The document discusses techniques for systematically testing startup ideas through experiments and pivots. It provides examples of startup hypotheses that were tested, such as the idea of creating lists of top professionals and whether people would pay for access to such lists. It emphasizes testing ideas quickly through real-world experiments and validating or invalidating hypotheses through metrics before committing significant resources.
3. Startup Science
Systematic Innovation
Today, in Australia and Singapore ...
Execution teams, deploying Pollenizer tools and
process create investable internet businesses in
6-9 months and we currently do this about 10
times per year.
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4. Startup Science
Startups = a series of
hypotheses
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7. Startup Science
Academy Courses
• Building Lean Startups
Take an idea from inception to pitch and everything in between.
• The Lean Product Manager
Learn how to build, measure and learn your way to success.
• Coding for Designers & Managers
You work with coders and you dream of impressing them with
your own coding chops.
• Web Development for Lean Startups
What you need to know to be a developer in a Lean Startup.
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8. Startup Science
About Me
Lean Product Manager
Work @ Pollenizer
Successfully failed
Ruby hacker
@micdijkstra
github.com/
micdijkstra
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13. Startup Science
1. Problem 4. Solution 3. UVP 9. Unfair 2. Customer
Advantage
The lean canvas shows each risk as a
8. KPI 5. Channels
hypothesis to be tested.
7. Costs 6. Revenue
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15. Startup Science
It’s hard to find the best person for a job
What if we could create a list of the best
people for a given profession
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16. Startup Science
Test #1
Recruiters will pay for (find value in) a list
of top talent in a profession.
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17. Startup Science
We need to find 50 top professionals for a
given role, add them to a list and
then we can start selling!
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30. Startup Science
Measure Viral Coefficient
• Spread of the network
New members / lists created
• Conversion
New members signed up / new members added
• Cycle
Signups who created a list
• Returning users
Existing signed in users / existing base users
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31. Startup Science
Within 2 weeks …
• Over 500 people listed
• 150 people signed up
• Viral coefficient of 0.31
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53. Startup Science
How do you know what to
manual test?
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54. Startup Science
Focus on the why
Figuring out the how is the easy (fun) part
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55. Startup Science
We want people to create lots of lists … Why?
To create a master list of talent … Why?
So we can sell it to recruiters … Why?
So they can have a shortlist of the best
candidates … Why?
So they can provide the best candidates to
employers … Why?
So an employer can find the best person for
the job.
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56. Startup Science
Think of the Flow
• What is the big piece of value that you are
basing everything off?
• How do you think your solution will work?
• What key stages are there?
• Can you fake one side of the market?
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57. Startup Science
Create lots of
lists
Generate
master list
Sell list
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58. Startup Science
Create lots of
lists
Fake It
Master List
Sell list
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59. Startup Science
What are you waiting for?
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60. Startup Science
If you’re so confident that your
solution will work, then you
should have no problem manual
testing to prove it.
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61. Questions?
Test Storyberg for me
http://storyberg.com
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