Diese Präsentation wurde erfolgreich gemeldet.
Wir verwenden Ihre LinkedIn Profilangaben und Informationen zu Ihren Aktivitäten, um Anzeigen zu personalisieren und Ihnen relevantere Inhalte anzuzeigen. Sie können Ihre Anzeigeneinstellungen jederzeit ändern.

5 Data Traps to Avoid When Testing Your Value Proposition Design

12.340 Aufrufe

Veröffentlicht am

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

Veröffentlicht in: Daten & Analysen, Business
  • Hello! High Quality And Affordable Essays For You. Starting at $4.99 per page - Check our website! https://vk.cc/82gJD2
       Antworten 
    Sind Sie sicher, dass Sie …  Ja  Nein
    Ihre Nachricht erscheint hier
  • @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
       Antworten 
    Sind Sie sicher, dass Sie …  Ja  Nein
    Ihre Nachricht erscheint hier
  • 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 :)
       Antworten 
    Sind Sie sicher, dass Sie …  Ja  Nein
    Ihre Nachricht erscheint hier

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

×