Stefan binner advanced quant - 2011

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Advanced
Quant
Techniques

July
14,
2011

ACBC
Case
Study

Stefan
Binner,
bms
marke;ng
research

+
strategy

Stefan Binner, bms-marketing research + strategy, Germany
NewMR Advanced Quant Techniques, July 14, 2011
ACBC Case Study
Stefan Binner
Advanced Quant Webinar - July 14, 2011

In 2009 Sawtooth Software launched ACBC
(Adaptive Choice Based Conjoint)
As many researchers we expected a new “power tool” and increased value
for our projects.
Following presentation report our experience illustrated with base case from
a commercial study…

Case Study: Background
ü Chemical Product for DIY market
ü 14 attributes including price, many non compensatory
attributes
ü Difficult to find target group (“Moonlighters”)
=> small sample N=200
ü Objective: Product development & identification of best USP
ü No focus on price

“Unacceptable” Questions “Must-‐Have” Questions
Build
Your
Own
Section
Screening
Section
(Respondent answers 6 screens like this)
Choice
Tasks

Interview Progress
Design Considerations
ACBC

ACBC Parameter Settings
Case Study:
13
8
4
3
18
6
3
3
6
mixed

Parameters
Number of Attributes w/o price
# of Screening Tasks
# of Must Haves
# of Unacceptables
Max. # of Concepts in Choice T
# of Calibration Concepts
# of Concepts / Screening task
Min. Attributes to vary from BYO
Max. Attributes to vary from BYO
BYO Modification Strategy
Case Study
13
8
4
3
18
6
3
3
6
mixed
Given by the nature of
the project – required by
customer

Parameters
# of Must Haves
# of Unacceptables
Case Study
13
8
4
3
18
6
3
3
6
mixed
8 x 3 = 24 concepts
seen as sufficient
(interview length!)

Parameters
# of Must Haves
# of Unacceptables
Case Study
13
8
4
3
18
6
3
3
6
mixed
Less than suggested by
Sawtooth.
Intention: to avoid too
many MH or UA

Parameters
# of Must Haves
# of Unacceptables
Case Study
13
8
4
3
18
6
3
3
6
mixed
Less than suggested by
Sawtooth
(Interview lengths!)

Parameters
# of Must Haves
# of Unacceptables
Case Study
13
8
4
3
18
6
3
3
6
mixed
Used
Sawtooth
recommendation

Parameters
# of Must Haves
# of Unacceptables
Case Study
13
8
4
3
18
6
3
3
6
mixed
Screen Size Limitation
Complexity

Parameters
Number of Attributes
# of Must Haves
# of Unacceptables
Case Study
13
8
4
3
18
6
3
3
6
mixed
More than suggested
by Sawtooth

Parameters
Number of Attributes
# of Must Haves
# of Unacceptables
Case Study
13
8
4
3
18
6
3
3
6
mixed
Sawtooth
recommendation

Prohibitions
Initial prohibitions led to huge design problems
No Standard Tool to “test design efficiency” in ACBC
=> Be careful and avoid as possible
"  Only one prohibition was used

Price Attribute
v Price range +/- 50%
v Rounded to 99 cents
v Prices was used in unacceptable section
v Level Prices for selected attribute levels were used in 7 of
13 non price attributes

Holdout Tasks
§  No easy holdout tasks like in CBC
§  Calibration concept no substitute for holdout tasks
§  Possible Solution:
Use one random tournament question as holdout

Pre Testing
N = 20 Pretest
§  Internal Pre-Test indicated too long and complex interviews
§  Real Pre-Test were promising: respondents liked the
questions and found good sense in them
§  => we increased the number of questions slightly

Field Work
N = 200 face-to-face CAPI
§  Good response
§  Happy respondents
§  Relevant questions
§  Positive feedback
§  Average duration around 30 minutes

Results
Utility Values
§  Individual level utilities calculated with HB
§  All results met common sense expectations
§  Some surprises and hints for segmentation
-100
-80
-60
-40
-20
0
20
40
60
80
100

Results
Price
§  Linear price function result in very large price interval with
only few data points at the end of the interval
(base price + all possible level prices +/- 50%)
§  Use of piecewise price function with 5 data points
§  Check data! (get_acbc_prices.exe tool)
§  Rather flat price elasticity which needed calibration

Results
Price
§  Due to the large interval price the IMPORTANCE of might
gets over-estimated
0
5
10
15
20
25
30
35
Att1
Att2
Att3
Att4
Att5
Att6
Att7
Att8
Att9
Att10
Att11
Att12
Att13
Price

Results
Price
§  Despite non price focus of project a calibration of PRICE
ELASTICITY seem to be necessary
0
10
20
30
40
50
60
70
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16 P17 P18 P19 P20 P21 P22 P23 P24

Results
Simulations
§  Base Case scenario tuned to current market shares
§  Best attribute levels search based on Profit Contribution
modeling
§  Product optimization
§  Product range optimization

Results
Example for Product Optimisation
20
30
40
50
60
70
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14
0,25
0,5
0,75
1
1,25
1,5
SOP BC
SOP IMP
PC1 BC
PC1 IMP
SOP PC1

Results
Benefits of the Study
§  Definition for new product development
§  Improvement of package design
§  Optimization of Product range

Lessons Learned
ACBC Pro
§  Intuitive to clients
§  Realistic and relevant interview for respondents
§  Smaller sample size possible
§  Reliable results

Lessons Learned
ACBC Con
§  Price range definition
§  Lack of Alternative Specific Designs
§  Danger of prohibitions
§  Measurement and simulation of price elasticity

Limitations
No Alternative Specific Designs
Limited Graphics
Flat price elasticity
Lack of experience
Difficult design decisions
Model Scenarios
Complex product features and options
Non-Compensatory Attributes
Many Attributes
Small Sample Available (CPI, B2B)
Deeper insights on individual level
Markets
Industrial
B2B
Durables
Conclusions
ACBC Application

A new tool in the
MR Toolbox!!
CBC ACA M-DCVA
ü Rarely used
ü Traditional
ü Not CJ
ü M. Attributes
ü Efficient
ACBC
ü Attributes ++
ü Non compensatory
ü Realistic interview
ü Weak on pricing
ü Individual level
ü Small sample
ü Mostly used
ü Full Profile
ü ADM
ü Strong for Pricing
ü Ind. level (HB)
ü IIA
ü Adaptive
ü Attributes++
ü Weak on Pricing
ü Ind. Level
According to the latest “Report on
Conjoint Analysis Usage among
Sawtooth Software Customers” 9% of
all projects are done with ACBC

Ü ACBC study was great
success
Ü ACBC is intuitive to
clients and respondents
Ü ACBC will not replace
CBC or other methods
but it will become an
additional tool
So what?

Questions ?
Stefan Binner
bms
Sue York
The Future Place

Stefan binner advanced quant - 2011

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