45 minute presentation on Lean Analytics, presented at the Onlab facilities on April 8, 2013

1. Lean Analytics
Use data to build a
better business faster.
www.leananalyticsbook.com
@byosko | @acroll
@leananalytics

2. Silicon Valley
doesn’t love failure.

3. It just hates it
less than the alternative:

4. Making something nobody needs.

5. Most startups don’t know what they’ll be
when they grow up.
Freshbooks Mitel
was invoicing Wikipedia was a
Paypal
for a web was to be lawnmower
first built for company
design firm written by
Palmpilots experts only
Flickr
Hotmail Twitter Autodesk
was going to
was a was a made desktop
be an MMO
database podcasting automation
company company

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

8. Analytics is the measurement
of movement towards your
business goals.
http://www.flickr.com/photos/itsgreg/446061432/

9. Small business example:
Solare watches the
numbers
• Stage: Revenue
• Model: Retailer
• Solare is an Italian fine-dining restaurant under new management. The new team
is trying to identify the key metrics and leading indicators

10. Solare watches the numbers
• A line in the sand: Gross Revenue to Labor Cost
• Under 30% is good
• Below 24% is great
• Lower than 20% and you may be under-staffing, leading to dissatisfied
customers
• A leading indicator: Total covers is 5x reservations at 5PM
• If you have 50 reservations at 5, you’ll have 250 covers that night.
• This ratio varies by restaurant.

11. In a startup, the purpose of
analytics is to iterate to a
product/market fit before
the money runs out.

12. Qualitative or Quantitative
5 things you Exploratory or Reporting
need to know Vanity or Actionable
about metrics Correlated or Causal
Leading or Lagging

13. Qualitative Quantitative
Unstructured, Numbers and stats;
anecdotal, hard facts but less
revealing, hard to insight.
aggregate.
Warm and fuzzy. Cold and hard.
http://www.flickr.com/photos/zooboing/8388257248/ http://www.flickr.com/photos/x1brett/4665645157/

14. Simply: you can’t count smiles.
Discover qualitatively, prove quantitatively.
Qualitative is inspiration, quantitative is verification.

15. Exploratory Reporting
Speculative, trying Predictable, keeping
to find unexpected you abreast of
or interesting normal, managerial
insights. operations.
http://www.flickr.com/photos/50755773@N06/5415295449/ http://www.flickr.com/photos/elwillo/4737933662/

16. Donald Rumsfeld on analytics
Are facts which may be wrong and
we know should be checked against data.
know
we don’t Are questions we can answer by
reporting, which we should baseline
know & automate.
Things we
Are intuition which we should
we know quantify and teach to improve
don’t effectiveness, efficiency.
know
we don’t Are exploration which is where
unfair advantage and interesting
know epiphanies live.
(Or rather, Avinash Kaushik channeling Rumsfeld)

17. Vanity Actionable
Picks a
direction.
Makes you feel
good, but doesn’t
change how you’ll
act.
http://www.flickr.com/photos/lostseouls/807253220/ http://www.flickr.com/photos/aussiegall/6382775153/

18. A metric from the early, foolish days of the Web.
Hits
Count people instead.
Marginally better than hits. Unless you’re displaying
Page views
ad inventory, count people.
Is this one person visiting a hundred times, or are a
Visits
hundred people visiting once? Fail.
This tells you nothing about what they did, why they
Unique visitors
stuck around, or if they left.
Followers/ Count actions instead. Find out how many followers
friends/likes will do your bidding.
Time on site, or Poor version of engagement. Lots of time spent on
pages/visit support pages is actually a bad sign.
How many recipients will act on what’s in them?
Emails collected
Number of Outside app stores, downloads alone don’t lead to
downloads lifetime value. Measure activations/active accounts.

19. 2-sided market model:
AirBnB and photography
• Stage: Revenue
• Model: 2-sided marketplace
• Rental-by-owner marketplace that allows property owners to list and market
their houses. Offers a variety of related services as well.

20. AirBnB tests a hypothesis
• The hypothesis: “Hosts with professional photography will get more business.
And hosts will sign up for professional photography as a service.”
• Built a concierge MVP
• Found that professionally photographed listings got 2-3x more bookings than the
market average.
• In mid-to-late 2011, AirBnB had 20 photographers in the field taking pictures for
hosts.

21. NIGHTS BOOKED
10 million
8 million
6 million
20 photographers
4 million
2 million
2008 2009 2010 2011 2012

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

23. A few words on causality.
http://www.flickr.com/photos/roryfinneren/65729247

24. 50
37.5
25
12.5
0
1 2 3 4 5 6 7 8 9 10
Seat rentals
http://www.rvca.com/anp/wp-content/plugins/wp-o-matic/cache/57226_07+proof+1a+hb+beach+day.jpg

25. http://www.imdb.com/media/rm3768753408/tt0073195

26. http://www.flickr.com/photos/kapungo/2287237966

27. 10000
1000
100
10
1
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Ice cream consumption Drownings

28. http://www.flickr.com/photos/25159787@N07/3766111564

29. http://www.flickr.com/photos/wheressteve/3284532080

30. http://www.flickr.com/photos/wtlphotos/1086968783

31. 10000
1000
100
10
1
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Ice cream consumption Drownings Temperature

32. http://www.flickr.com/photos/stuttermonkey/57096884

33. http://www.flickr.com/photos/germanuncut77/3785152581

34. http://www.flickr.com/photos/fasteddie42/2421039207

35. Correlated Causal
Two variables that An independent
change in similar factor that directly
ways , perhaps impacts a
because they’re dependent one.
linked to something
else.
Summer
al
Ca
us
us
Ca
Correlated al Drowning
Ice cream
consumption

36. http://www.flickr.com/photos/bootbearwdc/1243690099/

37. Causality is a superpower, because it lets you
change the future.
Correlation lets you Causality lets you
predict the future change the future
“I will have 420 “If I can make more
engaged users and first-time visitors stay
75 paying customers on for 17 minutes I
next month.” will increase sales in
90 days.”
Optimize the
Find correlation Test causality
causal factor

38. Leading Lagging
Number today that Historical metric that
shows metric shows how you’re
tomorrow—makes doing—reports the
the news. news.

39. A leading indicator for e-commerce
How many of
your customers Then you are in Your customers You are just
Focus on
buy a second this mode will buy from you like
time in 90 days?
Low CAC,
1-15% Acquisition Once 70% high
of retailers checkout
15-30% Hybrid 2-2.5 20% Increasing
per year of retailers returns
Loyalty,
>30% Loyalty >2.5 10% inventory
per year of retailers expansion
(Thanks to Kevin Hilstrom for this.)

40. Think about a car
•60MPH is twice as fast as 30MPH
•Speed limits and mileage are well understood
•Kilometres are conveniently decimal; miles map to hours
•Ratios everywhere
•Miles travelled is good;
•Miles per hour is better;
•Accelerating or decelerating changes your gas pedal
•Custom metrics: “MPH divided by speeding tickets” as a
metric of “driving fast without losing my license”

41. The Lean Analytics Framework.

42. Eric Ries’
Three engines
Stickiness Virality Price
Approach Keep people Make people Spend revenue
coming back. invite friends. getting customers.
Math that Get customers How many they Customers are
matters faster than you tell, how fast worth more than
lose them. they tell them. they cost to get.

43. Dave McClure’s Pirate metrics
How do your users become aware of you?
Acquisition
AARRR
SEO, SEM, widgets, email, PR, campaigns, blogs ...
Do drive-by visitors subscribe, use, etc?
Activation Features, design, tone, compensation, affirmation ...
Does a one-time user become engaged?
Retention Notifications, alerts, reminders, emails, updates...
Do you make money from user activity?
Revenue Transactions, clicks, subscriptions, DLC, analytics...
Do users promote your product?
Referral Email, widgets, campaigns, likes, RTs, affiliates...

44. The five Stages of Lean Analytics
Empathy
The stage you’re at
Stickiness
Virality
Revenue
Scale

45. Example: a restaurant
• Empathy: Before opening, the owner first learns about the diners in its area,
their desires, what foods aren’t available, and trends in eating.
• Stickiness: Then he develops a menu and tests it out with consumers, making
frequent adjustments until tables are full and patrons return regularly. He’s giving
things away, testing things, asking diners what they think. Costs are high
because of variance and uncertain inventory.
• Virality: He starts loyalty programs to bring frequent diners back, or to
encourage people to share with their friends. He engages on Yelp and
Foursquare.
• Revenue: With virality kicked off, he works on margins—fewer free meals,
tighter controls on costs, more standardization.
• Scale: Finally, knowing he can run a profitable business, he pours some of the
revenues into marketing and promotion. He reaches out to food reviewers, travel
magazines, and radio stations. He launches a second restaurant, or a franchise
based on the initial one.

46. Example: a software company
• Empathy: The founder finds an unmet need, often because she has a background in a
particular industry or has worked with existing solutions that are being disrupted.
• Stickiness: She meets with an initial group of prospects, and signs contracts that look more
like consulting agreements, which she uses to build an initial product. She’s careful not to
commit to exclusivity, and tries to steer customers towards standardized solutions, charging
heavily for custom features. She supports the customers directly from the engineering team
until the product is stable and usable.
• Virality: Product in hand, she asks for references from satisfied customers, and uses them as
testimonials. She starts direct sales, and grows the customer base. She launches a user group,
and starts to automate support. She releases an API, encouraging third-party development and
scaling potential market size without direct development.
• Revenue: She focuses on growing the pipeline, sales margins, and revenues while controlling
costs. Tasks are automated, outsourced, or offshored. Feature enhancements are scored
based on anticipated payoff and development cost. Recurring license and support revenue
becomes an increasingly large component of overall revenues.
• Scale: She signs deals with large distributors, and works with global consulting firms to have
them deploy and integrate her tool. She attends trade shows to collect leads, carefully
measuring cost of acquisition against close rate and lead value.

47. Empathy
Get inside their head.

48. Mobile app model:
Localmind hacks Twitter
• Stage: Empathy
• Model: UGC/mobile
• Real-time question and answer platform tied to locations.
• Needed to find out if a core behavior—answering questions about a place—
happened enough to make the business real

49. Localmind hacks Twitter
• Before writing a line of code, Localmind was concerned that people would never
answer questions.
• This was their biggest risk: if questions went unanswered users would have a
terrible experience and stop using Localmind.
• Ran an experiment on Twitter
• Tracked geolocated tweets in Times Square
• Sent @ messages to people who had just tweeted, asking questions about
the area: how busy is it; is the subway running on time; is something open;
etc.
• The response rate to their tweeted questions was very high.
• Good enough proxy to de-risk the solution, and convince the team and
investors that it was worth building Localmind.

50. When it’s time to move on
• Have you conducted enough quality customer interviews to feel confident that
I’ve found a problem worth solving?
• Do you understand your customer well enough?
• Do you believe your solution will meet the needs of customers?

51. Stickiness
The dogs like the dogfood.

52. 1995 Hits
1997 Visits
1999 Visitors
2002 Conversions Who did you add? Where from? Why?
2010 Engagement What did they do? How did it benefit?
Who did you lose? Why did they leave?

53. Stickiness stage:
WP Engine discovers the
2% cancellation rate
• Stage: Stickiness
• Model: SaaS
• Wordpress hosting company founded in July 2010, it raised $1.2M in November
2011

54. WP-Engine discovers the 2%
cancellation rate
• All companies have cancellations, but founder Jason Cohen was alarmed that he
was losing a quarter of customers every year.
• Jason called customers himself. “Not everyone wanted to speak with me, but
enough people were willing to talk, even after they had left, that I learned a lot
about why they were leaving.”
• Asked around. Turns out 2% is best case for most hosting companies.
• Without this, the company would have been getting diminishing returns over-
optimizing churn; instead, they could focus on maximizing revenues or lowering
acquisition costs.

55. When it’s time to move on
•
Are people using the product as expected?
•
Define an active user. What percentage of your users/customers is active?
Write this down. Could this be higher? What can you do to improve engagement?
•
Evaluate your feature roadmap against the 7 questions to ask before building
more features. Does this change the priorities of feature development?
•
Evaluate the complaints you’re getting from users. How does this impact
feature development going forward?

56. Virality
I told two friends.

57. Virality stage:
Timehop’s content sharing
• Stage: Virality
• Model: Mobile app
• Social network around the past
• Focused on virality (but not necessarily the coefficient!)

58. The one metric that matters: 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

59. 3 kinds of virality
•
Inherent virality is built into the product, and happens as a function of use.
•
Artificial virality is forced, and often built into a reward system.
•
Word of mouth virality is simply conversations generated by satisfied users.

60. When it’s time to move on
• Are you using one of the three types of virality (inherent, artificial, word of mouth)
for your startup? Describe how. If virality is a weak aspect of your startup, write
down 3-5 ideas for how you could build more virality into your product.
• What’s your viral coefficient? Even if it’s below 1 (which it likely is), do you feel like
the virality that exists is good enough to help sustain growth and lower customer
acquisition costs?
• What’s your viral cycle time? How could you speed it up?

61. Revenue
Pour some of the money back into acquisition.

62. Revenue stage:
Backupify’s customer
lifecycle
• Stage: Revenue
• Model: SaaS
• Leading backup provider for cloud based data.
• The company was founded in 2008 by Robert May and Vik Chadha
• Has gone on to raise $19.5M in several rounds of financing.

63. Shifting to Customer Acquisition
Payback as a key metric
• 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

64. Sergio Zyman’s many “mores”
• If you’re dependent on physical, per-transaction costs (like direct sales, or
shipping products to a buyer, or signing up merchants) then more efficiently will
figure prominently on either the supply or demand side of your business model.
• If you’ve found a high viral coefficient, then more people makes sense, because
you’ve got a strong force multiplier added to every dollar you pour into customer
acquisition.
• If you’ve got a loyal, returning set of customers who buy from you every time,
then more often makes sense, and you’re going to emphasize getting them to
come back more frequently.
• If you’ve got a one-time, big-ticket transaction, then more money will help a lot,
because you’ve only got one chance to extract revenue from the customer and
need to leave as little money as possible on the table.
• If you’re a subscription model, and you’re fighting churn, then upselling
customers to higher-capacity packages with broader features to additional
subscribers within their organization is your best way of growing existing
revenues, so you’ll spend a lot of time on more stuff.

65. When it’s time to move on
You’re making money
You’re sustainable
You’re tracking growth metrics

66. Scale
Let others grow your business for you.

67. The hole in the middle
Differentiation Efficiency
Apple Costco
Here be
dragons
Your local
sustainable gluten-free
cupcake shop
Niche

68. Guerrilla Data-
marketing driven
learning
GROWTH
HACKING
Subversiveness

69. The trust equation
Your expertise & Do what you Are you one of
reputation; say; say what us? Morality &
certifications you do. personality.
Credibility + Reliability + Intimacy
Trustworthiness =
Self-orientation
What’s in it
for you?
Maister, Green and Galford

70. • 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)
(These are also great segments to analyze.)
(from the 2012 Growth Hacking conference)

71. 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
• At its most basic: Optimize a factor you think is correlated with growth

72. AirBnB and Craigslist

73. Getsatisfaction extortion

74. Coveting GMail invites

75. Farmville and wall posts

76. The five Stages of Lean Analytics
The business you’re in
E- 2-sided Mobile User-gen
SaaS Media
commerce market app content

77. UGC model:
Reddit goes from links to
community
• Stage: Virality
• Model: UGC
• A graduate of the first YCombinator class, reddit was acquired by Conde Nast
but left largely to its own devices. Thanks to a vibrant community and some
good guidance by its founders, it’s a traffic powerhouse.

78. Reddit goes from links to community
• Product evolution
• Started as a simple link-sharing site with voting
• Then added the ability to comment, with votes on comments
• Then created the ability to make “self-posts” rather than only comment on off-
site traffic
• Now self-posts are more than half of all posts

79. Reddit goes from links to community
• Revenue from ads and “reddit gold”
• Started as a joke, but turned into a revenue source
• One person paid $1000 for a month; some paid $0.01. Avg. around $4.
• Paying users get early access to features, since they’re an engaged beta

80. The five Stages of Lean Analytics
The business you’re in
E- 2-sided Mobile User-gen
SaaS Media
commerce market app content
Empathy
The stage you’re at
One Metric
Stickiness
Virality
Revenue That Matters.
Scale

81. Choose only one metric.

82. Yes, one metric.

83. It will soon change.

84. In a startup,
focus is hard to achieve.

85. Having only one metric
addresses this problem.

86. Metrics are like
squeeze toys.
http://www.flickr.com/photos/connortarter/4791605202/

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

88. B2B: Selling to the enterprise

89. The B2B stereotype
• Domain expert knows
industry and the problem
domain. Has a Rolodex;
proxy for customers.
http://www.techdigest.tv/2007/02/im_a_pc_im_a_ma.html
• Disruption expert knows
tech that will produce a
change Sees beyond the
current model.
Domain Disruption
expert expert Operations

90. Three typical approaches
Create a popular consumer Dropbox
Enterprise pivot product then pivot to tackle the
enterprise
Take an existing consumer or Yammer,
Copy and rebuild open source idea and make it MapR
enterprise-ready
Convince the enterprise to Taleo,
Disrupt a problem discard the old way because of Google
overwhelming advantages. Apps

91. Enterprise example:
Coradiant pivots from
service to appliance
• Stage: Revenue
• Model: Enterprise sale
• Coradiant started as a research firm, then moved into managed services. As the
market’s needs changed and data center preferences ossified, the company
switched from services to a physical appliance for web performance
management.

92. Coradiant pivots from service to
appliance
• Started as an MSP in colocated spaces, offering service and virtual
infrastructure.
• Data center partners became competitors
• Talked to customers, who liked the monitoring interface and performance
management
• Hibernated the company and turned the internal tool for monitoring web health
(OutSight) into an appliance
• MVP focused on the core value—what was actually happening on the wire
• Reporting etc. was introduced as Excel exports initially
• Made it easy to get data off the box to mitigate limited feature sets
• Scaled through channels and partnerships (Splunk, Akamai, etc.)

93. Lean Analytics lifecycle
for an enterprise-focused startup
Stage Do this Fear this
Consulting to test ideas and Lock-in, IP
Empathy bootstrap the business control, overfitting
Standardization and integration; Ability to
Stickiness shift from custom to generic integrate; support
Word of mouth, references, case Bad vibes;
Virality studies exclusivity
Growing direct sales, professional Pipeline, revenue
Revenue services, support recognition, comp
Channels, analysts, ecosystems, Crossing the
Scale APIs, vertically targeted products chasm; Gorillas

94. 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

95. Intrapreneur

96. Skunk Works for intrapreneurs
• The Lockheed Martin Skunk Works

97. Span of control and the railroads
• Daniel C. McCallum

98. The BCG matrix
• How businesses think
about products or Question marks! increase
Pivot to
Stars!
companies (low market share, market (high growth rate,
share
high growth rate)
through high market share)
May be the next big thing. virality, What everyone wants. As
• Lean is about moving Consumes investment, but attention
market invariably stops
will require money to growing, should become
up and to the right Growth rate
increase market share.
cash cows.
Milk with
Pivot to Pivot to
revenue
redefine problem/ increase growth
optimization as
solution through rate through
growth slows
empathy
disruption
Dogs! Cash cows!
(low market share, (high market share,
low growth rate)
low growth rate)
Barely breaks even, may Boring sources of cash, to
be a distraction from better be milked but not worth
opportunities. Sell off or additional investment.
shut down.
Market share

99. Intrapreneur example:
P&G changes the mop
instead of the soap
• Stage: Empathy
• Model: Retail/consumer packaged goods
• P&G is constantly looking for better soaps. But innovation was slowing.
Frustrated, they hired a design team to help them.

100. P&G changes the mop
instead of the soap
• Heavy internal investment in R&D, but limited results
• Brought in an outside agency (Continuum) to help
• The team watched people as they mopped, recording and iterating their
research approach
• Watched someone pick up spilled coffee. Rather than mopping, the person
swept up with a broom, then wiped with a cloth
• Realized the mop, not the liquid, mattered
• Studied the makeup of floor dirt; realized much of it is dust
• Swiffer is a $500M innovation in a stalled industry

101. The Lean Analytics lifecycle
for an Intrapreneur
Stage Do this Fear this
Get buy-in Political fallout
Beforehand
Find problems; don’t test demand. Entitled, aggrieved
Empathy Skip the business case, do analytics customers
Know your real minimum based on Hidden “must haves”,
Stickiness expectations, regulations feature creep
Build inherent virality in from the Luddites who don’t
Virality start; attention is the new currency understand sharing
Consider the ecosystem, channels, Channel conflict,
Revenue and established agreements resistance, contracts
Hand the baton to others gracefully Hating what happens
Scale to your baby

102. Metrics in practice:
The Lean Analytics Cycle
Success! Pick OMTM Draw a line
in the sand
Pivot or
give up Draw a new line Find a
potential
Try again improvement
Did we move
the needle? Without With data:
data: make a find a
good guess commonality
Design a test
Measure
the results Hypothesis
Make changes
in production

103. Virality stage:
Circle of Moms finds an
engaged market
• Stage: Stickiness
• Model: UGC
• Launched as Circle of Friends in 2007, it was a way for small groups to interact
atop Facebook’s platform; but when engagement wasn’t good enough, the
founders decided to dig deeper.

104. The problem: 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

105. What Circle of Moms found
• 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

106. Virality stage:
qidiq streamlines invites
• Stage: Virality
• Model: SaaS
• Tool to poll small groups, built in the Year One Labs accelerator

107. Initial design Redesigned workflow
Survey owner adds recipient to group Survey owner adds recipient to group
70-90% RESPONSE RATE
Survey owner asks question Survey owner asks question
Recipient gets invite Recipient reads survey question
10-25% RESPONSE RATE
Recipient installs mobile app Recipient responds to question
Recipient sees survey results
Recipient creates account, profile
Recipient can edit profile, view past (Later, if needed…)
questions, etc.
Recipient visits website
Recipient reads survey question
Recipient has no password!
Recipient responds to question
Recipient does password recovery
Recipient sees survey results
One-time link sent to email
Recipient creates password
Recipient can edit profile, view past
questions, etc.

108. “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

109. Pic by Twodolla on Flickr. http://www.flickr.com/photos/twodolla/3168857844

110. ARCHIMEDES
HAD TAKEN
BATHS BEFORE.

111. Once, a leader convinced others in
the absence of data.

112. Now, a leader knows what
questions to ask.

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