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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
Automated solutions for product 

and pricing research 
with Nik Samoylov
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
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
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
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
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
Testing a new product: 

A/B testing
Product A
 Product B
Testing a new product: 

Prediction market
Product A
Calibrate
 Predict
 Judge 
Explain 
Check example at Conjoint.ly/NewMR
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
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
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
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)
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
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
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
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
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
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
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)
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?
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
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
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.
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)
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
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
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
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
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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PRICING RESEARCH

  • 2. Automated solutions for product 
 and pricing research with Nik Samoylov
  • 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. 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. 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. 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. 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. Testing a new product: 
 A/B testing Product A Product B
  • 9. Testing a new product: 
 Prediction market Product A Calibrate Predict Judge Explain Check example at Conjoint.ly/NewMR
  • 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. 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. 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. 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.
  • 15. 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
  • 16. 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
  • 17. 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
  • 18. 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
  • 19. 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
  • 20. 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
  • 21.
  • 22. 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)
  • 23. 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?
  • 24. 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
  • 25.
  • 26. 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
  • 27. 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.
  • 28. 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)
  • 29. 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
  • 30. 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