SlideShare a Scribd company logo
Chicago New York London Dubai New Delhi Bangalore SingaporeSan Francisco
www.absolutdata.com
© Absolutdata 2014 Proprietary and Confidential
April 30, 2014
Application of MBC in CPG Industry
through Storytelling
2© Absolutdata 2014 Proprietary and Confidential
About Absolutdata
Market
Analytics
Customer
Analytics
Market
Research
Data
Visualization &
Reporting
Big Data Strategy
& Services
Company Overview
 Founded in 2001
 We are decision engineers and apply decision sciences every day to
improve decisions at the world’s largest companies
 Senior management from McKinsey, Kraft, Pfizer, Mitsubishi, Nielsen,
GE, HSBC and Citigroup
 Headquartered in San Francisco and delivery centre in Gurgaon, India
with regional offices in London, Singapore and Dubai
 Significant Investment in capability building – Deepening existing
competencies and diversifying into new areas
 Continued focus on thought leadership – at international
conferences, NASSCOM paper on Marketing Analytics
Corporate Philosophy
Mission
To empower forward-looking
organizations reach new
heights of business
performance through the
optimal use of data
Services Provided
3© Absolutdata 2014 Proprietary and Confidential
A Short Tale of Intelligent Analytics
Introducing the protagonist of this tale Mr. Target who is Product Manager for a leading fast-food restaurant
THE FAST-FOOD RESTAURANT
His job is to decide the different items of the menu
As a consistent performer in his company, he is the go-to guy for all
business related issues
Product Manager
Mr. Target
4© Absolutdata 2014 Proprietary and Confidential
The Problem of Plummeting Revenue
One day Mr. Target gets a frantic call from his Senior Manager Mr. Hassled..
..who is completely hassled by
the falling revenue shares
5© Absolutdata 2014 Proprietary and Confidential
Strategy to Increase Revenue
Mr. Target identifies a two-pronged strategy to increase the restaurant’s revenues
Ticket Size
Increasing per ticket sale for existing
customers
Guest Count
Incremental volume from new
customers
6© Absolutdata 2014 Proprietary and Confidential
Revamping the Menu – Means to an End
He knows that revamping the menu is the key and narrows down to the following business questions
 Based on demand and revenue, what are the right combos and
optimal price for each?
 Which menu items are profitable complements with the combo
offerings at what price?
 What should be the optimal price for the individual items being sold?
Optimal Menu & Pricing
New Product – Substitute or Complement
 Would the introduction of “Tacos” cause any cannibalization?
?

7© Absolutdata 2014 Proprietary and Confidential
Search for the Right Approach – Does CBC Answer the Questions?
 Mr. Target’s instinctive solution to this problem is Choice Based
Conjoint (CBC)
 But he soon realizes that CBC is not the best approach to this
problem. This is because in a CBC exercise, respondents make a
single choice among pre-designed available options and they
cannot build their preferred choice
 What Mr. Target needs is an approach that mimics the actual
purchase process of a customer who visits his restaurant and
creates his order!
?

With the business questions in place, all Mr. Target needs is the right research approach
8© Absolutdata 2014 Proprietary and Confidential
Mr. Target’s Eureka Moment – Menu Based Conjoint
 MBC is a choice modeling method used for products and services
that allow buyers to choose from one to many items (or bundles)
on each menu where each item has a price associated to it
 MBC is the perfect solution to Mr. Target’s problem as it would:
– Compare preferences for different combos and a la carte menu
items offered in the fixed menu at different prices
– Optimize the product offerings for maximizing revenue and
uptake
– Anticipate the sales and profits
?

Mr. Target suddenly remembers his notes from a conference where they spoke about Menu Based Conjoint
(MBC)
9© Absolutdata 2014 Proprietary and Confidential
Root of all Hassles – Underperforming Menu
This shows the current menu available at the fast food chain
COMBO MEALS
Classic Combo
$3.00
Cheese Burger Combo $3.50
Pizza Combo
$4.00
SIGNATURE MAINS
Basic Burger
$2.00
Cheese Burger
$2.50
Pizza
$3.5
SIDES & BEVERAGES
Fries
$1.50
Drink
$1.00
10© Absolutdata 2014 Proprietary and Confidential
Point of Arrival – Hypotheses to Test
Note: Respondents are shown several scenarios with variations in products and price. The selections in the scenarios is indicative of their preference.
Mr. Target carefully puts down certain hypotheses he plans to test using Menu Based Conjoint
SIGNATURE MAINS
Basic Burger
$2.00
Cheese Burger
$2.50
Pizza
$3.5
COMBO MEALS
Classic Combo
$3.00
Cheese Burger Combo
$3.50
Pizza Combo
$4.00
SIDES & BEVERAGES
Fries
$1.50
Drink
$1.00
Signature Mains
 Change prices of individual items to identify optimal
price
 Introduction of “Tacos”
Combo Meals
 Change prices for different bundles to maximize
revenue and uptake
Sides & Beverages
 Change prices of Sides and Beverages to identify
profitable complements with the combo offerings
11© Absolutdata 2014 Proprietary and Confidential
Please Make your Selection (1 of 3)
Change in Price of Drink
Note: This is only for illustrative purpose
Classic combo selected with a la carte as pizza, fries & drink on the screen shown
Hey!! I think I’ll buy
an extra drink along
with the Pizza.
Respondent
COMBO MEALS
Classic Combo
$3.00
Cheese Burger
Combo $3.50
Pizza Combo
$4.00
SIGNATURE MAINS
Basic
Burger
$2.00
Cheese
Burger
$2.50
Pizza
$3.5
SIDES & BEVERAGES
Fries
$1.50
Drink
$1.00
P
PP P
12© Absolutdata 2014 Proprietary and Confidential
Please Make your Selection (2 of 3)
Addition of Tacos & Change in Price of Classic Combo, Basic Burger, Cheese Burger
Note: This is only for illustrative purpose
With change in menu items and introduction of tacos, classic combo selected with tacos, fries & drink but NOT
pizza
COMBO MEALS
Classic Combo
$3.00
Cheese Burger
Combo $3.50
Pizza Combo
$4.00
Tacos Combo
$4.00
SIGNATURE MAINS
Basic
Burger
$2.00
Cheese
Burger
$2.50
Pizza
$3.5
Tacos
$2.0
SIDES & BEVERAGES
Fries
$1.50
Drink
$1.00
P
P PP
Respondent
Oh!! they now have
Tacos and its cheaper
than the Pizza. So, I’m
going to go with that
for now
13© Absolutdata 2014 Proprietary and Confidential
Please Make your Selection (3 of 3)
Change in Price of Pizza Combo, Pizza and Fries
Note: This is only for illustrative purpose
With Pizza at a lower price and classic combo at an increased price, both these items selected along with fries &
drink
COMBO MEALS
Classic Combo
$3.00
Cheese Burger
Combo $3.50
Pizza Combo
$4.00
Tacos Combo
$4.00
SIGNATURE MAINS
Basic
Burger
$2.00
Cheese
Burger
$2.50
Pizza
$3.5
Tacos
$2.0
SIDES & BEVERAGES
Fries
$1.50
Drink
$1.00
P
P P
P
P
The Tacos are more
expensive and the
Pizza is cheaper.
Hmm.. I think I will
buy Pizza instead.
Respondent
14© Absolutdata 2014 Proprietary and Confidential
Insights (1 of 4): Right Combos at the Right Prices
MBC helps identify the most preferred combo at the right price by allowing to compare performances of combos
at different prices
Classic Combo is the most preferred
combo amongst the combos offered
Optimized Price for
Classic Combo is
$3.25
-20%
-10%
0%
10%
20%
30%
$2.5 $2.75 $3 $3.25 $3.5 $4
Price Curve for Classic Combo
Revenue Transaction
0%
20%
40%
60%
80%
100%
Classic… Cheese Burger… Pizza…
Preference Curve for Combos
PreferenceShares Base price%agechangeoverBaseCase
15© Absolutdata 2014 Proprietary and Confidential
Insights (2 of 4): Profitable Complements with Combo
MBC helps identify the most profitable complement at the optimal price which can be offered with the combo
People purchase pizza with Classic
combo and its removal would lead to
decrease in combo off takes
Optimized Price for
Pizza is
$3.00
-20%
-10%
0%
10%
20%
30%
$2.75 $3.0 $3.25 $3.5 $3.75 $4.0
Price Curve for Pizza
Revenue Transaction
Base price
$3.0 is the optimal price point for Pizza
since a decline from $3.5 to $3 shows a
significant increase (~8%) in the number of
customers as well as the total revenue
over current menu
16© Absolutdata 2014 Proprietary and Confidential
Insights (3 of 4): Optimal Price for Sides & Beverages
MBC also helps understand the profitable sides & beverages at their optimal price points
Price of fries can be increased to
$1.75 from $1.5 as it would only lead
to a drop of 3% in purchase
Price of fries can be increased to
$1.75 from $1.5 as it would only lead
to a drop of 3% in purchase
0%
10%
20%
30%
$1.0 $1.5 $2 $2.5 $3 $3.5
Price Curve for Drink
0%
10%
20%
30%
$1.0 $1.25 $1.5 $1.75 $2 $2.5
Price Curve for Fries
DemandDemand
17© Absolutdata 2014 Proprietary and Confidential
Insights (4 of 4): New Product – A Substitute or Complement?
MBC helps understand the cannibalization of a la carte items when prices are changed or new items added to
the menu
Pizza & Tacos are purchased by
different consumer segments and do
not cannibalize each other
Optimized Price for Taco
Launch
$2.00
0%
10%
20%
30%
$1.5 $1.75 $2 $2.5 $3 $3.5
Price Curve for Tacos
Demand
After $2 there is sudden decrease in the
demand for Tacos and hence $2 is the
optimal price point to introduce Tacos for
maximum off take
18© Absolutdata 2014 Proprietary and Confidential
Mr. Target hits the Jackpot – The New and Improved Menu
MBC helped Mr. Target to decide his new and improved optimized menu to increase his company’s revenue
shares
COMBO MEALS
Classic Combo
$3.00
Cheese Burger Combo
$3.50
Pizza Combo
$4.00
SIGNATURE MAINS
Basic Burger
$1.50
Cheese Burger
$1.50
Pizza
$3.0
Tacos
$2.0
SIDES & BEVERAGES
Fries
$1.75
Drink
$1.50
Note: Addition of Tacos at $2; Classic Combo, Fries & Drink price increased; Pizza price decreased
19© Absolutdata 2014 Proprietary and Confidential
Mr. Target wins the Market
9%
5% 4%
Ticket Size Guest Count1 2
Increase in total
revenue
The results yielded a 9% revenue growth from both existing and new consumers
20© Absolutdata 2014 Proprietary and Confidential
Industry Application of Menu Based Conjoint
Industry
Applications
of MBC
Software as a Service (SaaS)
Different packages with certain features
Automobile Industry
‘Build Your Own’ Car
Pharma – Drug Therapy
Combination of drugs for prescription
Financial Sector
Multiple services that can be add-ons
Shared Resources & Outsourcing IT
Bundling services from different vendors
21© Absolutdata 2014 Proprietary and Confidential
Conclusion – A Short Summary
MBC gives more power to consumers by allowing consumers to select one to multiple options
from a menu to indicate their preference. It is most useful in in markets where customers have
freedom to customize an existing product or build their own package.
It can help answer the following business questions:
 Understanding trade-offs between pre-configured bundles versus single features (à la carte
options)
 Identify the right bundle of products to offer
 Price the bundle and individual products optimally
 Identify substitutes vs. compliments from the menu
 Does reducing the price for an item cause a different item on the menu to be chosen more
likely (or even less likely)?
 Enables to maximize configurations for revenue and uptake
22© Absolutdata 2014 Proprietary and Confidential
For more information visit www.absolutdata.com
For queries, please write to info@absolutdata.com
Name
Designation
Phone:
Email:
Follow us on:

More Related Content

What's hot

Colgate palmolive HBR case study
Colgate palmolive HBR case studyColgate palmolive HBR case study
Colgate palmolive HBR case study
Roshan Tathed
 
Consumer behaviour tooth paste industries
Consumer behaviour tooth paste industriesConsumer behaviour tooth paste industries
Consumer behaviour tooth paste industries
Ranjeet Singh
 
Decision Making 2013
Decision Making 2013 Decision Making 2013
Decision Making 2013
Evolution Insights - Dale Henry
 
Colgate- The Precision Toothbrush
Colgate- The Precision ToothbrushColgate- The Precision Toothbrush
Colgate- The Precision Toothbrush
Prasham Bhargava
 
Analyzing the spillover roles of user-generated reviews on purchases: Evidenc...
Analyzing the spillover roles of user-generated reviews on purchases: Evidenc...Analyzing the spillover roles of user-generated reviews on purchases: Evidenc...
Analyzing the spillover roles of user-generated reviews on purchases: Evidenc...
Gene Moo Lee
 
five:am Marketing Research Proposal
five:am Marketing Research Proposalfive:am Marketing Research Proposal
five:am Marketing Research Proposal
Jonathan Zhang
 
Colgate palmolive company- the precision toothbrush (case study)
Colgate palmolive company- the precision toothbrush (case study)Colgate palmolive company- the precision toothbrush (case study)
Colgate palmolive company- the precision toothbrush (case study)
Duruva SSKG
 
NCA Grocery Shopper Survey July 2009
NCA Grocery Shopper Survey July 2009NCA Grocery Shopper Survey July 2009
NCA Grocery Shopper Survey July 2009
Amarach Research
 

What's hot (10)

Mathilde Beljaarts Metrix Lab
Mathilde Beljaarts Metrix LabMathilde Beljaarts Metrix Lab
Mathilde Beljaarts Metrix Lab
 
Colgate palmolive HBR case study
Colgate palmolive HBR case studyColgate palmolive HBR case study
Colgate palmolive HBR case study
 
Consumer behaviour tooth paste industries
Consumer behaviour tooth paste industriesConsumer behaviour tooth paste industries
Consumer behaviour tooth paste industries
 
Decision Making 2013
Decision Making 2013 Decision Making 2013
Decision Making 2013
 
Colgate- The Precision Toothbrush
Colgate- The Precision ToothbrushColgate- The Precision Toothbrush
Colgate- The Precision Toothbrush
 
Analyzing the spillover roles of user-generated reviews on purchases: Evidenc...
Analyzing the spillover roles of user-generated reviews on purchases: Evidenc...Analyzing the spillover roles of user-generated reviews on purchases: Evidenc...
Analyzing the spillover roles of user-generated reviews on purchases: Evidenc...
 
five:am Marketing Research Proposal
five:am Marketing Research Proposalfive:am Marketing Research Proposal
five:am Marketing Research Proposal
 
Home Care in Singapore
Home Care in SingaporeHome Care in Singapore
Home Care in Singapore
 
Colgate palmolive company- the precision toothbrush (case study)
Colgate palmolive company- the precision toothbrush (case study)Colgate palmolive company- the precision toothbrush (case study)
Colgate palmolive company- the precision toothbrush (case study)
 
NCA Grocery Shopper Survey July 2009
NCA Grocery Shopper Survey July 2009NCA Grocery Shopper Survey July 2009
NCA Grocery Shopper Survey July 2009
 

Similar to Application of MBC through Storytelling in CPG Industry

What’s on the Menu? An Introduction to Menu Based Choice
What’s on the Menu? An Introduction to Menu Based ChoiceWhat’s on the Menu? An Introduction to Menu Based Choice
What’s on the Menu? An Introduction to Menu Based Choice
Ray Poynter
 
Proven Menu Engineering Techniques - 2017 Mid America Restaurant Expo
Proven Menu Engineering Techniques - 2017 Mid America Restaurant ExpoProven Menu Engineering Techniques - 2017 Mid America Restaurant Expo
Proven Menu Engineering Techniques - 2017 Mid America Restaurant Expo
Return On Ingredients
 
Brand Strategy: The Redefinition of Value
Brand Strategy: The Redefinition of ValueBrand Strategy: The Redefinition of Value
Brand Strategy: The Redefinition of Value
Anya C. Gonzales
 
Happy planet presentation v8
Happy planet presentation v8Happy planet presentation v8
Happy planet presentation v8Ezgi Em
 
Price, income &_consumption
Price, income &_consumptionPrice, income &_consumption
Price, income &_consumption
karun11
 
Marketing Plan
Marketing PlanMarketing Plan
Marketing PlanScott Nunn
 
Food truck business plan example
Food truck business plan exampleFood truck business plan example
Food truck business plan example
upmetrics.co
 
Final Project
Final ProjectFinal Project
Final Project
Andrea Li
 
Mm assi no 6 positioning and pricing
Mm assi no 6 positioning and pricingMm assi no 6 positioning and pricing
Mm assi no 6 positioning and pricingNajeebhemat Malikzia
 
SkillBuilder5PepsiCo
SkillBuilder5PepsiCoSkillBuilder5PepsiCo
SkillBuilder5PepsiCoLucas Meyer
 
Improve Your Menu Engineering
Improve Your Menu EngineeringImprove Your Menu Engineering
Improve Your Menu Engineering
Return On Ingredients
 
Spicy gypsy food truck
Spicy gypsy food truckSpicy gypsy food truck
Spicy gypsy food truck
Amila Rathnayake
 
Berry products case product concept & marketing modeling via facebook
Berry products case   product concept & marketing modeling via facebookBerry products case   product concept & marketing modeling via facebook
Berry products case product concept & marketing modeling via facebook
CMYK Ingredients
 
Berry products case: product concept & marketing modeling via facebook
Berry products case:   product concept & marketing modeling via facebookBerry products case:   product concept & marketing modeling via facebook
Berry products case: product concept & marketing modeling via facebook
Ksenia Zazhigina
 
12. Basic Hotel Accounting Cost Control #3 by Dino Leonandri
12. Basic Hotel Accounting Cost Control #3 by Dino Leonandri12. Basic Hotel Accounting Cost Control #3 by Dino Leonandri
12. Basic Hotel Accounting Cost Control #3 by Dino Leonandri
DINOLEONANDRI
 
12. Basic Hotel's Accounting by Dino Leonandri
12. Basic Hotel's Accounting by Dino Leonandri12. Basic Hotel's Accounting by Dino Leonandri
12. Basic Hotel's Accounting by Dino Leonandri
DINOLEONANDRI
 
Unit 2 lesson 2 presentation
Unit 2 lesson 2 presentationUnit 2 lesson 2 presentation
Unit 2 lesson 2 presentation
Derek D'Angelo
 
How to make paid search (google ad words) work for your business
How to make paid search (google ad words) work for your businessHow to make paid search (google ad words) work for your business
How to make paid search (google ad words) work for your business
Claire Edmondson
 

Similar to Application of MBC through Storytelling in CPG Industry (20)

What’s on the Menu? An Introduction to Menu Based Choice
What’s on the Menu? An Introduction to Menu Based ChoiceWhat’s on the Menu? An Introduction to Menu Based Choice
What’s on the Menu? An Introduction to Menu Based Choice
 
Proven Menu Engineering Techniques - 2017 Mid America Restaurant Expo
Proven Menu Engineering Techniques - 2017 Mid America Restaurant ExpoProven Menu Engineering Techniques - 2017 Mid America Restaurant Expo
Proven Menu Engineering Techniques - 2017 Mid America Restaurant Expo
 
Marketing business plan
Marketing business planMarketing business plan
Marketing business plan
 
Brand Strategy: The Redefinition of Value
Brand Strategy: The Redefinition of ValueBrand Strategy: The Redefinition of Value
Brand Strategy: The Redefinition of Value
 
Happy planet presentation v8
Happy planet presentation v8Happy planet presentation v8
Happy planet presentation v8
 
Price, income &_consumption
Price, income &_consumptionPrice, income &_consumption
Price, income &_consumption
 
Abc
AbcAbc
Abc
 
Marketing Plan
Marketing PlanMarketing Plan
Marketing Plan
 
Food truck business plan example
Food truck business plan exampleFood truck business plan example
Food truck business plan example
 
Final Project
Final ProjectFinal Project
Final Project
 
Mm assi no 6 positioning and pricing
Mm assi no 6 positioning and pricingMm assi no 6 positioning and pricing
Mm assi no 6 positioning and pricing
 
SkillBuilder5PepsiCo
SkillBuilder5PepsiCoSkillBuilder5PepsiCo
SkillBuilder5PepsiCo
 
Improve Your Menu Engineering
Improve Your Menu EngineeringImprove Your Menu Engineering
Improve Your Menu Engineering
 
Spicy gypsy food truck
Spicy gypsy food truckSpicy gypsy food truck
Spicy gypsy food truck
 
Berry products case product concept & marketing modeling via facebook
Berry products case   product concept & marketing modeling via facebookBerry products case   product concept & marketing modeling via facebook
Berry products case product concept & marketing modeling via facebook
 
Berry products case: product concept & marketing modeling via facebook
Berry products case:   product concept & marketing modeling via facebookBerry products case:   product concept & marketing modeling via facebook
Berry products case: product concept & marketing modeling via facebook
 
12. Basic Hotel Accounting Cost Control #3 by Dino Leonandri
12. Basic Hotel Accounting Cost Control #3 by Dino Leonandri12. Basic Hotel Accounting Cost Control #3 by Dino Leonandri
12. Basic Hotel Accounting Cost Control #3 by Dino Leonandri
 
12. Basic Hotel's Accounting by Dino Leonandri
12. Basic Hotel's Accounting by Dino Leonandri12. Basic Hotel's Accounting by Dino Leonandri
12. Basic Hotel's Accounting by Dino Leonandri
 
Unit 2 lesson 2 presentation
Unit 2 lesson 2 presentationUnit 2 lesson 2 presentation
Unit 2 lesson 2 presentation
 
How to make paid search (google ad words) work for your business
How to make paid search (google ad words) work for your businessHow to make paid search (google ad words) work for your business
How to make paid search (google ad words) work for your business
 

More from Absolutdata Analytics

Seven questions you must answer before starting concept research
Seven questions you must answer before starting concept researchSeven questions you must answer before starting concept research
Seven questions you must answer before starting concept researchAbsolutdata Analytics
 
Navik Concept Test Overview Webinar
Navik Concept Test Overview WebinarNavik Concept Test Overview Webinar
Navik Concept Test Overview Webinar
Absolutdata Analytics
 
Shared Data - Assured Success
Shared Data - Assured SuccessShared Data - Assured Success
Shared Data - Assured Success
Absolutdata Analytics
 
When Less Is More: Focusing on the Persuadable Guest
When Less Is More: Focusing on the Persuadable GuestWhen Less Is More: Focusing on the Persuadable Guest
When Less Is More: Focusing on the Persuadable Guest
Absolutdata Analytics
 
'No menu - Give us the Chef's Special'
'No menu - Give us the Chef's Special' 'No menu - Give us the Chef's Special'
'No menu - Give us the Chef's Special'
Absolutdata Analytics
 
Mobile Behavioral Analytics - A new window on the soul
Mobile Behavioral Analytics - A new window on the soulMobile Behavioral Analytics - A new window on the soul
Mobile Behavioral Analytics - A new window on the soulAbsolutdata Analytics
 
Mobile Behavioural Analytics - A new window on the soul
Mobile Behavioural Analytics - A new window on the soulMobile Behavioural Analytics - A new window on the soul
Mobile Behavioural Analytics - A new window on the soulAbsolutdata Analytics
 
3 Steps to Influence Purchase Decision Through Social Media
3 Steps to Influence Purchase Decision Through Social Media3 Steps to Influence Purchase Decision Through Social Media
3 Steps to Influence Purchase Decision Through Social Media
Absolutdata Analytics
 
Innovations in Market Mix Modelling
Innovations in Market Mix Modelling Innovations in Market Mix Modelling
Innovations in Market Mix Modelling Absolutdata Analytics
 
(MRSI - 3/3) Strategic country clusters using ensemble clustering methodolgie...
(MRSI - 3/3) Strategic country clusters using ensemble clustering methodolgie...(MRSI - 3/3) Strategic country clusters using ensemble clustering methodolgie...
(MRSI - 3/3) Strategic country clusters using ensemble clustering methodolgie...
Absolutdata Analytics
 
(MRSI- 2/3) Re-engineering Segmentation methodologies for an Enriching Custom...
(MRSI- 2/3) Re-engineering Segmentation methodologies for an Enriching Custom...(MRSI- 2/3) Re-engineering Segmentation methodologies for an Enriching Custom...
(MRSI- 2/3) Re-engineering Segmentation methodologies for an Enriching Custom...
Absolutdata Analytics
 
Adapting conjoint to the mobile phenomenon
Adapting conjoint to the mobile phenomenonAdapting conjoint to the mobile phenomenon
Adapting conjoint to the mobile phenomenon
Absolutdata Analytics
 
Multi Channel Attribution - Driving Marketing Spend Planning In The Big Data Age
Multi Channel Attribution - Driving Marketing Spend Planning In The Big Data AgeMulti Channel Attribution - Driving Marketing Spend Planning In The Big Data Age
Multi Channel Attribution - Driving Marketing Spend Planning In The Big Data Age
Absolutdata Analytics
 
Camera ready sentiment analysis : quantification of real time brand advocacy ...
Camera ready sentiment analysis : quantification of real time brand advocacy ...Camera ready sentiment analysis : quantification of real time brand advocacy ...
Camera ready sentiment analysis : quantification of real time brand advocacy ...
Absolutdata Analytics
 
Customer analytics fast facts v3
Customer analytics fast facts v3Customer analytics fast facts v3
Customer analytics fast facts v3
Absolutdata Analytics
 
Optimization as a Golden Layer - Chris Diener, SVP Analytics, Absolutdata
Optimization as a Golden Layer - Chris Diener, SVP Analytics, AbsolutdataOptimization as a Golden Layer - Chris Diener, SVP Analytics, Absolutdata
Optimization as a Golden Layer - Chris Diener, SVP Analytics, Absolutdata
Absolutdata Analytics
 
From 'I think' to 'I know'
From 'I think' to 'I know'From 'I think' to 'I know'
From 'I think' to 'I know'
Absolutdata Analytics
 

More from Absolutdata Analytics (18)

Seven questions you must answer before starting concept research
Seven questions you must answer before starting concept researchSeven questions you must answer before starting concept research
Seven questions you must answer before starting concept research
 
Navik Concept Test Overview Webinar
Navik Concept Test Overview WebinarNavik Concept Test Overview Webinar
Navik Concept Test Overview Webinar
 
Skin care report
Skin care reportSkin care report
Skin care report
 
Shared Data - Assured Success
Shared Data - Assured SuccessShared Data - Assured Success
Shared Data - Assured Success
 
When Less Is More: Focusing on the Persuadable Guest
When Less Is More: Focusing on the Persuadable GuestWhen Less Is More: Focusing on the Persuadable Guest
When Less Is More: Focusing on the Persuadable Guest
 
'No menu - Give us the Chef's Special'
'No menu - Give us the Chef's Special' 'No menu - Give us the Chef's Special'
'No menu - Give us the Chef's Special'
 
Mobile Behavioral Analytics - A new window on the soul
Mobile Behavioral Analytics - A new window on the soulMobile Behavioral Analytics - A new window on the soul
Mobile Behavioral Analytics - A new window on the soul
 
Mobile Behavioural Analytics - A new window on the soul
Mobile Behavioural Analytics - A new window on the soulMobile Behavioural Analytics - A new window on the soul
Mobile Behavioural Analytics - A new window on the soul
 
3 Steps to Influence Purchase Decision Through Social Media
3 Steps to Influence Purchase Decision Through Social Media3 Steps to Influence Purchase Decision Through Social Media
3 Steps to Influence Purchase Decision Through Social Media
 
Innovations in Market Mix Modelling
Innovations in Market Mix Modelling Innovations in Market Mix Modelling
Innovations in Market Mix Modelling
 
(MRSI - 3/3) Strategic country clusters using ensemble clustering methodolgie...
(MRSI - 3/3) Strategic country clusters using ensemble clustering methodolgie...(MRSI - 3/3) Strategic country clusters using ensemble clustering methodolgie...
(MRSI - 3/3) Strategic country clusters using ensemble clustering methodolgie...
 
(MRSI- 2/3) Re-engineering Segmentation methodologies for an Enriching Custom...
(MRSI- 2/3) Re-engineering Segmentation methodologies for an Enriching Custom...(MRSI- 2/3) Re-engineering Segmentation methodologies for an Enriching Custom...
(MRSI- 2/3) Re-engineering Segmentation methodologies for an Enriching Custom...
 
Adapting conjoint to the mobile phenomenon
Adapting conjoint to the mobile phenomenonAdapting conjoint to the mobile phenomenon
Adapting conjoint to the mobile phenomenon
 
Multi Channel Attribution - Driving Marketing Spend Planning In The Big Data Age
Multi Channel Attribution - Driving Marketing Spend Planning In The Big Data AgeMulti Channel Attribution - Driving Marketing Spend Planning In The Big Data Age
Multi Channel Attribution - Driving Marketing Spend Planning In The Big Data Age
 
Camera ready sentiment analysis : quantification of real time brand advocacy ...
Camera ready sentiment analysis : quantification of real time brand advocacy ...Camera ready sentiment analysis : quantification of real time brand advocacy ...
Camera ready sentiment analysis : quantification of real time brand advocacy ...
 
Customer analytics fast facts v3
Customer analytics fast facts v3Customer analytics fast facts v3
Customer analytics fast facts v3
 
Optimization as a Golden Layer - Chris Diener, SVP Analytics, Absolutdata
Optimization as a Golden Layer - Chris Diener, SVP Analytics, AbsolutdataOptimization as a Golden Layer - Chris Diener, SVP Analytics, Absolutdata
Optimization as a Golden Layer - Chris Diener, SVP Analytics, Absolutdata
 
From 'I think' to 'I know'
From 'I think' to 'I know'From 'I think' to 'I know'
From 'I think' to 'I know'
 

Recently uploaded

Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
roli9797
 
Adjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTESAdjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTES
Subhajit Sahu
 
Everything you wanted to know about LIHTC
Everything you wanted to know about LIHTCEverything you wanted to know about LIHTC
Everything you wanted to know about LIHTC
Roger Valdez
 
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
slg6lamcq
 
Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptxData_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
AnirbanRoy608946
 
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
ahzuo
 
My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.
rwarrenll
 
Machine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptxMachine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptx
balafet
 
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
dwreak4tg
 
Malana- Gimlet Market Analysis (Portfolio 2)
Malana- Gimlet Market Analysis (Portfolio 2)Malana- Gimlet Market Analysis (Portfolio 2)
Malana- Gimlet Market Analysis (Portfolio 2)
TravisMalana
 
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfEnhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
GetInData
 
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
mzpolocfi
 
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...
John Andrews
 
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
slg6lamcq
 
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
u86oixdj
 
Learn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queriesLearn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queries
manishkhaire30
 
Adjusting OpenMP PageRank : SHORT REPORT / NOTES
Adjusting OpenMP PageRank : SHORT REPORT / NOTESAdjusting OpenMP PageRank : SHORT REPORT / NOTES
Adjusting OpenMP PageRank : SHORT REPORT / NOTES
Subhajit Sahu
 
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
74nqk8xf
 
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
v3tuleee
 
Nanandann Nilekani's ppt On India's .pdf
Nanandann Nilekani's ppt On India's .pdfNanandann Nilekani's ppt On India's .pdf
Nanandann Nilekani's ppt On India's .pdf
eddie19851
 

Recently uploaded (20)

Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
 
Adjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTESAdjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTES
 
Everything you wanted to know about LIHTC
Everything you wanted to know about LIHTCEverything you wanted to know about LIHTC
Everything you wanted to know about LIHTC
 
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
 
Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptxData_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
 
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
 
My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.
 
Machine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptxMachine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptx
 
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
 
Malana- Gimlet Market Analysis (Portfolio 2)
Malana- Gimlet Market Analysis (Portfolio 2)Malana- Gimlet Market Analysis (Portfolio 2)
Malana- Gimlet Market Analysis (Portfolio 2)
 
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfEnhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
 
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
一比一原版(Dalhousie毕业证书)达尔豪斯大学毕业证如何办理
 
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...
 
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
 
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
 
Learn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queriesLearn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queries
 
Adjusting OpenMP PageRank : SHORT REPORT / NOTES
Adjusting OpenMP PageRank : SHORT REPORT / NOTESAdjusting OpenMP PageRank : SHORT REPORT / NOTES
Adjusting OpenMP PageRank : SHORT REPORT / NOTES
 
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
 
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
 
Nanandann Nilekani's ppt On India's .pdf
Nanandann Nilekani's ppt On India's .pdfNanandann Nilekani's ppt On India's .pdf
Nanandann Nilekani's ppt On India's .pdf
 

Application of MBC through Storytelling in CPG Industry

  • 1. Chicago New York London Dubai New Delhi Bangalore SingaporeSan Francisco www.absolutdata.com © Absolutdata 2014 Proprietary and Confidential April 30, 2014 Application of MBC in CPG Industry through Storytelling
  • 2. 2© Absolutdata 2014 Proprietary and Confidential About Absolutdata Market Analytics Customer Analytics Market Research Data Visualization & Reporting Big Data Strategy & Services Company Overview  Founded in 2001  We are decision engineers and apply decision sciences every day to improve decisions at the world’s largest companies  Senior management from McKinsey, Kraft, Pfizer, Mitsubishi, Nielsen, GE, HSBC and Citigroup  Headquartered in San Francisco and delivery centre in Gurgaon, India with regional offices in London, Singapore and Dubai  Significant Investment in capability building – Deepening existing competencies and diversifying into new areas  Continued focus on thought leadership – at international conferences, NASSCOM paper on Marketing Analytics Corporate Philosophy Mission To empower forward-looking organizations reach new heights of business performance through the optimal use of data Services Provided
  • 3. 3© Absolutdata 2014 Proprietary and Confidential A Short Tale of Intelligent Analytics Introducing the protagonist of this tale Mr. Target who is Product Manager for a leading fast-food restaurant THE FAST-FOOD RESTAURANT His job is to decide the different items of the menu As a consistent performer in his company, he is the go-to guy for all business related issues Product Manager Mr. Target
  • 4. 4© Absolutdata 2014 Proprietary and Confidential The Problem of Plummeting Revenue One day Mr. Target gets a frantic call from his Senior Manager Mr. Hassled.. ..who is completely hassled by the falling revenue shares
  • 5. 5© Absolutdata 2014 Proprietary and Confidential Strategy to Increase Revenue Mr. Target identifies a two-pronged strategy to increase the restaurant’s revenues Ticket Size Increasing per ticket sale for existing customers Guest Count Incremental volume from new customers
  • 6. 6© Absolutdata 2014 Proprietary and Confidential Revamping the Menu – Means to an End He knows that revamping the menu is the key and narrows down to the following business questions  Based on demand and revenue, what are the right combos and optimal price for each?  Which menu items are profitable complements with the combo offerings at what price?  What should be the optimal price for the individual items being sold? Optimal Menu & Pricing New Product – Substitute or Complement  Would the introduction of “Tacos” cause any cannibalization? ? 
  • 7. 7© Absolutdata 2014 Proprietary and Confidential Search for the Right Approach – Does CBC Answer the Questions?  Mr. Target’s instinctive solution to this problem is Choice Based Conjoint (CBC)  But he soon realizes that CBC is not the best approach to this problem. This is because in a CBC exercise, respondents make a single choice among pre-designed available options and they cannot build their preferred choice  What Mr. Target needs is an approach that mimics the actual purchase process of a customer who visits his restaurant and creates his order! ?  With the business questions in place, all Mr. Target needs is the right research approach
  • 8. 8© Absolutdata 2014 Proprietary and Confidential Mr. Target’s Eureka Moment – Menu Based Conjoint  MBC is a choice modeling method used for products and services that allow buyers to choose from one to many items (or bundles) on each menu where each item has a price associated to it  MBC is the perfect solution to Mr. Target’s problem as it would: – Compare preferences for different combos and a la carte menu items offered in the fixed menu at different prices – Optimize the product offerings for maximizing revenue and uptake – Anticipate the sales and profits ?  Mr. Target suddenly remembers his notes from a conference where they spoke about Menu Based Conjoint (MBC)
  • 9. 9© Absolutdata 2014 Proprietary and Confidential Root of all Hassles – Underperforming Menu This shows the current menu available at the fast food chain COMBO MEALS Classic Combo $3.00 Cheese Burger Combo $3.50 Pizza Combo $4.00 SIGNATURE MAINS Basic Burger $2.00 Cheese Burger $2.50 Pizza $3.5 SIDES & BEVERAGES Fries $1.50 Drink $1.00
  • 10. 10© Absolutdata 2014 Proprietary and Confidential Point of Arrival – Hypotheses to Test Note: Respondents are shown several scenarios with variations in products and price. The selections in the scenarios is indicative of their preference. Mr. Target carefully puts down certain hypotheses he plans to test using Menu Based Conjoint SIGNATURE MAINS Basic Burger $2.00 Cheese Burger $2.50 Pizza $3.5 COMBO MEALS Classic Combo $3.00 Cheese Burger Combo $3.50 Pizza Combo $4.00 SIDES & BEVERAGES Fries $1.50 Drink $1.00 Signature Mains  Change prices of individual items to identify optimal price  Introduction of “Tacos” Combo Meals  Change prices for different bundles to maximize revenue and uptake Sides & Beverages  Change prices of Sides and Beverages to identify profitable complements with the combo offerings
  • 11. 11© Absolutdata 2014 Proprietary and Confidential Please Make your Selection (1 of 3) Change in Price of Drink Note: This is only for illustrative purpose Classic combo selected with a la carte as pizza, fries & drink on the screen shown Hey!! I think I’ll buy an extra drink along with the Pizza. Respondent COMBO MEALS Classic Combo $3.00 Cheese Burger Combo $3.50 Pizza Combo $4.00 SIGNATURE MAINS Basic Burger $2.00 Cheese Burger $2.50 Pizza $3.5 SIDES & BEVERAGES Fries $1.50 Drink $1.00 P PP P
  • 12. 12© Absolutdata 2014 Proprietary and Confidential Please Make your Selection (2 of 3) Addition of Tacos & Change in Price of Classic Combo, Basic Burger, Cheese Burger Note: This is only for illustrative purpose With change in menu items and introduction of tacos, classic combo selected with tacos, fries & drink but NOT pizza COMBO MEALS Classic Combo $3.00 Cheese Burger Combo $3.50 Pizza Combo $4.00 Tacos Combo $4.00 SIGNATURE MAINS Basic Burger $2.00 Cheese Burger $2.50 Pizza $3.5 Tacos $2.0 SIDES & BEVERAGES Fries $1.50 Drink $1.00 P P PP Respondent Oh!! they now have Tacos and its cheaper than the Pizza. So, I’m going to go with that for now
  • 13. 13© Absolutdata 2014 Proprietary and Confidential Please Make your Selection (3 of 3) Change in Price of Pizza Combo, Pizza and Fries Note: This is only for illustrative purpose With Pizza at a lower price and classic combo at an increased price, both these items selected along with fries & drink COMBO MEALS Classic Combo $3.00 Cheese Burger Combo $3.50 Pizza Combo $4.00 Tacos Combo $4.00 SIGNATURE MAINS Basic Burger $2.00 Cheese Burger $2.50 Pizza $3.5 Tacos $2.0 SIDES & BEVERAGES Fries $1.50 Drink $1.00 P P P P P The Tacos are more expensive and the Pizza is cheaper. Hmm.. I think I will buy Pizza instead. Respondent
  • 14. 14© Absolutdata 2014 Proprietary and Confidential Insights (1 of 4): Right Combos at the Right Prices MBC helps identify the most preferred combo at the right price by allowing to compare performances of combos at different prices Classic Combo is the most preferred combo amongst the combos offered Optimized Price for Classic Combo is $3.25 -20% -10% 0% 10% 20% 30% $2.5 $2.75 $3 $3.25 $3.5 $4 Price Curve for Classic Combo Revenue Transaction 0% 20% 40% 60% 80% 100% Classic… Cheese Burger… Pizza… Preference Curve for Combos PreferenceShares Base price%agechangeoverBaseCase
  • 15. 15© Absolutdata 2014 Proprietary and Confidential Insights (2 of 4): Profitable Complements with Combo MBC helps identify the most profitable complement at the optimal price which can be offered with the combo People purchase pizza with Classic combo and its removal would lead to decrease in combo off takes Optimized Price for Pizza is $3.00 -20% -10% 0% 10% 20% 30% $2.75 $3.0 $3.25 $3.5 $3.75 $4.0 Price Curve for Pizza Revenue Transaction Base price $3.0 is the optimal price point for Pizza since a decline from $3.5 to $3 shows a significant increase (~8%) in the number of customers as well as the total revenue over current menu
  • 16. 16© Absolutdata 2014 Proprietary and Confidential Insights (3 of 4): Optimal Price for Sides & Beverages MBC also helps understand the profitable sides & beverages at their optimal price points Price of fries can be increased to $1.75 from $1.5 as it would only lead to a drop of 3% in purchase Price of fries can be increased to $1.75 from $1.5 as it would only lead to a drop of 3% in purchase 0% 10% 20% 30% $1.0 $1.5 $2 $2.5 $3 $3.5 Price Curve for Drink 0% 10% 20% 30% $1.0 $1.25 $1.5 $1.75 $2 $2.5 Price Curve for Fries DemandDemand
  • 17. 17© Absolutdata 2014 Proprietary and Confidential Insights (4 of 4): New Product – A Substitute or Complement? MBC helps understand the cannibalization of a la carte items when prices are changed or new items added to the menu Pizza & Tacos are purchased by different consumer segments and do not cannibalize each other Optimized Price for Taco Launch $2.00 0% 10% 20% 30% $1.5 $1.75 $2 $2.5 $3 $3.5 Price Curve for Tacos Demand After $2 there is sudden decrease in the demand for Tacos and hence $2 is the optimal price point to introduce Tacos for maximum off take
  • 18. 18© Absolutdata 2014 Proprietary and Confidential Mr. Target hits the Jackpot – The New and Improved Menu MBC helped Mr. Target to decide his new and improved optimized menu to increase his company’s revenue shares COMBO MEALS Classic Combo $3.00 Cheese Burger Combo $3.50 Pizza Combo $4.00 SIGNATURE MAINS Basic Burger $1.50 Cheese Burger $1.50 Pizza $3.0 Tacos $2.0 SIDES & BEVERAGES Fries $1.75 Drink $1.50 Note: Addition of Tacos at $2; Classic Combo, Fries & Drink price increased; Pizza price decreased
  • 19. 19© Absolutdata 2014 Proprietary and Confidential Mr. Target wins the Market 9% 5% 4% Ticket Size Guest Count1 2 Increase in total revenue The results yielded a 9% revenue growth from both existing and new consumers
  • 20. 20© Absolutdata 2014 Proprietary and Confidential Industry Application of Menu Based Conjoint Industry Applications of MBC Software as a Service (SaaS) Different packages with certain features Automobile Industry ‘Build Your Own’ Car Pharma – Drug Therapy Combination of drugs for prescription Financial Sector Multiple services that can be add-ons Shared Resources & Outsourcing IT Bundling services from different vendors
  • 21. 21© Absolutdata 2014 Proprietary and Confidential Conclusion – A Short Summary MBC gives more power to consumers by allowing consumers to select one to multiple options from a menu to indicate their preference. It is most useful in in markets where customers have freedom to customize an existing product or build their own package. It can help answer the following business questions:  Understanding trade-offs between pre-configured bundles versus single features (à la carte options)  Identify the right bundle of products to offer  Price the bundle and individual products optimally  Identify substitutes vs. compliments from the menu  Does reducing the price for an item cause a different item on the menu to be chosen more likely (or even less likely)?  Enables to maximize configurations for revenue and uptake
  • 22. 22© Absolutdata 2014 Proprietary and Confidential For more information visit www.absolutdata.com For queries, please write to info@absolutdata.com