MMENUENU--BBASEDASED CCHOICEHOICE MMODELSODELS

A Technical Note on MenuA Technical Note on Menu--Based Choice ModelsBased Choice Models

Dr. Steven CosgroveDr. Steven CosgroveDr. Steven CosgroveDr. Steven Cosgrove

MBC

Menu-based Choice modelling (MBC) is an

innovative conjoint-based method, specifically

designed for markets, where the purchase

choice is based on a mass customization. The

interview process in MBC is different, as it

builds its ideal concept/combinations of items

using a menu, perfectly mimicking the type of

mass customization consumers face in real life.

Menu-based choice models perform better

because it is a single model that predicts all

combinational outcomes.MBC is a good fit for

many business questions, and reflects real-

world buying situations.

Advantages

1. Reflects real-world buying situations (mass customization)

2. Lets you configure service options

2

Three types of MBC models:

1. Different packages including a certain number of

features (e.g. Neteflix,SaaS on-line services)

2. Products are offered in combos side by side with á la

carte items(McDonalds, Dell, mobile phone plans,

banking services)

3. Customers build their own product from scratch (eg.,

Ford, BMW)

2. Lets you configure service options

3. Enables you to maximize configurations for revenue and uptake

4. Lets you analye complex model—choice between packages anda la carte?

5. Anticpate sales and profits (mass customization)

Disadvantages

1. MBC requires more expertise than other conjoint (CBC ACBC).

Menu-based Choice modelling (MBC) is an innovative conjoint-based method specifically designed for markets where the purchase choice is based on a

mass customization.

Conjoint analysis is a popular marketing research tool to help companies determine the optimal features and pricing for their products.

Conjoint analysis determines the relative

importance that consumers attach to attributes and the value or utility they attach

to the different levels of the attributes.

Adaptive conjoint analysis

(ACBC) made some improvements by including

a set of exercises to

Menu-based conjoint

(MBC) creates hypothetical-choice models that

estimate the probabiliy of picking a combo or

individual items presented in the menu at diiferent

prices.

3

The research method involves the presentation

of alternative configurations of products,

usually in pairs, to the respondent, for him/her to

select one. levels of the various attributes are

usually randomly selected for presentation.

Preferences can be simulated using the model, and the

results of the simulation runs can be used to derive the optimal configuration and

price models.

Traditional choice-based

conjoint (CBC )asked respondents to trade-off a

set of options and asked their preference, if any. given the

number of permutations, the number of attributes and

levels were limited.

a set of exercises to determine the most

relevant attributes for a particular respondent

before asking the respondent to trade-off.

acbc not only increased the number of attributes and

levels, it also reduced options that were irrelevant to the

respondent.

The interview process in MBC is different, as respondents build their ideal concept/combinations of items using a menu, perfectly mimicking the type of mass customization that they would face in real life.

Some examples of mass customization sales

include:

1. Automobile options,

2. Employee benefit packages,

3. Pharma –drug therapy choices,

4. Restaurant menu (fast-food value menus),

5. Insurance coverage( layers and

Three types of MBC models:

1. Different packages including a certain number of features (e.g. Neteflix,SaaS on-line services)

2. Products are offered in combos side by side with á la carte items(McDonalds, Dell, mobile phone plans, banking services)

4

5. Insurance coverage( layers and

configuration),

6. Mobile phones, internet, cable bundles,

7. Hotels,

8. Banking Service,

9. Software as a Service (SaaS),

10. Shared resouces and outsourcing IT, as

well as cloud services.

3. Customers build their own product from scratch (eg., Ford, BMW)

Menu-based choice model performs better because it is a single model that predicts all combinational outcomes.

5

Each respondent completed 8 menu-based choice tasks involving selections of value meal vs. a la carte options as shown . Source: Orme, Bran K. , Sawtooth Software: Research Paper Series, Task Order Effects in Menu-Based Choice Modelling, p. 3.

Each respondent completed 8 menu-based choice tasks involving selections of car model vs. a la carte options as shown . Source: Orme, Bran K. , Sawtooth Software: Research Paper Series, Task Order Effects in Menu-Based Choice Modelling, p. 10.

MBC is a good fit for many business questions, and reflects real-world buying situations.

AdvantagesReflects real-world buying situations

(mass customization)Lets you configure service options

Enables you to maximize configurations for revenue and

uptakeLets you analyze complex model—

6

Lets you analyze complex model—choice between packages and

a la carte?Anticipate sales and profits (mass

customizationDisadvantages

MBC requires more expertise than other conjoint programs (CBC

ACBC).

MBC models include the relative importance of each of the attributes (including packages) , as well as the ability to run simulations to predict market preference.

Total Equal to 1 Equal to 2 Equal to 3 Equal to 4 Equal to 5 Equal to 6 Equal to 7

Total Respondents 612 190 156 33 116 37 32 48

Rescaling Method:

Total Equal to 1 Equal to 2 Equal to 3 Equal to 4 Equal to 5 Equal to 6 Equal to 7

Plug-in Hybrid Pow ertrain (costs up to 50% more compared to a gasoline engine, but signif icantly low er fuel cost (including electricity) About 70% increase in fuel economy (mpg) and signif icant reduction in emissions compared to a comparable gasoline en -56,84 -52,88 -62,03 -60,11 -54,95 -56,15 -59,55 -56,73

Extended Range Pow ertrain (Up to 100% more compared to a gasoline engine, but substantially low er fuel cost (including energy) Up to 100% increase in fuel economy (mpg) and signif icant reduction in emissions compared to a comparable gasoline engine w ith 7,90 5,73 12,35 12,66 3,57 10,49 -1,74 13,60

All- electric or Battery Pow ertrain (Up to 100% more compared to a gasoline engine, substantially low er fuel (energy) cost) Zero fuel consumption and zero emissions, driving range on full charge is limited, typically 100 miles 48,95 47,15 49,68 47,44 51,38 45,66 61,29 43,14

Slow charging at 110V (no extra charge) 12 to 14 Hrs charging time -64,79 -71,07 -58,22 -42,28 -68,06 -56,33 -76,34 -67,68

Fast charging 240V ($500) 6 to 8 Hrs charging time 3,60 1,71 0,42 3,50 9,51 3,75 8,16 4,07

Rapid charging ($1,500) 30 minutes charge time 61,19 69,36 57,80 38,78 58,55 52,59 68,18 63,61

100 miles (no extra charge) -32,51 -34,76 -29,93 -42,81 -31,69 -30,34 -18,23 -38,09

150 miles ($5,000) 0,94 2,27 -0,52 4,45 0,38 -1,02 -0,41 1,80

200 miles ($10,000) 31,57 32,49 30,45 38,37 31,31 31,37 18,65 36,29

No Navigation -53,12 -48,41 -54,38 -66,73 -53,71 -67,73 -48,20 -48,91

Conventional static navigation ($800) Provides shortest/fastest route ignoring traff ic and road conditions 2,09 4,54 -3,14 3,27 3,36 7,90 -1,37 3,36

Dynamic Navigation ($1,200) Provides most energy eff icient route based on traff ic and roadside condition, rated driving performance based on energy/fuel consumption and provides driving suggestions/instructions to conserve fuel/energy 51,03 43,87 57,52 63,46 50,35 59,83 49,57 45,56

Total Equal to 1 Equal to 2 Equal to 3 Equal to 4 Equal to 5 Equal to 6 Equal to 7

Type of plug-in electric engine 26,45 25,01 27,93 26,89 26,58 25,45 30,21 24,97

Charging system 31,49 35,11 29,01 20,27 31,65 27,23 36,13 32,82

Driving range on full charge 16,02 16,81 15,09 20,30 15,75 15,43 9,22 18,59

Navigation 26,04 23,07 27,97 32,55 26,02 31,89 24,44 23,62

Average Importances by New seg_AutoSeg

Total Respondents by New seg_AutoSeg

Average Utility Values by Newseg_AutoSeg

Zero-Centered Diffs

25%

22%18%

14%

12%

6%

3%

Price

Installation

Warranty

Brand

Channel

Consultation

Credit

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Utility scores (part worths) are also produced by conjoint analysis. A utility score is associated with each level of each attribute -- the higher the utility score, the greater its value in terms of its positive impact. When utility scores for each level of each factor for each respondent are combined with respondents’ perceptions of each product or service on each factor, it is possible to simulate customer behavior to determine likely market share a product or service will achieve before committing large sums of money. For example, suppose customers were exposed to individual descriptions of companies.

The values this customer places on each level of each factor are added to obtain a total utility score. In the simulation, the provider with the highest total score will receive the customer’s purchase vote. Averaged across all respondents, market share estimates emerge. In addition, the simulation can be repeated to learn how sales will vary given price changes and different product performance characteristics. Menu-based choice model performs better because it is a single model that simulates all combinational outcomes.