Dirk huisman advanced quant - 2011

Event sponsored by Affinnova All copyright owned by The Future Place and the presenters of the material For more informa=on about Affinnova visit h>p://www. affinnova.com/

For more informa=on about NewMR events visit newmr.org

Advanced Quant Techniques July 14, 2011

MBC, as Easy As ABC? An introduc:on to Menu Based Conjoint

Dirk Huisman, SKIM

Dirk Huisman, SKIM, The Netherlands NewMR Advanced Quant Techniques, July 14, 2011

Dirk Huisman Chairman | SKIM

expect great answers

MBC, as Easy As ABC? An introduction to Menu Based Conjoint


What is Menu-Based Conjoint?

An exercise that replicates a specific kind of choice situation by allowing consumers (respondents) to specify their desired product by selecting single features or bundled group of features. Menu-based conjoint is the family name showing the relation with other variations to conjoint analysis, a class of discrete choice models. You may also call it a build-your-own product exercise.


In “traditional” CBC a consumer choses among full profiles


Traditional CBC is most suitable for “complete” products without optional features

•  Consumers do intuitively choose one out of several pre-defined concepts and repeat the “shopping trip”.

•  Methodology has been validated and results are calibrated to fully mimic reality

but

•  This does not mimic many real life choice situations:


Capturing real life in a fast food restaurant looks as easy as ABC Building your own product is as easy as ordering a meal at Burger King Mmmh, today I

feel for a Whopper. I mean, the

menu, with fries and Coke ..and I could go

large, it’s only $1 more!

Surprise me, they have cookies!

OK, then I’ll not take the menu, just a whopper, and a

cookie And who cares I am about to consume

2500 calories. It’s a balance day.


Choice situations where combining items matters, require Menu Based Conjoint

•  Menu optimization in fast food/branded restaurant chains

•  Converging TLC markets / services: bundling •  BYO computers (e.g. Dell) •  Optional features pricing optimization in automotive

market •  Add-on services in the financial and insurance

services industry •  Mix and Match situations like in apparel


Whopper $3.50 California W. $ 4.50

Omega3 $3.75 Chicken Deli $ 3.50

Cheddar $0.50 American cheese $ 0.75

Crispy Onions $1.50

Bacon $1.50

Curly fries $1.25

French fries $1.05

✔ ✔

✔

✔ Supersize + $

0.25

✔

Total price $ 8.50

Mimicking reality in the choice task is not complex


Or why don’t we build our own computer, as if we’re Dell?


MBC sound like a great idea. Why didn’t we do it earlier?

•  Computational barriers are relieved •  Hundreds of ways you can configure your product •  Computationally not feasible to take all of them into

account •  Lack of rules to meaningfully aggregate and generalize

individual ideal points

•  Recent developments make it easier (not easy) •  New interest in the methodology, better estimates •  Papers and methodological conferences •  Commercially available software to analyze


•  Realistic choice tasks, representative for a different class of choice situations

•  Enables predictions about many items

•  Valuable insights into aspects not captured by CBC •  Most-often chosen combination, explicitly allowing

for interaction effects between items •  Cross-effects price sensitivity and cannibalization

effects •  Menu pricing and discounts

MBC is new. Is it better?


% =mes a single burger is purchased

Cookie Price Price discount for a menu Forecast how a price change for one or more of the menu items impacts revenues

Menu

% =mes cookies are included in an order

MBC results: valuable new insights

Estimate interaction effects between menu items, suggesting cannibalization dynamics


0%

5%

10%

15%

20%

25%

Tofu burger + Vitamin water

+ pecan cookie


+ fries

Tofu burger + Soda + fries

Tofu burger + Soda + salad

Tofu burger + Soda + muesly

yogurt


+ fries

Tofu burger + Fruit juice +

fries

Most chosen combinations of drink and sides when a Tofu burger is chosen

Most notably how menu items perform in conjunction

Observation of the most common combinations suggests the creation of a new menu based on Tofu burger and Vitamin water


Challenges are primarily due to the “infancy” of the approach

•  Analysis approach under development •  Different methods for analyzing different approaches to MBC

and BYO are known •  But we lack a golden standard or precise guidelines; the

final decision is left to the “experience” of the methodologist •  Computationally intensive

•  Survey challenges •  Respondent fatigue in a situation of repetitive tasks needed

for collecting sufficient data point •  Large sample sizes necessary for validity and precision


Q & A

Dirk Huisman SKIM

Sue York The Future Place


For further information: Technical papers about MBC: Bakken, David G. and Megan Kaiser Bond (2004), “Estimating Preferences for Product Bundles vs. a la carte Choices”, Sawtooth Software Conference Proceedings, pp 123-134. Cohen, Steven H. and John C. Liechty (2007), “Have it Your Way: Menu-based conjoint analysis helps marketers understand mass customization”, Marketing Research Magazine, Fall 2007, pp 28-34. Liechty, John, Venkatram Ramaswamy, and Steven H. Cohen (2001), “Choice Menus for Mass Customization: An Experimenal Approach for Analyzing Customer Demand with an Application to a Web-Based Information Service”, Journal of Marketing Research, May 2001, pp 183-196. Rogers, Greg and Tim Renken (2003), “Validation and Calibration of Choice-Based Conjoint for Pricing Research,” Sawtooth Software Conference Proceedings, pp 209-215. Ben-Akiva, M. and S. Gershenfeld (1998), “Multi-featured Products and Services: Analysing Pricing and Bundling Strategies”, Journal of Forecasting, 17. Conklin. M., B. Paris, T. Boehnlien-Kearby, C. Johnson, K. Juhl, A. Zanetti-Polzi, K. Gustafson, B. Palmer, (2007) “Menu Based Choice Models”, ART Forum. Bryan K. Orme,,(2010) “Menu-Based Choice Modeling Using Traditional Tools”, Sawtooth Software, RESEARCH PAPER SERIES


contact us or follow us online!

SKIM

Dirk Huisman | Chairman [email protected] | +31 102823561

twi>er.com/ skimgroup

facebook.com/ skimgroup

linkedin.com/ company/skim

youtube.com/ skimvideos skimgroup.com


contact us or follow us online!

SKIM | Locations New York, USA Juan Andrés Tello [email protected] +1 201 963 8430 Rotterdam, NL Mini Kalivianakis [email protected] +31 10 282 3535

twi>er.com/ skimgroup

facebook.com/ skimgroup

linkedin.com/ company/skim

youtube.com/ skimvideos skimgroup.com

Geneva, Switzerland Vicky Nef [email protected] +41 22 747 7519 London, UK Debora Corfield [email protected] +44 203 178 6910

Documents

Dirk huisman advanced quant - 2011