5Data Traps to Avoid 
when testing your Value 
Proposition Design
Overview of the Testing Process 
Extract Hypotheses Prioritize Hypotheses Design Test Prioritize Test 
Run Tests Capture L...
Avoid failure by thinking 
critically about your data. 
Experiments can’t predict future 
successes with 100% accuracy.
trap #1 
False Positive Trap 
risk: Occurs when your testing data misleads 
you to conclude, for example, that your custom...
trap #1 
False Positive Trap 
tips: Test “the circle” before you test “the 
square”. Understand what’s relevant to 
custom...
trap #2 
False Negative Trap 
risk: Not seeing things that are there. 
Occurs when your experiment fails to detect, 
for e...
trap #2 
False Negative Trap 
tips: Make sure your test is adequate. 
Dropbox initially tested customer interest 
with Goo...
trap #3 
The “Local Maximum” Trap 
risk: Missing out on the real potential. 
Occurs when you conduct experiments that 
opt...
trap #3 
The “Local Maximum” Trap 
tips: Focus on learning rather than optimizing. 
Don’t hesitate to go back to designing...
trap #4 
The “Exhausted Maximum” Trap 
risk: Overlooking limitations (e.g. of a market). 
Occurs when you think an opportu...
trap #4 
The “Exhausted Maximum” Trap 
tips: Design tests that prove the potential 
beyond the immediately addressed test ...
trap #5 
The Wrong Data Trap 
risk: Searching in the wrong place. 
Occurs when you abandon an opportunity 
because you are...
trap #5 
The Wrong Data Trap 
tip: Go back to designing other alternatives 
before you give up.
trap #5 
Create products and services 
customer want. Start with your 
best value proposition. 
www.strategyzer.com/value-...
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5 Data Traps to Avoid When Testing Your Value Proposition Design

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Avoid failure by thinking critically about your data. Avoid these 5 data traps and create products and services customers want.

Based on Value Proposition Design by Alexander Osterwalder, Yves Pigneur, Greg Bernarda & Alan Smith. More info: http://bit.ly/1tbBCH6. #vpdesign

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  • @Misha Berger Thanks! There are other examples throughout the book - and a 100 page free sampler on the site, too! Check it out here: http://bit.ly/1tbBCH6
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  • Really loved the example on slide 7, how Drew from Dropbox nearly fell for a false negative trap. Would love to hear similar real world examples for the other 4 data traps :)
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5 Data Traps to Avoid When Testing Your Value Proposition Design

  1. 5Data Traps to Avoid when testing your Value Proposition Design
  2. Overview of the Testing Process Extract Hypotheses Prioritize Hypotheses Design Test Prioritize Test Run Tests Capture Learnings Make Progress
  3. Avoid failure by thinking critically about your data. Experiments can’t predict future successes with 100% accuracy.
  4. trap #1 False Positive Trap risk: Occurs when your testing data misleads you to conclude, for example, that your customer has a pain, when in fact that is not true.
  5. trap #1 False Positive Trap tips: Test “the circle” before you test “the square”. Understand what’s relevant to customers and avoid being misled by positive signals for irrelevant value propositions. Design different experiments for the same hypothesis before making important decisions.
  6. trap #2 False Negative Trap risk: Not seeing things that are there. Occurs when your experiment fails to detect, for example, a customer job it was designed to unearth.
  7. trap #2 False Negative Trap tips: Make sure your test is adequate. Dropbox initially tested customer interest with Google Adwords. They invalidated their hypotheses because the ads didn’t perform. Yet, people didn’t search because it was a new market, not for a lack of interest.
  8. trap #3 The “Local Maximum” Trap risk: Missing out on the real potential. Occurs when you conduct experiments that optimize around a local maximum, while ignoring the larger opportunity. Positive testing feedback might get you stuck with a much less profitable model while there is a more profitable one.
  9. trap #3 The “Local Maximum” Trap tips: Focus on learning rather than optimizing. Don’t hesitate to go back to designing better alternatives if the testing data is positive, but the numbers feel like they should be better.
  10. trap #4 The “Exhausted Maximum” Trap risk: Overlooking limitations (e.g. of a market). Occurs when you think an opportunity is larger than it is in reality.
  11. trap #4 The “Exhausted Maximum” Trap tips: Design tests that prove the potential beyond the immediately addressed test subjects.
  12. trap #5 The Wrong Data Trap risk: Searching in the wrong place. Occurs when you abandon an opportunity because you are looking at the wrong data.
  13. trap #5 The Wrong Data Trap tip: Go back to designing other alternatives before you give up.
  14. trap #5 Create products and services customer want. Start with your best value proposition. www.strategyzer.com/value-proposition-design #vpdesign

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