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http://www.michaelrwolfe.com
michaelrwolfe
michael.wolfe@stanfordalumni.org
Innovation as applied to early
stage startups
Our journey today
This is the story of a successful
B2B Silicon Valley startup
launching a new product into
a new market.
!
I will talk about how we
validated the idea, designed
the solution, and how we
successfully grew and exited
the company.
I've seen the story many
times
As a founder, exec, or
advisor to a bunch of
startups
!
The same recipe doesnā€™t
works twice, but patterns
emerge
Let me take you back to
2002
The economy wasnā€™t so hot
"e-business"
is still new
Companies still reasoning
about risks and
opportunities
Enter our intrepid band of
tech dudes
Joseph Ansanelli, CEO!
ā€¢ Multi-time founder/CEO, Apple, product
management and marketing
Kevin Rowney, CTO!
ā€¢ Security Architect, Netcentives
Michael Wolfe, VP Engineering!
ā€¢ Several startups, Entrepreneur in
Residence at Benchmark Capital
Kevinā€™s experience leads him
to an insight
Companies spend a great deal of
money keeping bad guys out of their
network
ā€¢ Firewalls
ā€¢ Intrusion detection
ā€¢ Anti-malware
But insiders who has access to the
network can easily take data out of it
ā€¢ Via email, chat, web posts
ā€¢ Via thumb drives, DVDs, or
laptops
ā€¢ Either accidentally or maliciously
A kernel of an idea
Build software that allows
companies to prevent the loss of
conļ¬dential data from the inside
It might seem obvious now
ā€¢ Legal risk
ā€¢ Reputational risk
ā€¢ Regulatory
compliance
ā€¢ And other Truly Bad
Things
!
But was it then?
Did we do this?
1. Raise venture capital
2. Hire some engineers
3. Build the product
4. Hire marketing and
sales people
5. The product ļ¬‚ies off the
shelves
6. IPO!
It doesnā€™t work that way
The graveyards
are full of startups
with products that
customers
"should have
wanted"
It usually goes wrong
Too early - there will be a market, but not yet
Too late - competitors already addressing the
problem, or customer has workaround or internal
solution
Not a "top 3" priority for the customer
Building the wrong feature set
Product canā€™t be built or is delayed!
Pricing, messaging, and distribution never ļ¬gured
out
The industry has gotten
smarter about this
Growing recognition that startups are completely different
than established businesses
A startup is an experiment
ā€¢ Form hypothesis
ā€¢ Find fastest/cheapest
way to validate
hypothesis
ā€¢ Test and measure
ā€¢ Adjust, Ā«pivotĀ» if
needed
I will walk through our:
Questions
What were the most important questions we had to
answer
!
Validation
How we got the answer to each of those questions
!
Learnings
What we learned and how we adjusted
Question #1:
!
Do companies care about the
loss of conļ¬dential data
enough to invest in this market?
Careful before you say "yes"
When is the last time you sent an encrypted email?
Pre-product validation
ā€¢ Get meetings with potential customers
ā€¢ Interview them on their problems and desired
solutions
ā€¢ Show them mock-ups, examples, anything
tangible that will get them talking
ā€¢ Ask for follow-up meetings, repeat
Getting the meetings
ā€¢ Work your personal network
ā€¢ LinkedIn, Twitter, comment
threads, blogs
ā€¢ Put up a landing page, drive
trafļ¬c, gather names
ā€¢ Cold call, email, twitter - be
persistent
!
Requires "hustle" and may be
painful or uncomfortable
Getting them to respond
ā€¢ Be clear it is not a sales call
ā€¢ Flatter them - you want their feedback and
advice
ā€¢ Entice them with the opportunity to work with
a cutting edge company - more interesting
than their usual meetings
ā€¢ Meet them anywhere, anytime
ā€¢ Ask for a short amount of time - theyā€™ll give
you more if they are interested
Running the meeting
ā€¢ Listen, listen, listen
ā€¢ Don't try to "sell" your solutions
ā€¢ Ask open-ended questions
ā€¢ Bring screenshots/slides/mockups - get their
reaction
ā€¢ Close them on another meeting
Sample questions
ā€¢ ā€œTalk us through your top priorities and
projectsā€
ā€¢ ā€œTell us about your existing infrastructureā€
ā€¢ ā€œHave you experienced this problemā€
ā€¢ ā€œHow are you solving this problem todayā€
ā€¢ ā€œForce rank the following capabilitiesā€
ā€¢ I'll show you some prototypes - give me
your reactionā€
?
What we heard
"This is something
we'd seriously
consider"
"We have been
building homegrown
solutions to address
this"
"We are talking about
this problem at the
board level"
"Weā€™d try it if you built
it. Put us on your beta
list"
Takeaway:
!
It is never too early to talk to
customers.
!
If you canā€™t reach customers now, why
do you think you can reach them later?
!
Build the company alongside a few key
customers.
Then we raised money
ā€¢ We raised a $5M series A ļ¬nancing
based on this feedback.
ā€¢ Normally youā€™d raise later than this, but
we already had ļ¬rms predisposed to
give us money.
ā€¢ Today it would be typical for a company
to get much further along before raising
a round
ā€¢ Cloud computing and low-cost
distribution channels allow companies
to get much further along before raising
Oh, we also named the
company
Next Question:
!
What customer segments care
the most about the problem?
Which verticals?
ā€¢ Technology
ā€¢ Oil and Gas
ā€¢ Entertainment
ā€¢ Financial services
ā€¢ Manufacturing
ā€¢ Automotive
What tier?
Start at large companies!
Larger budgets
Most public scrutiny
Largest amount of data to
protect
ā€œName brandā€ references
!
!
Start small, build up!
Less demanding
Shorter sales cycle
More innovative
Gain experience before
going big
What we learned
The strongest feedback came from
large companies in regulated
industries
In this market, the larger companies
were more, not less innovative
Drivers were regulatory and
reputational risk.
ā€œKeep me off of the front page of the
WSJā€
What we did
Laser focus on large companies in regulated
industries, primarily protecting customer data
De-emphasized the rest and even ignored some
smaller companies that came to us ready to buy
This focus meant we would lose deals that werenā€™t
in our sweet spot
Takeaway:
!
Focus, focus, focus
!
If you try to help everyone,
you will help no one
!
This means losing business
!
And thatā€™s OK
Next Question:
!
What kinds of data do
customers care the most about
protecting?
Data types
ā€¢ Employee data?
ā€¢ Customer data?
ā€¢ Intellectual property?
ā€¢ Strategic plans?
ā€¢ Financials?
How we found out
ā€¢ Built trust with prospects
ā€¢ Spent time with them as they walked us through
actual internal breaches and their costs
ā€¢ We showed them several kinds of policies and
got their reactions to each
ā€¢ Found that almost everything they talked about
had to do with consumer PII (personally
identiļ¬able information)
What we did next
We pivoted away from an
earlier idea - tagging
emails and documents
We focused instead on
one that could identify
and protect large
databases of consumer
data
Contrarian move - at the
time DRM was the next
new thing
Next Question: what threat do
companies care the most about?
ā€¢ Data escaping via outbound
email
ā€¢ Data escaping via web posts /
web mail
ā€¢ Data escaping via FTP, P2P
networks, other internet ļ¬le
transfer
ā€¢ Data escaping via thumb
drives, DVDs, and lost laptops
Do they want block incidents
or simply monitor + notify?
Block!
Prevent the incident from
happening
Avoid cost of the incident
Provide assurance to
customers
!
Monitor!
Less disruptive
Less expensive
Allows education and
policy changes in
response to incidents
Our minimum viable product
We did Not
Focus on data loss
Malware, anti-porn, URL
monitoring
Focus on customer data
Documents, intellectual
property, ļ¬nancials
Email only Webmail, thumbdrives, FTP
Monitoring only Endpoint blocking
Tools for remediation Simply logging them
Great reporting Reporting as afterthought
Focus on large companies Sell to anyone with money
Some competitors did ā€œmoreā€œ but ended up losing
What happened next
ā€¢ Responded to an RFP from
Bank of America
ā€¢ Focused and won the deal
ā€¢ ~$500K, over time grew to
several million
ā€¢ Needed to promise several
near-term features to win the
deal
ā€¢ Made them referencable
and a champion
Takeaway:
!
The ā€œminimum viable productā€ can often
be way more minimal than you think.
!
Do a few things, and do them right.
!
Customers will want more, but if you are
solving an important problem, they will
be patient.
Example MVPs
ā€¢ Created an ā€œexplainer videoā€
demoing the product, got > 100K
signups, didnā€™t ship product until 18
months later
ā€¢ Went to shoe shops, took pictures of
shoes, put online. When people
ordered, went back to shop to get
shoes.
ā€¢ Started with one plane and one
route. Perfected their system and
then expanded
Would you
ship a phone
without cut
and paste?
Other things we learned
ā€¢ Opportunity to sell high - to the CSO/CIO level
ā€¢ Bring in experienced enterprise sales reps
ā€¢ Partners were not a large factor - we had to
evangelize/sell ourselves
ā€¢ Employees with security experience often did
not do well in the company
This sure helped
Expanded to more verticals
Added products
We obsessed about
Team - Putting tons of time and
money into recruiting, and removing
bad hires
Training and team building -
constant trainings and company
events
Transparency - everyone at the
company had access to almost all
information
Customer success - making them
reference able and our champions
Planning and forecasting - quarterly
replans, goals and objectives
Grew and grew
2003 - $500K in bookings, 1 customer
2004 - $3.5M, 7 customers
2005 - $13.5M, 30 customers
2006 - $27M, Europe ofļ¬ce
2007 - $50M, 175 employees
!
FTW
Key takeaways
ā€¢ Validate, validate, validate
ā€¢ Build your product with customers. Seek face
to face meetings, not just metrics
ā€¢ Seek focus
ā€¢ Get an MVP to market as quickly as possible
and then iterate!
ā€¢ Obsess about people
http://www.michaelrwolfe.com
michaelrwolfe
michael.wolfe@stanfordalumni.org
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Lecture on Innovation at Startups at ESADE

  • 2. Our journey today This is the story of a successful B2B Silicon Valley startup launching a new product into a new market. ! I will talk about how we validated the idea, designed the solution, and how we successfully grew and exited the company.
  • 3. I've seen the story many times As a founder, exec, or advisor to a bunch of startups ! The same recipe doesnā€™t works twice, but patterns emerge
  • 4. Let me take you back to 2002
  • 6. "e-business" is still new Companies still reasoning about risks and opportunities
  • 7. Enter our intrepid band of tech dudes Joseph Ansanelli, CEO! ā€¢ Multi-time founder/CEO, Apple, product management and marketing Kevin Rowney, CTO! ā€¢ Security Architect, Netcentives Michael Wolfe, VP Engineering! ā€¢ Several startups, Entrepreneur in Residence at Benchmark Capital
  • 8. Kevinā€™s experience leads him to an insight Companies spend a great deal of money keeping bad guys out of their network ā€¢ Firewalls ā€¢ Intrusion detection ā€¢ Anti-malware But insiders who has access to the network can easily take data out of it ā€¢ Via email, chat, web posts ā€¢ Via thumb drives, DVDs, or laptops ā€¢ Either accidentally or maliciously
  • 9. A kernel of an idea Build software that allows companies to prevent the loss of conļ¬dential data from the inside
  • 10. It might seem obvious now ā€¢ Legal risk ā€¢ Reputational risk ā€¢ Regulatory compliance ā€¢ And other Truly Bad Things ! But was it then?
  • 11. Did we do this? 1. Raise venture capital 2. Hire some engineers 3. Build the product 4. Hire marketing and sales people 5. The product ļ¬‚ies off the shelves 6. IPO!
  • 12. It doesnā€™t work that way The graveyards are full of startups with products that customers "should have wanted"
  • 13. It usually goes wrong Too early - there will be a market, but not yet Too late - competitors already addressing the problem, or customer has workaround or internal solution Not a "top 3" priority for the customer Building the wrong feature set Product canā€™t be built or is delayed! Pricing, messaging, and distribution never ļ¬gured out
  • 14. The industry has gotten smarter about this Growing recognition that startups are completely different than established businesses
  • 15. A startup is an experiment ā€¢ Form hypothesis ā€¢ Find fastest/cheapest way to validate hypothesis ā€¢ Test and measure ā€¢ Adjust, Ā«pivotĀ» if needed
  • 16. I will walk through our: Questions What were the most important questions we had to answer ! Validation How we got the answer to each of those questions ! Learnings What we learned and how we adjusted
  • 17. Question #1: ! Do companies care about the loss of conļ¬dential data enough to invest in this market?
  • 18. Careful before you say "yes" When is the last time you sent an encrypted email?
  • 19. Pre-product validation ā€¢ Get meetings with potential customers ā€¢ Interview them on their problems and desired solutions ā€¢ Show them mock-ups, examples, anything tangible that will get them talking ā€¢ Ask for follow-up meetings, repeat
  • 20. Getting the meetings ā€¢ Work your personal network ā€¢ LinkedIn, Twitter, comment threads, blogs ā€¢ Put up a landing page, drive trafļ¬c, gather names ā€¢ Cold call, email, twitter - be persistent ! Requires "hustle" and may be painful or uncomfortable
  • 21. Getting them to respond ā€¢ Be clear it is not a sales call ā€¢ Flatter them - you want their feedback and advice ā€¢ Entice them with the opportunity to work with a cutting edge company - more interesting than their usual meetings ā€¢ Meet them anywhere, anytime ā€¢ Ask for a short amount of time - theyā€™ll give you more if they are interested
  • 22. Running the meeting ā€¢ Listen, listen, listen ā€¢ Don't try to "sell" your solutions ā€¢ Ask open-ended questions ā€¢ Bring screenshots/slides/mockups - get their reaction ā€¢ Close them on another meeting
  • 23. Sample questions ā€¢ ā€œTalk us through your top priorities and projectsā€ ā€¢ ā€œTell us about your existing infrastructureā€ ā€¢ ā€œHave you experienced this problemā€ ā€¢ ā€œHow are you solving this problem todayā€ ā€¢ ā€œForce rank the following capabilitiesā€ ā€¢ I'll show you some prototypes - give me your reactionā€ ?
  • 24. What we heard "This is something we'd seriously consider" "We have been building homegrown solutions to address this" "We are talking about this problem at the board level" "Weā€™d try it if you built it. Put us on your beta list"
  • 25. Takeaway: ! It is never too early to talk to customers. ! If you canā€™t reach customers now, why do you think you can reach them later? ! Build the company alongside a few key customers.
  • 26. Then we raised money ā€¢ We raised a $5M series A ļ¬nancing based on this feedback. ā€¢ Normally youā€™d raise later than this, but we already had ļ¬rms predisposed to give us money. ā€¢ Today it would be typical for a company to get much further along before raising a round ā€¢ Cloud computing and low-cost distribution channels allow companies to get much further along before raising
  • 27. Oh, we also named the company
  • 28. Next Question: ! What customer segments care the most about the problem?
  • 29. Which verticals? ā€¢ Technology ā€¢ Oil and Gas ā€¢ Entertainment ā€¢ Financial services ā€¢ Manufacturing ā€¢ Automotive
  • 30. What tier? Start at large companies! Larger budgets Most public scrutiny Largest amount of data to protect ā€œName brandā€ references ! ! Start small, build up! Less demanding Shorter sales cycle More innovative Gain experience before going big
  • 31. What we learned The strongest feedback came from large companies in regulated industries In this market, the larger companies were more, not less innovative Drivers were regulatory and reputational risk. ā€œKeep me off of the front page of the WSJā€
  • 32. What we did Laser focus on large companies in regulated industries, primarily protecting customer data De-emphasized the rest and even ignored some smaller companies that came to us ready to buy This focus meant we would lose deals that werenā€™t in our sweet spot
  • 33. Takeaway: ! Focus, focus, focus ! If you try to help everyone, you will help no one ! This means losing business ! And thatā€™s OK
  • 34. Next Question: ! What kinds of data do customers care the most about protecting?
  • 35. Data types ā€¢ Employee data? ā€¢ Customer data? ā€¢ Intellectual property? ā€¢ Strategic plans? ā€¢ Financials?
  • 36. How we found out ā€¢ Built trust with prospects ā€¢ Spent time with them as they walked us through actual internal breaches and their costs ā€¢ We showed them several kinds of policies and got their reactions to each ā€¢ Found that almost everything they talked about had to do with consumer PII (personally identiļ¬able information)
  • 37. What we did next We pivoted away from an earlier idea - tagging emails and documents We focused instead on one that could identify and protect large databases of consumer data Contrarian move - at the time DRM was the next new thing
  • 38. Next Question: what threat do companies care the most about? ā€¢ Data escaping via outbound email ā€¢ Data escaping via web posts / web mail ā€¢ Data escaping via FTP, P2P networks, other internet ļ¬le transfer ā€¢ Data escaping via thumb drives, DVDs, and lost laptops
  • 39. Do they want block incidents or simply monitor + notify? Block! Prevent the incident from happening Avoid cost of the incident Provide assurance to customers ! Monitor! Less disruptive Less expensive Allows education and policy changes in response to incidents
  • 40. Our minimum viable product We did Not Focus on data loss Malware, anti-porn, URL monitoring Focus on customer data Documents, intellectual property, ļ¬nancials Email only Webmail, thumbdrives, FTP Monitoring only Endpoint blocking Tools for remediation Simply logging them Great reporting Reporting as afterthought Focus on large companies Sell to anyone with money Some competitors did ā€œmoreā€œ but ended up losing
  • 41. What happened next ā€¢ Responded to an RFP from Bank of America ā€¢ Focused and won the deal ā€¢ ~$500K, over time grew to several million ā€¢ Needed to promise several near-term features to win the deal ā€¢ Made them referencable and a champion
  • 42. Takeaway: ! The ā€œminimum viable productā€ can often be way more minimal than you think. ! Do a few things, and do them right. ! Customers will want more, but if you are solving an important problem, they will be patient.
  • 43. Example MVPs ā€¢ Created an ā€œexplainer videoā€ demoing the product, got > 100K signups, didnā€™t ship product until 18 months later ā€¢ Went to shoe shops, took pictures of shoes, put online. When people ordered, went back to shop to get shoes. ā€¢ Started with one plane and one route. Perfected their system and then expanded
  • 44. Would you ship a phone without cut and paste?
  • 45. Other things we learned ā€¢ Opportunity to sell high - to the CSO/CIO level ā€¢ Bring in experienced enterprise sales reps ā€¢ Partners were not a large factor - we had to evangelize/sell ourselves ā€¢ Employees with security experience often did not do well in the company
  • 47. Expanded to more verticals
  • 49. We obsessed about Team - Putting tons of time and money into recruiting, and removing bad hires Training and team building - constant trainings and company events Transparency - everyone at the company had access to almost all information Customer success - making them reference able and our champions Planning and forecasting - quarterly replans, goals and objectives
  • 50. Grew and grew 2003 - $500K in bookings, 1 customer 2004 - $3.5M, 7 customers 2005 - $13.5M, 30 customers 2006 - $27M, Europe ofļ¬ce 2007 - $50M, 175 employees !
  • 51. FTW
  • 52.
  • 53. Key takeaways ā€¢ Validate, validate, validate ā€¢ Build your product with customers. Seek face to face meetings, not just metrics ā€¢ Seek focus ā€¢ Get an MVP to market as quickly as possible and then iterate! ā€¢ Obsess about people