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Automated solutions for product and pricing research

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In this webinar Ray Poynter interviews Conjoint.ly’s founder Nik Samoylov about automated tools for product and pricing research. Conjoint.ly is both a research firm and an automation provider, which means that the tools are tested in full-service projects, particularly in the FMCG and technology industries.

In the webinar you will learn how you can access:

- Claims testing
- Conjoint analysis
- Prediction markets
- Pricing techniques such as Gabor-Granger and Van Westendorp

Published in: Education
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Automated solutions for product and pricing research

  1. 1. Automated solu,ons for product and pricing research Nik Samoylov Founder Conjoint.ly All copyright owned by The Future Place and the presenters of the material. For more informaAon about NewMR events visit hDp://newmr.org
  2. 2. Automated solutions for product 
 and pricing research with Nik Samoylov
  3. 3. Today’s objectives •  What is automation? •  Go through specific research questions for •  Test a product concept •  Select claims and benefits for your product •  Feature selection •  Willingness to pay for a feature •  Cannibalisation and pricing in a market with a few competitors •  Pricing in general •  Answer your questions
  4. 4. Automation is the new kid on the block Full service Automated DIY Input from clients Direction and stimuli Choice of tool and stimuli Full set-up Output Presentations, reports Reports Data External mark of quality Full Medium Little Customisability Full Little to medium Full Direct costs High Low to moderate Low Time investment Low Low High Overall cost Moderate Low Moderate
  5. 5. Today’s objectives •  What is automation? •  Go through specific research questions for •  Test a product concept •  Select claims and benefits for your product •  Feature selection •  Willingness to pay for a feature •  Cannibalisation and pricing in a market with a few competitors •  Pricing in general •  Answer your questions
  6. 6. Testing a new product:
 Is our product good? RQ: Do people like it? RQ: Do people like it better than an alternative? RQ: Will it succeed on the market? How do you define “good”? Monadic testing A/B testing Prediction market
  7. 7. Testing a new product: 
 Monadic test, i.e. focus on a single product Product A “Do you like or dislike it?” + “Why” Key measures (e.g., relevance, uniqueness, modernity) Emotional assessment Heatmap of clicks Keyword association: Pick one + Provide your own Video/audio response Secret tip: This is Conjoint.ly’s next tool
  8. 8. Testing a new product: 
 A/B testing Product A Product B
  9. 9. Testing a new product: 
 Prediction market Product A Calibrate Predict Judge Explain Check example at Conjoint.ly/NewMR
  10. 10. Testing claims and benefits: 
 General approach “No addiAves” “No preservaAves” “No GMO” “Minimal GMO” “Made at an old farmhouse” Choice-based tesAng Brand associaAon Open-ended feedback AMtudes and key metrics MaxDiff AdapAve choice
  11. 11. MaxDiff vs adaptive choice-based test: 
 How MaxDiff works Worst Claim Best ● No additives ○ ○ No preservatives ○ ○ No GMO ● ○ Made at an old country house ○ Worst Claim Best ● No additives ○ ○ No preservatives ○ ○ No GMO ● ○ Made at an old country house ○ Worst Claim Best ● No additives ○ ○ No preservatives ○ ○ No GMO ● ○ Made at an old country house ○ Worst Claim Best ● No additives ○ ○ No preservatives ○ ○ No GMO ● ○ Made at an old country house ○ “No additives” “No preservatives” “No GMO” “Minimal GMO” “Made at an old farmhouse” [SERIES NAME] Series3 Series4 Series5 Series1 -80 -60 -40 -20 0 20 40 60 80 List of claims Respondents identify best and worst options in each question All claims ranked with good certainty Check example at Conjoint.ly/NewMR
  12. 12. MaxDiff vs adaptive choice-based test:
 How adaptive choice works “No additives” “No preservatives” “No GMO” “Minimal GMO” “Made at an old farmhouse” [SERIES NAME] Series3 Series4 Series5 Series1 -80 -60 -40 -20 0 20 40 60 80 List of claims Respondents identify best option in each question (not worst) All claims are ranked, with greater certainty for top claims No additives Choose No GMO Choose Minimal GMO Choose No additives Choose No GMO Choose Minimal GMO Choose No additives Choose No GMO Choose Minimal GMO Choose More certain Less certain Survey adapts to focus on more promising claims Check example at Conjoint.ly/NewMR
  13. 13. MaxDiff vs adaptive choice-based test:
 How adaptive choice works What’s wrong with MaxDiff Cost savings from Adaptive Choice ×  “Worst” is not very relevant because we are usually interested in “best” ×  Usually, not mobile friendly ×  Unnatural task for respondents, takes longer ×  Standard MaxDiff does not adaptively eliminate worst options Typical sample costs (100% for MaxDiff)
  14. 14. Today’s objectives •  What is automation? •  Go through specific research questions for •  Test a product concept •  Select claims and benefits for your product •  Feature selection •  Willingness to pay for a feature •  Cannibalisation and pricing in a market with a few competitors •  Pricing in general •  Answer your questions
  15. 15. What is conjoint analysis?
 Attributes and levels Product Hip chat Name: Slack Rocket.Chat … 10 Max users in a group: 200 500 Unlimited 6 months Retention of messages: 1 year Unlimited Exact phrase only Searchable history: Full search function … Yes, in app File sharing: Yes, Dropbox only … $2 per user per mo Pricing: $5 per user per mo $9 per user per mo
  16. 16. What is conjoint analysis?
 Example choice task Which of these smartphones would you buy? Choose Choose Choose Attributes Levels of each attribute Product concepts to choose from Brand iPhone Samsung Sony Screen size 5” 6” 5.5” Colour Silver Turquoise White Price $1,200 $1,100 $1,000
  17. 17. What is conjoint analysis?
 Multiple choice tasks per respondent Q3. Which of these chat apps would you choose? Q4. Which of these chat apps would you choose? Choose Choose Choose Choose Choose Choose Q2. Which of these chat apps would you choose? Choose Choose Choose Q1. Which of these chat apps would you choose? Choose Choose Choose Name Slack HipChat Rocket File share Yes Yes No History 1 year 6 months Unlimited Price $2 $5 $9 Check example at Conjoint.ly/NewMR
  18. 18. What is conjoint analysis?
 Numerous outputs Segment 2
 ü  Price sensitive ü  Needs searchable history Segment 1
 ü  Not price sensitive ü  Needs full file sharing capability Attribute importance 0 5 10 15 20 25 30 35 1 2 3 4 5 Level performance Series1 Series2 Series3 Series5 Series6 $[VALUE] -40 -20 0 20 40 1 Market share simulation 1 2 3 4 Willingness to pay Price elasticity 0 20 40 60 80 $1 $2 $3 $4 $5 $6 $7 Series1 Series2 Customer segmentation Series1 Series2 Series4 Dropbox file sharing (vs. none) $0 $2 $4 $6 $8 $10 $12 $14 1 40% of market 60% of market
  19. 19. Feature selection:
 Outputs of Generic Conjoint Preferences for can sizes Attribute importance scores 0 10 20 30 40 1 2 3 4 5 6 [SERIES NAME] [SERIES NAME] [SERIES NAME] -15 -10 -5 0 5 10 15 1 Relative importance score Relative preference score
  20. 20. Willingness to pay for a feature:
 Outputs of Generic Conjoint Marginal Willingness to Pay Set-up of the test 80 cans/ min 5” 3” and 5” Automatic shape scan $0 $2,000 $4,000 $6,000 $8,000 $10,000 Marginal Willingness to Pay (relative to baselines) (vs. no shape scanner) (vs. 3” can) (vs. 40 can per minute)
  21. 21. Launching a new product:
 Context and objectives Objectives Context •  Pharma Co is a leader in special liquid soap for patients with a certain disease with two SKUs, targeting different sub-segments •  Competitor has been eating into Pharma Co’s market share recently due to their new packaging which gives a modern feel to their soap •  Pharma Co decided to launch a new product line to compete with the revamped competitor product •  In designing the conjoint study, Pharma Co’s insights manager decides on the following research questions: •  RQ1: What is the most preferred packaging type for the new product? •  RQ2: What is the extent of cannibalisation from new SKU? •  RQ3: What is the optimal pricing for the new product?
  22. 22. Launching a new product:
 Setting up a Brand-Specific Conjoint •  To ensure that the choice sets are as realistic as possible, current and competitor products should reflect the features currently offered: •  SKU1: Round and tall at $13 •  SKU2: Standard square at $5 •  Competitor: Slim and curvy at $11 •  The new product offering should vary in terms of levels and price. This way, we can simulate the entry of SKU3 at different features and prices Deciding on features and levels
  23. 23. Launching a new product: RQ1: What is most preferred packaging type for the new product? •  The conjoint study found that winning packaging type is the “Slim & curvy” Preference for packaging type [SERIES NAME] [SERIES NAME] [SERIES NAME] [SERIES NAME] -40 -20 0 20 40 Relative preference score
  24. 24. Launching a new product: RQ2: What is the extent of cannibalisation from the new SKU? SKU1, 26% SKU1, 20% SKU2, 50% SKU2, 49% New SKU3, 15% Competitor, 23% Competitor, 16% 0% 20% 40% 60% 80% 100% Before: Current market After: New SKU launch New SKU3 
 with “Skinny and curvy” packaging at $11 Cannibalisation of SKU2 by 1 p.p. Cannibalisation of SKU1 by 6 p.p.
  25. 25. Launching a new product: RQ3: What is the optimal pricing for the new product? Revenue projections Preference share simulation 0% 20% 40% 60% 80% 100% $7 $9 $11 $13 $15 SKU1 SKU2 NEW SKU3 Competitor Launching new SKU3 at $11 will maximise total market share (84%) for Pharma Co $0 $200 $400 $600 $800 $1,000 $7 $9 $11 $13 $15 Launching new SKU3 at $13 will maximise total revenue to Pharma Co Simulated share of preference Projected revenue ($M)
  26. 26. Pricing in general:
 Van Westendorp vs. Gabor-Granger Gabor-Granger Van Westendorp 0% 20% 40% 60% 80% 100% $0 $5 $10 $15 $20 Too cheap Cheap Expensive Too expensive Acceptable price range 61% 52% 41% 34% 30% 27% 22% 19% 16% 16% 13% 11% 10% 9% 6% $6K $6K $6K $5K $5K $5K $5K $5K $4K $4K $4K $4K $3K $3K $2K $K $1K $2K $3K $4K $5K $6K $7K 0% 20% 40% 60% 80% 100% $10 $15 $20 $25 $30 $35 $40 % of customers willing to pay Revenue (assuming 1,000 units) Revenue-maximising price level Check example at Conjoint.ly/NewMR
  27. 27. Today’s objectives •  What is automation? •  Go through specific research questions for •  Test a product concept •  Select claims and benefits for your product •  Feature selection •  Willingness to pay for a feature •  Cannibalisation and pricing in a market with a few competitors •  Pricing in general •  Answer your questions
  28. 28. Automated solu,ons for product and pricing research Discussion Nik Samoylov Founder Conjoint.ly Ray Poynter The Future Place All copyright owned by The Future Place and the presenters of the material. For more informaAon about NewMR events visit hDp://newmr.org
  29. 29. Automated solu,ons for product and pricing research Q & A Sue York NewMR Ray Poynter The Future Place Nik Samoylov Founder Conjoint.ly All copyright owned by The Future Place and the presenters of the material. For more informaAon about NewMR events visit hDp://newmr.org
  30. 30. Thank you All copyright owned by The Future Place and the presenters of the material. For more informaAon about NewMR events visit hDp://newmr.org

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