Ce diaporama a bien été signalé.
Le téléchargement de votre SlideShare est en cours. ×

DiDo #27: Tom van den Berg (Online Dialogue)

Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Chargement dans…3
×

Consultez-les par la suite

1 sur 45 Publicité

Plus De Contenu Connexe

Plus par Online Dialogue (20)

Publicité

DiDo #27: Tom van den Berg (Online Dialogue)

  1. 1. SUBTITLE BELOW Experimenteren & personaliseren binnen (grote) webshops
  2. 2. Agenda 14.30 – 14.40 Welkom 14.40 – 15.00 Tom van den Berg | Conversie Manager @ Online Dialogue 15.00 – 15.30 Niels Reijmer | Lead Data Analyst @ Bijenkorf Pauze 16.00 – 16.30 Ellen Tonkens | Conversion Specialist @ wehkamp 16.30 – 17.00 Ask them anything 17.00 – 18.30 Borrel
  3. 3. Validation in every organization
  4. 4. Digital made validation possible
  5. 5. Validation to the max?
  6. 6. Validation to the max? > 2.000 experiments per day > 7.000 experiments 7 years ago > 2.000 experiments live now
  7. 7. “Our success at Amazon is a function of how many experiments we do per year, per month, per week, per day…” Jeff Bezos, CEO Amazon
  8. 8. More tests = more growth
  9. 9. 3 Validation rules: 1. OEC 2. Effectiveness over Efficiency 3. Quantity over quality
  10. 10. 3 Validation rules: 1. OEC 2. Effectiveness over Efficiency 3. Quantity over quality
  11. 11. First agree on your OEC
  12. 12. 3 Validation rules: 1. OEC 2. Effectiveness over Efficiency 3. Quantity over quality
  13. 13. Effectiveness Over efficiency
  14. 14. But… $
  15. 15. Even better… ROI
  16. 16. ROI Return Investments = ____________________
  17. 17. ITOptimization
  18. 18. ITOptimization Validation
  19. 19. Useless to spend scarce resources onHurts our bussiness Brings value Significantly positiveInconclusiveSignificantly negative Validation
  20. 20. Hurts Doesn't make a difference Improves 0% 25% 50% 75% 100% 25%60%15% Typically, most optimization are ineffective
  21. 21. Typically, most optimization are ineffective Hurts Doesn't make a difference Improves 0% 25% 50% 75% 100% Brings value B A A B A B B A 25%60%15% 25% - 15% = 10%
  22. 22. Validation boosts effectiveness! Hurts Doesn't make a difference Improves 0% 25% 50% 75% 100% regret Brings value regret
  23. 23. 3 Validation rules: 1. OEC 2. Effectiveness over Efficiency 3. Quantity over quality
  24. 24. What is easier? Double experiments in: 1. Quantity 2. Quality
  25. 25. What is easier? Double experiments in: 1. Quantity 2. Quality
  26. 26. But… there is a maximum What’s your Bandwidth?
  27. 27. test velocity Validation is about Velocity! Prevent Regret: Run as much experiments as possible
  28. 28. Validation is about Velocity!
  29. 29. Validation = Culture
  30. 30. Validation is about reducing investments! ROI Increase Improvements Lower Investments = ____________________ What’s your value / hour spend?
  31. 31. test velocity You think & talk too much!
  32. 32. Too much discussion All new experiments
  33. 33. Velocity over Value $$ Resources per validation Costs of resources Value per validation Value per hour spend validating
  34. 34. Example Scenario 1 2 Uren per week 200 200 Uren per experiment 40 25 # experimenten p/w 5 8 # experimenten p/y 260 416 % winnaars 25% 20% # winnaars 65 83 Value per winner €100K €100K Revenu €6,5M €8,3M Extra revenue €1,8M
  35. 35. Example Scenario 1 2 Uren per week 200 200 Uren per experiment 40 25 # experimenten p/w 5 8 # experimenten p/y 260 416 % winnaars 25% 20% # winnaars 65 83 Value per winner €100K €100K Revenu €6,5M €8,3M Extra revenue €1,8M
  36. 36. Example Scenario 1 2 Uren per week 200 200 Uren per experiment 40 25 # experimenten p/w 5 8 # experimenten p/y 260 416 % winnaars 25% 20% # winnaars 65 83 Value per winner €100K €100K Revenu €6,5M €8,3M Extra revenue €1,8M
  37. 37. Example Scenario 1 2 Uren per week 200 200 Uren per experiment 40 25 # experimenten p/w 5 8 # experimenten p/y 260 416 % winnaars 25% 20% # winnaars 65 83 Value per winner €100K €100K Revenu €6,5M €8,3M Extra revenue €1,8M
  38. 38. Example Scenario 1 2 Uren per week 200 200 Uren per experiment 40 25 # experimenten p/w 5 8 # experimenten p/y 260 416 % winnaars 25% 20% # winnaars 65 83 Value per winner €100K €100K Revenu €6,5M €8,3M Extra revenue €1,8M
  39. 39. Example Scenario 1 2 Uren per week 200 200 Uren per experiment 40 25 # experimenten p/w 5 8 # experimenten p/y 260 416 % winnaars 25% 20% # winnaars 65 83 Value per winner €100K €100K Revenu €6,5M €8,3M Extra revenue €1,8M
  40. 40. Example Scenario 1 2 Uren per week 200 200 Uren per experiment 40 25 # experimenten p/w 5 8 # experimenten p/y 260 416 % winnaars 25% 20% # winnaars 65 83 Value per winner €100K €100K Revenu €6,5M €8,3M Extra revenue €1,8M
  41. 41. Example Scenario 1 2 Uren per week 200 200 Uren per experiment 40 25 # experimenten p/w 5 8 # experimenten p/y 260 416 % winnaars 25% 20% # winnaars 65 83 Value per winner €100K €100K Revenu €6,5M €8,3M Extra revenue €1,8M
  42. 42. Example Scenario 1 2 Uren per week 200 200 Uren per experiment 40 25 # experimenten p/w 5 8 # experimenten p/y 260 416 % winnaars 25% 20% # winnaars 65 83 Value per winner €100K €100K Revenu €6,5M €8,3M Extra revenue €1,8M
  43. 43. Example Scenario 1 2 Uren per week 200 200 Uren per experiment 40 25 # experimenten p/w 5 8 # experimenten p/y 260 416 % winnaars 25% 20% # winnaars 65 83 Value per winner €100K €100K Revenu €6,5M €8,3M Extra revenue €1,8M €1,8M
  44. 44. Niet lullen, maar toetsen!

×