Statistical Discovery for Consumer and Marketing Research

Copyright © 2013, SAS Insti tute Inc. Al l r ights reserved.

STATISTICAL DISCOVERY IN

CONSUMER AND MARKET RESEARCH

08 JULY 2014 | SHANGRI-LA HOTEL AT THE SHARD, LONDON


WELCOME TO THE SHARD


WHO’S HERE? FROM JMP

Bernard

Julie Malcolm

Luke


APPLICATIONS MAKE BETTER DECISIONS, FASTER WITH JMP


TODAY’S AIMS WE WILL SHOW YOU HOW YOU CAN

• Get deep insight into your consumer and market research data

• Marriage of advanced analytics allied with compelling visuals

• Get more from your current environment

• JMP is simple to install and easy to use

• Build better models

• Do scenario analysis with clients and execs

• Ultimately, make better marketing decisions faster


AGENDA

Time Topic Presenter

09:40Introduction: Statistical Discovery in Consumer and

Market ResearchIan Cox

10:10Case Study: Using Visualisation to Inform the

Analysis of Large Survey DataRobert Anderson

10:50Case Study: Predicting Behaviour from

Ethnographic and Usage DataIan Cox

11:20 Break

11:50Case Study: Linking Sensory and Taste Panel Data

to Make Better ProductsIan Cox

12:20Case Study: Targeting Offers More Effectively Using

Uplift ModelingRobert Anderson

12:50 Conclusion Bernard McKeown

13:00 Lunch


TODAY’S

PRESENTERS

Robert AndersonIan Cox


AGENDA








11:20 Break






13:00 Lunch


HELP US TO HELP YOU . . .


(Select all that apply).

1. Excel files

2. Text files

3. Databases

4. Enter data yourself

5. Other

WHERE DOES YOUR DATA COME FROM?QUESTION 1


(Select one).

1. <100

2. 101 to 1,000

3. 1001 to 10,000

4. 10,001 to 100,000

5. >100,000

HOW MANY ROWS ARE TYPICALLY IN YOUR DATA SETS?QUESTION 2


HOW MANY COLUMNS ARE TYPICALLY IN YOUR DATA SETS?

(Select one).

1. <10

2. 11 to 20

3. 21 to 50

4. 51 to 100

5. >100

QUESTION 3


HOW DO YOU ANALYSE OR MAKE SENSE OF YOUR DATA?

(Select all that apply).

1. Tabular summaries

2. Graphs

3. Statistical methods

4. Data mining or predictive modelling

5. Statistically designed experiments

6. Quality or reliability methods

QUESTION 4


WHAT PROPORTION OF YOUR TOTAL ANALYSIS TIME IS TYPICALLY

SPENT ACCESSING AND PREPARING DATA FOR ANALYSIS?

(Select one).

1. <20%

2. 20% to 40%

3. 41% to 60%

4. 61% to 80%

5. >80%

QUESTION 5


STATISTICAL DISCOVERY IN CONSUMER

AND MARKET RESEARCH


A CHANGING

LANDSCAPE . . .. . . WITH SOME ENDURING THEMES

• Marketing is complex and driven by rapidly evolving digital technologies.

• Yet core business issues endure: finding the most profitable growth

opportunities, developing the best products and services, taking the best

marketing action, and maximizing cross-business impact.

• In addition to a constant focus on the customer — current or potential — one

of the imperatives is to be data-driven.

• Data is ubiquitous in all aspects of finding consumers and making them

happy, from introducing new products or services, to positioning, branding,

advertising, segmentation and promotion.

• Although the digital revolution offers the promise to positively change the

dynamic with consumers, this opportunity will be realized only if you can

successfully leverage new data to better understand what specific groups of

consumers really want and how you can best meet, or even shape, their

needs.


BROAD AREAS IN

WHICH DATA ARISE

Descriptive

ResearchUsually builds on prior

exploration to describe

markets, segments,

competitors and

consumers. It’s also used to

measure performance

within an agreed

framework, usually on an

ongoing basis

Exploratory

ResearchIll-defined problems and

opportunities relating to

consumers are usually

clarified and refined using a

combination of interviews,

focus groups and

observational and

ethnographic studies.

Causal

ResearchEstablishing cause requires

an explanatory theory, a

statistical relationship,

correct time ordering, and

adequate control of any

other Xs considered as

extraneous.

Sensory

StudiesAim to understand how our

human senses will

contribute to the overall

experience of consuming or

using a product.

Predicting

BehaviourY's are predicted from X's

using observational data,

usually already available.

While falling short of

establishing causality,

predictions of future

consumer behavior, if they

are trustworthy, can still be

incredibly valuable.


A PICTURE FOR

DEPENDENCE

STUDIES

System of InterestCauses We Understand

X1

X2

X3

Causes We Don’t Understand, Know About, or Care About

X4 X5 X6

Measured Effects or Outcomes of

Interest

Y1

Y2

Y1 = Signal Function1(X1, X2, X3) + Nuisance Function1(X4, X5, X6)

Y2 = Signal Function2(X1, X2, X3) + Nuisance Function2(X4, X5, X6)

The ‘Nuisance Functions’ or ‘Noise Functions’ are give rise to the Variation in the

outcomes of interest.


THE FUNDAMENTAL

CHALLENGE OF

WORKING WITH

DATA

THE PROBLEM OF INDUCTION

Given a body of data that has been collected, make a useful separation into

Signal and Noise.

. . . Or

. . . Or


FUNCTIONAL

ASPECTS OF

WORKING WITH

DATA . . .

Data Access

Data

Management

Analysis

Reporting

User

Inte

rface

Particularly in Marketing

applications, in which

users tend not to be

(and should not be?)

“statistical experts”, the

User Interface is very

important


BUT WAIT!THE WORLD IS FULL OF SOFTWARE – WHAT’S SPECIAL

ABOUT JMP?

Confirmatory Data Analysis

(CDA)

“Hypothesis Testing”

Exploratory Data Analysis

(EDA)

“Hypothesis Generation”


1. Data visualization, done properly, is very powerful and effective.

2. Statistical analysis, done properly (and defined broadly to include things

like experimental design and predictive modeling) is also very powerful

and effective, but in a different way.

3. Tightly integrating the two creates a synergy that is much more

powerful and effective than either one alone.

STATISTICAL

DISCOVERY


JMP . . .

• Is a SAS product (dating from 1989) with hundreds of man-years of development.

• Provides ‘Statistical Discovery’ on the desktop using an in-memory architecture.

• Can act as a client to SAS.

• Can interoperate with other software.

• Makes it easy to build ‘applications’ with the JMP look and feel.

• Easily deploys such applications via ‘add-ins’.


AGENDA








11:20 Break






13:00 Lunch


BREAK


AGENDA








11:20 Break






13:00 Lunch


APPLICATIONS MAKE BETTER DECISIONS, FASTER WITH JMP


TODAY’S AIMS WE HAVE SHOWN YOU HOW YOU CAN

• Get deep insight into your consumer and market research data

• Marriage of advanced analytics allied with compelling visuals

• Get more from your current environment

• JMP is simple to install and easy to use

• Build better models

• Do scenario analysis with clients and execs

• Ultimately, make better marketing decisions faster


YOUR CHANCE WHAT ARE YOU GOING TO DO NEXT?

Discussion with our technical expert

• Let us know using the “Comments” box on your feedback form

• Invite your managers and colleagues

• Discuss consumer and market research challenges

Show your interest by filling in request

On-Demand Webcasts on Statistical Discovery for Market Research:

• http://www.jmp.com/uk/about/events/ondemand/

Register on our website

http://www.jmp.com/uk/about/events/ondemand/

Statistical Discovery for Consumer and Marketing Research

Business

Transcript of Statistical Discovery for Consumer and Marketing Research