http://www.michaelrwolfe.com

michaelrwolfe

michael.wolfe@stanfordalumni.org

Innovation as applied to early stage startups

Our journey todayThis 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 doesn’t works twice, but patterns emerge

Let me take you back to 2002

The economy wasn’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!• Multi-time founder/CEO, Apple, product

management and marketing

Kevin Rowney, CTO!• Security Architect, Netcentives

Michael Wolfe, VP Engineering!• Several startups, Entrepreneur in

Residence at Benchmark Capital

Kevin’s experience leads him to an insight

Companies spend a great deal of money keeping bad guys out of their network

• Firewalls • Intrusion detection • Anti-malware

But insiders who has access to the network can easily take data out of it

• Via email, chat, web posts • Via thumb drives, DVDs, or

laptops • Either accidentally or maliciously

A kernel of an idea

Build software that allows companies to prevent the loss of confidential data from the inside

It might seem obvious now

• Legal risk • Reputational risk • Regulatory

compliance • 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 flies off the shelves

6. IPO!

It doesn’t work that way

The graveyards are full of startups with products that

customers "should have

wanted"

It usually goes wrongToo 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 can’t be built or is delayed!Pricing, messaging, and distribution never figured out

The industry has gotten smarter about this

Growing recognition that startups are completely different than established businesses

A startup is an experiment

• Form hypothesis • Find fastest/cheapest

way to validate hypothesis

• Test and measure • Adjust, «pivot» 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 confidential 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

• Get meetings with potential customers • Interview them on their problems and desired

solutions • Show them mock-ups, examples, anything

tangible that will get them talking • Ask for follow-up meetings, repeat

Getting the meetings• Work your personal network • LinkedIn, Twitter, comment

threads, blogs • Put up a landing page, drive

traffic, gather names • Cold call, email, twitter - be

persistent

!

Requires "hustle" and may be painful or uncomfortable

Getting them to respond• Be clear it is not a sales call • Flatter them - you want their feedback and

advice • Entice them with the opportunity to work with

a cutting edge company - more interesting than their usual meetings

• Meet them anywhere, anytime • Ask for a short amount of time - they’ll give

you more if they are interested

Running the meeting

• Listen, listen, listen • Don't try to "sell" your solutions • Ask open-ended questions • Bring screenshots/slides/mockups - get their

reaction • Close them on another meeting

Sample questions

• “Talk us through your top priorities and projects”

• “Tell us about your existing infrastructure” • “Have you experienced this problem” • “How are you solving this problem today” • “Force rank the following capabilities” • I'll show you some prototypes - give me

your reaction”

?

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"

"We’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 can’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• We raised a $5M series A financing

based on this feedback. • Normally you’d raise later than this, but

we already had firms predisposed to give us money.

• Today it would be typical for a company to get much further along before raising a round

• 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?

• Technology • Oil and Gas • Entertainment • Financial services • Manufacturing • Automotive

What tier?Start at large companies!Larger budgets

Most public scrutiny

Largest amount of data to protect

“Name brand” references

!

!

Start small, build up!Less demanding

Shorter sales cycle

More innovative

Gain experience before going big

What we learnedThe 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.

“Keep me off of the front page of the WSJ”

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 weren’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 that’s OK

Next Question: !

What kinds of data do customers care the most about protecting?

Data types• Employee data? • Customer data? • Intellectual property? • Strategic plans? • Financials?

How we found out

• Built trust with prospects • Spent time with them as they walked us through

actual internal breaches and their costs • We showed them several kinds of policies and

got their reactions to each • Found that almost everything they talked about

had to do with consumer PII (personally identifiable information)

What we did nextWe 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?

• Data escaping via outbound email

• Data escaping via web posts / web mail

• Data escaping via FTP, P2P networks, other internet file transfer

• 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 productWe did Not

Focus on data loss Malware, anti-porn, URL monitoring

Focus on customer data Documents, intellectual property, financials

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 “more“ but ended up losing

What happened next• Responded to an RFP from

Bank of America

• Focused and won the deal

• ~$500K, over time grew to several million

• Needed to promise several near-term features to win the deal

• Made them referencable and a champion

Takeaway: !

The “minimum viable product” 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• Created an “explainer video”

demoing the product, got > 100K signups, didn’t ship product until 18 months later

• Went to shoe shops, took pictures of shoes, put online. When people ordered, went back to shop to get shoes.

• 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

• Opportunity to sell high - to the CSO/CIO level • Bring in experienced enterprise sales reps • Partners were not a large factor - we had to

evangelize/sell ourselves • Employees with security experience often did

not do well in the company

This sure helped

Expanded to more verticals

Added products

We obsessed aboutTeam - 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 grew2003 - $500K in bookings, 1 customer

2004 - $3.5M, 7 customers

2005 - $13.5M, 30 customers

2006 - $27M, Europe office

2007 - $50M, 175 employees

!

FTW

Key takeaways

• Validate, validate, validate • Build your product with customers. Seek face

to face meetings, not just metrics • Seek focus • Get an MVP to market as quickly as possible

and then iterate!• Obsess about people

http://www.michaelrwolfe.com

michaelrwolfe

michael.wolfe@stanfordalumni.org

Questions?