SHORT-TERM INVESTORS 
HATE GOING DOWNHILL

In a big company,
analytics replaces opinion with fact.

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).
2011 MIT study of 179 large publicly traded ﬁrms

Times a song in “heavy
rotation” is played daily
2007 2012
266

Current 
state
Business
optimization
(ﬁve mores) 
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, 
only better.
Explore what’s 
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
More eﬃciently
Supply chain optimization
Per-transaction cost reduction
Loyal customer base that returns
Demand prediction, notiﬁcation
Maximum shopping cart
Price skimming/tiering
Highly viral offering
Low incremental order costs
Inventory increase
Gifting, wish lists

Blizzard extends the
lifespan of WOW
Early 
adopters
Rapid 
growth
Market 
saturation
The infamous S-curve
(Product lifecycle, Bass diffusion curve, etc.)

lifespan of WOW

lifespan of WOW
Fixing this: sustaining growth with novelty
Product & market innovation
(“New & improved!”)

lifespan of WOW
WOW
Burning 
Crusade
Wrath of 
the Lich King
Mists of 
PandariaCataclysm
Warlords of
Draenor

Adjacent innovation is about changing
one part of the model in a way that
alters the value network.

Experiment with product, market,
and method.

Product
(new “what”)
Market
(new “who”)
Method
(new “how”)
3 kinds of
innovation

Adjacent product
to the same
market in the
same way

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

Some street-smart 
tactics that work

“How quickly can you test this” 
should be a criteria.
You’re not building a product, 
you’re ﬁguring out what product to build.

How easily can you test these out?

Take baby steps
How you get there matters as much as where you’re going.

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
of SMS (160
characters) and
username (20
characters.)
http://i.i.cbsi.com/cnwk.1d/i/tim/2011/11/18/
sms_screen_twitter_activity_stream_270x405.png

Let them ask for an out
Detecting SaaS churn early without hurting cashﬂow

The tradeoff
Charge a monthly fee Charge annual fee up front
Find out if they hate it sooner, when
they cancel on ﬁrst billing cycle.
No need to pay back CAC; cash you
can use right away.
Takes months to recoup the money
you spent acquiring them.
May be a zombie user who vanishes
when the year is up.

They’re happy, you keep your
money, goodwill for offering.
They’re unsatisﬁed, you made it
right, they tell you why, you learn.
The solution—because the goal is to
learn, not to trap customers.
Annual fee, with an out
1. Oﬀer an annual, discounted fee.
2. After a couple of weeks, ask if
they’d like a refund.

Protip: Campaigns that don’t suck.

How to build a marketing campaign
http://www.yearonelabs.com/three-questions-all-marketers-must-answer/
When will you decide if it worked, and adjust?
Who are you
targeting?
Size, reachability, 
homogeneity.
What do you
want them to
do?
Speciﬁc,
measurable 
call to action.
Why should
they do it?
Laid, paid, made, 
or afraid;
message 
ﬁts their mindset.
How will you
know if they
did?
Analytics, 
instrumentation.

The whole point of digital is personal
Segment 1
User segment 
(who)
Segment 2
Segment 3
Goal 
(what)
Goal 1
Goal 2
Goal 3
Motivation 
(why)
Goal 1
Goal 2
Goal 3

http://www.thirdwunder.com/funnels-are-a-horrible-metaphor/Photo Credit: Patrick McGarvey
More like this.

Bounces Non- 
creators
Non- 
payers
Churn
Signup 
rate
Engagement 
level
Conversion 
rate
Visitors
Subscribers
Engaged users
Paying 
customers
Leaky buckets are a
bad metaphor

Bounces Non- 
creators
Non- 
payers
Churn
Improve stickiness; call-to-action optimization; 
A/B page testing; picking better traﬃc sources
Notiﬁcations; updates; reactivating users; 
segmenting those who are engaged.
Usage caps, natural upselling; 
premium features
Better support; credit card renewal;
naturally sustained features

Maybe they don’t love you 
like they said they do.
N
Your offering doesn’t make them want to 
brag or their contact isn’t really a friend
N
Advocates can’t learn & convey 
your message easily
N
They don’t trust you entirely
N
Woohoo! Scalable, viral, 
explainable product!
Y
Get a meeting
Y
Grab the phone
Y
They pitch it
Y
Call them now?
Y
Intro to a friend?
Interview

Use outliers and missed searches to
hunt for good ideas & adjacencies
(Multi-billion-dollar hygiene product company)
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.

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

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.

Focus on the desired behavior, not just
the information.
http://www.psychologytoday.com/blog/yes/
200808/changing-minds-and-changing-towels
26% increase in towel
re-use with an appeal
to social norms; 33%
increase when tied to
the speciﬁc room.
Energy Conservation “Nudges” and Environmentalist
Ideology: Evidence from a Randomized Residential Electricity
Field Experiment - Costa & Kahn 2011
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.

http://www.ﬂickr.com/photos/bootbearwdc/1243690099/
Think subversively.

“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.

Alistair Croll
acroll@gmail.com
@acroll
Ben Yoskovitz
byosko@gmail.com
@byosko

Lean Analytics: Using Data to Build a Better Business Faster

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