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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

Publié dans : Données & analyses, Business
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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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