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What to expect from
running a startup
(and what to do about it)
                            1
Successful startups are
created with Wizardry.
                          2
Successful startups are NOT
created with Wizardry.
                              3
Successful startups are NOT
created with Wizardry.
.                             4
Startup Theory Part 1: Value
We will fix the problem like this.




                                     5
Startup Theory Part 1: Value
We will fix the problem like this:

Understand Your Value Hypothesis:
 How will the product or service deliver value to
 people once they are using it?

 Sample Hypotheses:
 + Lower cost/time
 + Better experience (increase willingness to pay)
 + Improve supply chain for customers (B2B)
 + Increase volume for customers (B2B, B2C)

  Source: Value Hypothesis concepts comes from Eric Ries, The Lean Startup   6
Startup Theory Part 2: Growth
People will find out about us like this.




                                     7
Startup Theory Part 2: Growth
People will find out about us like this:

Understand Growth Hypothesis:
    How new users will discover product or service

    Sample Hypotheses:
    + People will tell their friends (viral)
    + Via advertisement (paid)
    + Marketed directly to enterprise customers (sales)
    + Established partners will distribute product.



 Source: Value, Growth Hypothesis concepts come from Eric Ries, The Lean Startup   8
Lean Startup = Startup Science
                  (NOTE: still A LOT of art left)

• Business plans are wrong, all startups are built on
  untested flawed assumptions (risks).

• 70-90% of startups fail

• Key risk is scaling too quickly
   • i.e. spending too much time/money based on
     assumptions instead of knowledge

• Think about productivity not in terms of how much stuff
  you are building, but how much stuff you are learning.

• Make sure you are learning as quickly as possible.
Successful startups go through phases
                                               Many startups say they are
                                                        here…
        …but are actually here




 1. Discovery          2. Validation       3. Efficiency        4. Scale
  (avg 5-7 months)     (avg 3-5 months)    (avg 5-6 months)     (avg 7-9 months)




        Riskiest time to spend $          Best time to spend $


     Trick is: Know where you’re at!
Discovery Phase (T+ 5-7 months)
Purpose:                                Key Graduation Milestone:
Validate whether startup is solving a   -Customer Validation of Problem
meaningful problem and whether          -Complete Minimum Viable Product
anybody would hypothetically be
interested in their solution            Key Stats (Avg):
                                        # of employees: 1
Events:                                 # of $ raised: $200k
• Founding team formed                  Monthly User Growth: 6%
• Many customer interviews conducted
• Minimum viable product
• Team joins accelerator
• Friends and family round
• Mentors & advisors




   Source: Startup Genome Project
What is Minimum Viable Product (MVP)?
MVP = F(Customer, Problem, Time or $$$)
• Primarily, MVP is a way to test your value hypothesis

• Focus on CUSTOMER
    – Qualitative Discovery, Quantitative Validation

• Get to know habits, problems, desires (FUN MATTERS)
    – what causes pain? what causes pleasure?

• Define 1-5 TESTABLE Conversion Metrics of Value
    –   Attention/Usage (session time, clicks)
    –   Customer Data (email, connect, profile)
    -   Revenue (direct or indirect)
    -   Retention (visits over time, cohort behavior)
    -   Referral (users evangelize to other users)

• Note: Paid Solutions drive FOCUS (& pay rent)


        SOURCE: DAVE MCCLURE, 500 Startups, Metrics4Pirates Presentation, June 2011
Validation Phase (T+ 8-12 months)
Purpose:                               Key Milestone:
Get early validation that people are   -Product market fit
interested in product through
exchange of $ or attention.            Key Stats (Avg at end of Phase):
                                       # of employees: 4
Events:                                # of $ raised: $800k
• Core features refined                Monthly User Growth: 21%
• Initial user growth
• Metrics & analytics
  implementation
• Seed funding
• 1st key hires
• 1st paying customers
• Product/Market Fit



    Source: Startup Genome Project
Boil down assumptions to 5-7 key
      Metrics that you can measure
Seven metrics that matter:
1. Acquisition: (rate of gaining new users)
2. Engagement: (how deeply are you engaging users)
3. Virality: (new customers coming from existing customers)
4. Monetization: (% of total users participating in the business)
5. Churn: (loss of existing users)
6. Lifetime customer value (projected monetization returns by class of customers)
7. Program Productive (Yield on promotional activities, both paid and viral)




   Source: Escape Velocity, Geoffrey Moore (2011)
Look for Product/Market Fit
PMF = F(Customer, Solution, Alternatives*)

• Product / Market Fit occurs when value hypothesis is validated:
    – Customers like your stuff better than other options
    – Not static, Not optimal – just Local Max 4 F(customers, solution, time)
    – make sure you’re moving in optimal direction 2 local max
• Q: what competitive solutions are available?
    – … that your customers know about?
    – how are you diff/same?
    – in ways that people care about? (will pay for)

• KILL a FEATURE regularly (or rotate 1% tests)
    – Q: what is MOST $ cust pay 4 LEAST func MVP relative 2 BEST alt?

• NICHE 2 WIN: RE-define cust + DIFFerentiated features

      SOURCE: DAVE MCCLURE, 500 Startups, Metrics4Pirates Presentation, June 2011
Efficiency Phase (T+ 13-18 months)
Purpose: Refine business model      Key Milestone:
and improve efficiency of           -Conversion Funnel Optimization
customer acquisition process to     -Growth Theory Validated
avoid scaling with a leaky
bucket.                             Key Stats (Avg at end of Phase):
                                    # of employees: 4
Events:                             # of $ raised: $900k
• Value proposition refined         Monthly User Growth: 29%
• UX Overhauled
• Conversion Funnel Optimized
• Viral growth achieved
• Repeatable sales process &/or
  customer acquisition channel




   Source: Startup Genome Project
Develop a marketing strategy based on
          what customers are doing

Q: What channels? Which users? Why?
A: High Volume (#), Low Cost ($), High Conv (%)

•    Design & Test Multiple Marketing Channels + Campaigns
•    Select & Focus on Best-Performing Channels & Themes
•    Optimize for conversion to target CTAs, not just site/landing page
•    Match/Drive channel cost to/below revenue potential

•     Low-Hanging Fruit:
    –    Blogs
    –    SEO/SEM
    –    Landing Pages
    –    Automated Emails


    SOURCE: DAVE MCCLURE, 500 Startups, Metrics4Pirates Presentation, June 2011
Conversion Funnel vs. Cohort Analysis
Scale Phase (T +20-27 months)
                                     Key Milestone:
Purpose: Step on the gas! Drive      -Next round of financing
growth aggressively.                 -Real Revenue (Breakeven?)
                                     Key Stats (Avg during Phase):
Events:                              # of employees: 17
• Large Investment Round             # of $ raised: $3M
• Massive Customer Acquisition       Monthly User Growth: 43%
• Back End Scalability
  Improvements
• 1st Executive Hires
• Process Implementation
• Establish Departments




    Source: Startup Genome Project
Key risks to scaling too early




Source: Startup Genome Project
Key takeaways
1. (Tech) startups go through phases

2. Understanding what phase a Startup is at is key to being able to
   evaluate the startup

3. The more intentionally (and leanly) startups learn, the faster they are
   likely to progress towards scale

4. Being able to identify correctly what phase an organization is at, should
   impact the way KF invests.

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What to expect from running a startup

  • 1. What to expect from running a startup (and what to do about it) 1
  • 3. Successful startups are NOT created with Wizardry. 3
  • 4. Successful startups are NOT created with Wizardry. . 4
  • 5. Startup Theory Part 1: Value We will fix the problem like this. 5
  • 6. Startup Theory Part 1: Value We will fix the problem like this: Understand Your Value Hypothesis: How will the product or service deliver value to people once they are using it? Sample Hypotheses: + Lower cost/time + Better experience (increase willingness to pay) + Improve supply chain for customers (B2B) + Increase volume for customers (B2B, B2C) Source: Value Hypothesis concepts comes from Eric Ries, The Lean Startup 6
  • 7. Startup Theory Part 2: Growth People will find out about us like this. 7
  • 8. Startup Theory Part 2: Growth People will find out about us like this: Understand Growth Hypothesis: How new users will discover product or service Sample Hypotheses: + People will tell their friends (viral) + Via advertisement (paid) + Marketed directly to enterprise customers (sales) + Established partners will distribute product. Source: Value, Growth Hypothesis concepts come from Eric Ries, The Lean Startup 8
  • 9. Lean Startup = Startup Science (NOTE: still A LOT of art left) • Business plans are wrong, all startups are built on untested flawed assumptions (risks). • 70-90% of startups fail • Key risk is scaling too quickly • i.e. spending too much time/money based on assumptions instead of knowledge • Think about productivity not in terms of how much stuff you are building, but how much stuff you are learning. • Make sure you are learning as quickly as possible.
  • 10. Successful startups go through phases Many startups say they are here… …but are actually here 1. Discovery 2. Validation 3. Efficiency 4. Scale (avg 5-7 months) (avg 3-5 months) (avg 5-6 months) (avg 7-9 months) Riskiest time to spend $ Best time to spend $ Trick is: Know where you’re at!
  • 11. Discovery Phase (T+ 5-7 months) Purpose: Key Graduation Milestone: Validate whether startup is solving a -Customer Validation of Problem meaningful problem and whether -Complete Minimum Viable Product anybody would hypothetically be interested in their solution Key Stats (Avg): # of employees: 1 Events: # of $ raised: $200k • Founding team formed Monthly User Growth: 6% • Many customer interviews conducted • Minimum viable product • Team joins accelerator • Friends and family round • Mentors & advisors Source: Startup Genome Project
  • 12. What is Minimum Viable Product (MVP)? MVP = F(Customer, Problem, Time or $$$) • Primarily, MVP is a way to test your value hypothesis • Focus on CUSTOMER – Qualitative Discovery, Quantitative Validation • Get to know habits, problems, desires (FUN MATTERS) – what causes pain? what causes pleasure? • Define 1-5 TESTABLE Conversion Metrics of Value – Attention/Usage (session time, clicks) – Customer Data (email, connect, profile) - Revenue (direct or indirect) - Retention (visits over time, cohort behavior) - Referral (users evangelize to other users) • Note: Paid Solutions drive FOCUS (& pay rent) SOURCE: DAVE MCCLURE, 500 Startups, Metrics4Pirates Presentation, June 2011
  • 13. Validation Phase (T+ 8-12 months) Purpose: Key Milestone: Get early validation that people are -Product market fit interested in product through exchange of $ or attention. Key Stats (Avg at end of Phase): # of employees: 4 Events: # of $ raised: $800k • Core features refined Monthly User Growth: 21% • Initial user growth • Metrics & analytics implementation • Seed funding • 1st key hires • 1st paying customers • Product/Market Fit Source: Startup Genome Project
  • 14. Boil down assumptions to 5-7 key Metrics that you can measure Seven metrics that matter: 1. Acquisition: (rate of gaining new users) 2. Engagement: (how deeply are you engaging users) 3. Virality: (new customers coming from existing customers) 4. Monetization: (% of total users participating in the business) 5. Churn: (loss of existing users) 6. Lifetime customer value (projected monetization returns by class of customers) 7. Program Productive (Yield on promotional activities, both paid and viral) Source: Escape Velocity, Geoffrey Moore (2011)
  • 15. Look for Product/Market Fit PMF = F(Customer, Solution, Alternatives*) • Product / Market Fit occurs when value hypothesis is validated: – Customers like your stuff better than other options – Not static, Not optimal – just Local Max 4 F(customers, solution, time) – make sure you’re moving in optimal direction 2 local max • Q: what competitive solutions are available? – … that your customers know about? – how are you diff/same? – in ways that people care about? (will pay for) • KILL a FEATURE regularly (or rotate 1% tests) – Q: what is MOST $ cust pay 4 LEAST func MVP relative 2 BEST alt? • NICHE 2 WIN: RE-define cust + DIFFerentiated features SOURCE: DAVE MCCLURE, 500 Startups, Metrics4Pirates Presentation, June 2011
  • 16. Efficiency Phase (T+ 13-18 months) Purpose: Refine business model Key Milestone: and improve efficiency of -Conversion Funnel Optimization customer acquisition process to -Growth Theory Validated avoid scaling with a leaky bucket. Key Stats (Avg at end of Phase): # of employees: 4 Events: # of $ raised: $900k • Value proposition refined Monthly User Growth: 29% • UX Overhauled • Conversion Funnel Optimized • Viral growth achieved • Repeatable sales process &/or customer acquisition channel Source: Startup Genome Project
  • 17. Develop a marketing strategy based on what customers are doing Q: What channels? Which users? Why? A: High Volume (#), Low Cost ($), High Conv (%) • Design & Test Multiple Marketing Channels + Campaigns • Select & Focus on Best-Performing Channels & Themes • Optimize for conversion to target CTAs, not just site/landing page • Match/Drive channel cost to/below revenue potential • Low-Hanging Fruit: – Blogs – SEO/SEM – Landing Pages – Automated Emails SOURCE: DAVE MCCLURE, 500 Startups, Metrics4Pirates Presentation, June 2011
  • 18. Conversion Funnel vs. Cohort Analysis
  • 19. Scale Phase (T +20-27 months) Key Milestone: Purpose: Step on the gas! Drive -Next round of financing growth aggressively. -Real Revenue (Breakeven?) Key Stats (Avg during Phase): Events: # of employees: 17 • Large Investment Round # of $ raised: $3M • Massive Customer Acquisition Monthly User Growth: 43% • Back End Scalability Improvements • 1st Executive Hires • Process Implementation • Establish Departments Source: Startup Genome Project
  • 20. Key risks to scaling too early Source: Startup Genome Project
  • 21. Key takeaways 1. (Tech) startups go through phases 2. Understanding what phase a Startup is at is key to being able to evaluate the startup 3. The more intentionally (and leanly) startups learn, the faster they are likely to progress towards scale 4. Being able to identify correctly what phase an organization is at, should impact the way KF invests.

Notas do Editor

  1. This is why User Growth and # of Users are Bullshit Numbers
  2. This is why User Growth and # of Users are Bullshit Numbers
  3. This is why User Growth and # of Users are Bullshit Numbers