Test description

1. Minimum Viable Presentation
1. Tell us your story
2. Be concise and clear
2. Use experiments as your vocabulary
3. Examples

2. Quick Review
“The team that shows, through
evidence, the most customer validation for
a new product or service.”
From your Workshop Manual (hint: READ IT!)
• Clear statement of business assumptions, documenting how these
assumptions changed over time
• Assumptions validated or invalidated based on market feedback
• MVP that demonstrates learning and productivity
• Strong evidence to support conclusions, qualitative or quantitative

3. Tell us your story
Take us along for the journey (but do it fast)
- What insight led you to believe in this opportunity?
- What expectations did you have as the LSM began?
- What experiments did you run and why?
- Share your craziest story!
Think like a movie trailer!

4. Be concise and clear
Communicate clearly with simple words and statements
- Focus on the most important events in your story
- Connect these events together into an narrative
- Make a clear link to your conclusion
Judges do not have the same background as you
- Avoid too much detail, or industry specific jargon
- We’re looking for specific behavior from the teams
- We should understand your vision, as well as your progress

5. Vocabulary of Experimentation
Each experiment is a key event in your journey
- Identified the riskiest assumptions in the business
- Created effective experiments to test assumptions
- Capture metrics and customer insights
What data supports your decision – Pivot or Persevere
- Capture metrics and customer insights
- Use observations customer behavior
- What DATA suggests a pivot or persevere?

6. Experiment Details
Highlight the most important components of your experiments
- What was your numerical hypothesis?
- Did the hypothesis pass or fail? WHY? What did you learn?
- What currency did your customers exchange?
- What behavior did they do as a result of your experiment?
- What decision did you make based on this experiment, and
what data supports this decision?
Output = Metrics + Surprises

7. Example (bad)
Assumption: Ben’s presentation will help LSM participants
Experiment: Share 15 minute presentation on hypotheses
Hypothesis: If Ben shares a 15 minute presentation on effective
hypotheses, 75% of LSM participants will be able to write an
effective hypothesis when when he is done talking.
Results: People didn’t seem to do this. Bummer.
Decision: Persevere (but create a better presentation next time)

8. Example (good)
Assumption: Ben’s presentation will help LSM participants
Experiment: Share 15 minute presentation on hypotheses
Hypothesis: If Ben shares a 15 minute presentation on effective
hypotheses, 75% of LSM participants will be able to write an
effective hypothesis when when he is done talking.
Results: 10% of LSM participants created hypotheses
Surprises: Few people listen to me. Difficult to remember my
talk when the time comes to write down hypotheses.
Decision: Pivot (need to provide hypotheses worksheet?)
Why: Hypotheses training must be embedded into LSM