SlideShare a Scribd company logo
Copyright © 2013, SAS Institute Inc. All rights reserved.
STATISTICAL DISCOVERY IN
CONSUMER AND MARKET RESEARCH
08 JULY 2014 | SHANGRI-LA HOTEL AT THE SHARD, LONDON
Copyright © 2013, SAS Institute Inc. All rights reserved.
WELCOME TO THE SHARD
Copyright © 2013, SAS Institute Inc. All rights reserved.
WHO’S HERE? FROM JMP
Bernard
Julie Malcolm
Luke
Copyright © 2013, SAS Institute Inc. All rights reserved.
APPLICATIONS MAKE BETTER DECISIONS, FASTER WITH JMP
Copyright © 2013, SAS Institute Inc. All rights reserved.
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
Copyright © 2013, SAS Institute Inc. All rights reserved.
AGENDA
Time Topic Presenter
09:40
Introduction: Statistical Discovery in Consumer and
Market Research
Ian Cox
10:10
Case Study: Using Visualisation to Inform the
Analysis of Large Survey Data
Robert Anderson
10:50
Case Study: Predicting Behaviour from
Ethnographic and Usage Data
Ian Cox
11:20 Break
11:50
Case Study: Linking Sensory and Taste Panel Data
to Make Better Products
Ian Cox
12:20
Case Study: Targeting Offers More Effectively Using
Uplift Modeling
Robert Anderson
12:50 Conclusion Bernard McKeown
13:00 Lunch
Copyright © 2013, SAS Institute Inc. All rights reserved.
TODAY’S
PRESENTERS
Robert AndersonIan Cox
Copyright © 2013, SAS Institute Inc. All rights reserved.
AGENDA
Time Topic Presenter
09:40
Introduction: Statistical Discovery in Consumer and
Market Research
Ian Cox
10:10
Case Study: Using Visualisation to Inform the
Analysis of Large Survey Data
Robert Anderson
10:50
Case Study: Predicting Behaviour from
Ethnographic and Usage Data
Ian Cox
11:20 Break
11:50
Case Study: Linking Sensory and Taste Panel Data
to Make Better Products
Ian Cox
12:20
Case Study: Targeting Offers More Effectively Using
Uplift Modeling
Robert Anderson
12:50 Conclusion Bernard McKeown
13:00 Lunch
Copyright © 2013, SAS Institute Inc. All rights reserved.
HELP US TO HELP YOU . . .
Copyright © 2013, SAS Institute Inc. All rights reserved.
(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
Copyright © 2013, SAS Institute Inc. All rights reserved.
(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
Copyright © 2013, SAS Institute Inc. All rights reserved.
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
Copyright © 2013, SAS Institute Inc. All rights reserved.
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
Copyright © 2013, SAS Institute Inc. All rights reserved.
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
Copyright © 2013, SAS Institute Inc. All rights reserved.
STATISTICAL DISCOVERY IN CONSUMER
AND MARKET RESEARCH
Copyright © 2013, SAS Institute Inc. All rights reserved.
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.
Copyright © 2013, SAS Institute Inc. All rights reserved.
BROAD AREAS IN
WHICH DATA ARISE
Descriptive
Research
Usually 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
Research
Ill-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
Research
Establishing cause requires
an explanatory theory, a
statistical relationship,
correct time ordering, and
adequate control of any
other Xs considered as
extraneous.
Sensory
Studies
Aim to understand how our
human senses will
contribute to the overall
experience of consuming or
using a product.
Predicting
Behaviour
Y'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.
Copyright © 2013, SAS Institute Inc. All rights reserved.
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.
Copyright © 2013, SAS Institute Inc. All rights reserved.
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
Copyright © 2013, SAS Institute Inc. All rights reserved.
FUNCTIONAL
ASPECTS OF
WORKING WITH
DATA . . .
Data Access
Data
Management
Analysis
Reporting
UserInterface
Particularly in Marketing
applications, in which
users tend not to be
(and should not be?)
“statistical experts”, the
User Interface is very
important
Copyright © 2013, SAS Institute Inc. All rights reserved.
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”
Copyright © 2013, SAS Institute Inc. All rights reserved.
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
Copyright © 2013, SAS Institute Inc. All rights reserved.
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’.
Copyright © 2013, SAS Institute Inc. All rights reserved.
AGENDA
Time Topic Presenter
09:40
Introduction: Statistical Discovery in Consumer and
Market Research
Ian Cox
10:10
Case Study: Using Visualisation to Inform the
Analysis of Large Survey Data
Robert Anderson
10:50
Case Study: Predicting Behaviour from
Ethnographic and Usage Data
Ian Cox
11:20 Break
11:50
Case Study: Linking Sensory and Taste Panel Data
to Make Better Products
Ian Cox
12:20
Case Study: Targeting Offers More Effectively Using
Uplift Modeling
Robert Anderson
12:50 Conclusion Bernard McKeown
13:00 Lunch
Copyright © 2013, SAS Institute Inc. All rights reserved.
BREAK
Copyright © 2013, SAS Institute Inc. All rights reserved.
AGENDA
Time Topic Presenter
09:40
Introduction: Statistical Discovery in Consumer and
Market Research
Ian Cox
10:10
Case Study: Using Visualisation to Inform the
Analysis of Large Survey Data
Robert Anderson
10:50
Case Study: Predicting Behaviour from
Ethnographic and Usage Data
Ian Cox
11:20 Break
11:50
Case Study: Linking Sensory and Taste Panel Data
to Make Better Products
Ian Cox
12:20
Case Study: Targeting Offers More Effectively Using
Uplift Modeling
Robert Anderson
12:50 Conclusion Bernard McKeown
13:00 Lunch
Copyright © 2013, SAS Institute Inc. All rights reserved.
APPLICATIONS MAKE BETTER DECISIONS, FASTER WITH JMP
Copyright © 2013, SAS Institute Inc. All rights reserved.
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
Copyright © 2013, SAS Institute Inc. All rights reserved.
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
Copyright © 2013, SAS Institute Inc. All rights reserved. www.SAS.com

More Related Content

What's hot

On the Measurement of Test Collection Reliability
On the Measurement of Test Collection ReliabilityOn the Measurement of Test Collection Reliability
On the Measurement of Test Collection Reliability
Julián Urbano
 
Introduction to regression
Introduction to regressionIntroduction to regression
Introduction to regression
Dr. C.V. Suresh Babu
 
Machine Learning and Multi Drug Resistant(MDR) Infections case study
Machine Learning and Multi Drug Resistant(MDR) Infections case studyMachine Learning and Multi Drug Resistant(MDR) Infections case study
Machine Learning and Multi Drug Resistant(MDR) Infections case study
AlgoAnalytics Financial Consultancy Pvt. Ltd.
 
Fish Bone
Fish BoneFish Bone
Fish Bone
Nishant Narendra
 
Exploratory data analysis data visualization
Exploratory data analysis data visualizationExploratory data analysis data visualization
Exploratory data analysis data visualization
Dr. Hamdan Al-Sabri
 
1555 track 2 ning_using our laptop
1555 track 2 ning_using our laptop1555 track 2 ning_using our laptop
1555 track 2 ning_using our laptop
Rising Media, Inc.
 
Causal Inference, Reinforcement Learning, and Continuous Optimization
Causal Inference, Reinforcement Learning, and Continuous OptimizationCausal Inference, Reinforcement Learning, and Continuous Optimization
Causal Inference, Reinforcement Learning, and Continuous Optimization
ScientificRevenue
 
Machine Learning For Stock Broking
Machine Learning For Stock BrokingMachine Learning For Stock Broking
Machine Learning For Stock Broking
AlgoAnalytics Financial Consultancy Pvt. Ltd.
 
MLPA for health care presentation smc
MLPA for health care presentation   smcMLPA for health care presentation   smc
MLPA for health care presentation smc
Shaun Comfort
 
1030 track 2 barrett_using our laptop
1030 track 2 barrett_using our laptop1030 track 2 barrett_using our laptop
1030 track 2 barrett_using our laptop
Rising Media, Inc.
 
Lecture 5.Riddles of the p value, CI and alpha values
Lecture 5.Riddles of the p value, CI and alpha valuesLecture 5.Riddles of the p value, CI and alpha values
Lecture 5.Riddles of the p value, CI and alpha values
Dr Rajeev Kumar
 
Random Forest Tutorial | Random Forest in R | Machine Learning | Data Science...
Random Forest Tutorial | Random Forest in R | Machine Learning | Data Science...Random Forest Tutorial | Random Forest in R | Machine Learning | Data Science...
Random Forest Tutorial | Random Forest in R | Machine Learning | Data Science...
Edureka!
 
Text Analytics for Legal work
Text Analytics for Legal workText Analytics for Legal work
Text Analytics for Legal work
AlgoAnalytics Financial Consultancy Pvt. Ltd.
 
Chapter Two
Chapter TwoChapter Two
Chapter Two
bhenthorn
 
Root Cause Analysis
Root Cause AnalysisRoot Cause Analysis
Root Cause Analysis
tqmdoctor
 
Fishbone and 5 Why webinar 02 11-21
Fishbone and 5 Why webinar 02 11-21Fishbone and 5 Why webinar 02 11-21
Fishbone and 5 Why webinar 02 11-21
Darren Dolcemascolo
 
Hypothesis Testing: Central Tendency – Normal (Compare 1:Standard)
Hypothesis Testing: Central Tendency – Normal (Compare 1:Standard)Hypothesis Testing: Central Tendency – Normal (Compare 1:Standard)
Hypothesis Testing: Central Tendency – Normal (Compare 1:Standard)
Matt Hansen
 
Image Analytics for Retail
Image Analytics for RetailImage Analytics for Retail
Visual and Functional Best Practices in Data Visualisation by Kurt Buhler (Or...
Visual and Functional Best Practices in Data Visualisation by Kurt Buhler (Or...Visual and Functional Best Practices in Data Visualisation by Kurt Buhler (Or...
Visual and Functional Best Practices in Data Visualisation by Kurt Buhler (Or...
Patrick Van Renterghem
 
Image Analytics In Healthcare
Image Analytics In HealthcareImage Analytics In Healthcare
Image Analytics In Healthcare
AlgoAnalytics Financial Consultancy Pvt. Ltd.
 

What's hot (20)

On the Measurement of Test Collection Reliability
On the Measurement of Test Collection ReliabilityOn the Measurement of Test Collection Reliability
On the Measurement of Test Collection Reliability
 
Introduction to regression
Introduction to regressionIntroduction to regression
Introduction to regression
 
Machine Learning and Multi Drug Resistant(MDR) Infections case study
Machine Learning and Multi Drug Resistant(MDR) Infections case studyMachine Learning and Multi Drug Resistant(MDR) Infections case study
Machine Learning and Multi Drug Resistant(MDR) Infections case study
 
Fish Bone
Fish BoneFish Bone
Fish Bone
 
Exploratory data analysis data visualization
Exploratory data analysis data visualizationExploratory data analysis data visualization
Exploratory data analysis data visualization
 
1555 track 2 ning_using our laptop
1555 track 2 ning_using our laptop1555 track 2 ning_using our laptop
1555 track 2 ning_using our laptop
 
Causal Inference, Reinforcement Learning, and Continuous Optimization
Causal Inference, Reinforcement Learning, and Continuous OptimizationCausal Inference, Reinforcement Learning, and Continuous Optimization
Causal Inference, Reinforcement Learning, and Continuous Optimization
 
Machine Learning For Stock Broking
Machine Learning For Stock BrokingMachine Learning For Stock Broking
Machine Learning For Stock Broking
 
MLPA for health care presentation smc
MLPA for health care presentation   smcMLPA for health care presentation   smc
MLPA for health care presentation smc
 
1030 track 2 barrett_using our laptop
1030 track 2 barrett_using our laptop1030 track 2 barrett_using our laptop
1030 track 2 barrett_using our laptop
 
Lecture 5.Riddles of the p value, CI and alpha values
Lecture 5.Riddles of the p value, CI and alpha valuesLecture 5.Riddles of the p value, CI and alpha values
Lecture 5.Riddles of the p value, CI and alpha values
 
Random Forest Tutorial | Random Forest in R | Machine Learning | Data Science...
Random Forest Tutorial | Random Forest in R | Machine Learning | Data Science...Random Forest Tutorial | Random Forest in R | Machine Learning | Data Science...
Random Forest Tutorial | Random Forest in R | Machine Learning | Data Science...
 
Text Analytics for Legal work
Text Analytics for Legal workText Analytics for Legal work
Text Analytics for Legal work
 
Chapter Two
Chapter TwoChapter Two
Chapter Two
 
Root Cause Analysis
Root Cause AnalysisRoot Cause Analysis
Root Cause Analysis
 
Fishbone and 5 Why webinar 02 11-21
Fishbone and 5 Why webinar 02 11-21Fishbone and 5 Why webinar 02 11-21
Fishbone and 5 Why webinar 02 11-21
 
Hypothesis Testing: Central Tendency – Normal (Compare 1:Standard)
Hypothesis Testing: Central Tendency – Normal (Compare 1:Standard)Hypothesis Testing: Central Tendency – Normal (Compare 1:Standard)
Hypothesis Testing: Central Tendency – Normal (Compare 1:Standard)
 
Image Analytics for Retail
Image Analytics for RetailImage Analytics for Retail
Image Analytics for Retail
 
Visual and Functional Best Practices in Data Visualisation by Kurt Buhler (Or...
Visual and Functional Best Practices in Data Visualisation by Kurt Buhler (Or...Visual and Functional Best Practices in Data Visualisation by Kurt Buhler (Or...
Visual and Functional Best Practices in Data Visualisation by Kurt Buhler (Or...
 
Image Analytics In Healthcare
Image Analytics In HealthcareImage Analytics In Healthcare
Image Analytics In Healthcare
 

Viewers also liked

Perk acties a6
Perk acties a6Perk acties a6
Perk acties a6
Jaap Kemp
 
Photobooooooooth
PhotoboooooooothPhotobooooooooth
Photobooooooooth
nadim1020
 
Webquest on output_devices[1]
Webquest on output_devices[1]Webquest on output_devices[1]
Webquest on output_devices[1]
edtechfacey
 
Advanced Use Cases of the Bootstrap Method in JMP Pro
Advanced Use Cases of the Bootstrap Method in JMP ProAdvanced Use Cases of the Bootstrap Method in JMP Pro
Advanced Use Cases of the Bootstrap Method in JMP Pro
JMP software from SAS
 
Localization 140704162405-phpapp02
Localization 140704162405-phpapp02Localization 140704162405-phpapp02
Localization 140704162405-phpapp02
Raiyad Raad
 
Jeopardy (output devices)
Jeopardy (output devices)Jeopardy (output devices)
Jeopardy (output devices)
edtechfacey
 
Perk laskrant
Perk laskrantPerk laskrant
Perk laskrant
Jaap Kemp
 
Vicios del lenguaje
Vicios del lenguajeVicios del lenguaje
Vicios del lenguaje
blft123
 
Cld 495 final
Cld 495 final Cld 495 final
Cld 495 final
Chandler Shepherd
 
Tips mengadakan majlis perkahwinan ros
Tips mengadakan majlis perkahwinan rosTips mengadakan majlis perkahwinan ros
Tips mengadakan majlis perkahwinan rosRose Katering
 
Washington presentation 3.1
Washington presentation 3.1Washington presentation 3.1
Washington presentation 3.1
jbuyonje
 
впн в россии
впн в россиивпн в россии
впн в россии19nature
 
Localization with Mozilla
Localization with MozillaLocalization with Mozilla
Localization with Mozilla
Raiyad Raad
 
কীভাবে হালনাগাদকৃত কেবি লোকালাইজ করবেন
কীভাবে হালনাগাদকৃত কেবি লোকালাইজ করবেনকীভাবে হালনাগাদকৃত কেবি লোকালাইজ করবেন
কীভাবে হালনাগাদকৃত কেবি লোকালাইজ করবেন
Raiyad Raad
 
Angloingles
AngloinglesAngloingles
Angloingles
blft123
 
Building Models for Complex Design of Experiments
Building Models for Complex Design of ExperimentsBuilding Models for Complex Design of Experiments
Building Models for Complex Design of Experiments
JMP software from SAS
 
Exploring Variable Clustering and Importance in JMP
Exploring Variable Clustering and Importance in JMPExploring Variable Clustering and Importance in JMP
Exploring Variable Clustering and Importance in JMP
JMP software from SAS
 
Washington, d.c. presentation
Washington, d.c. presentationWashington, d.c. presentation
Washington, d.c. presentation
jbuyonje
 
Correcting Misconceptions About Optimal Design
Correcting Misconceptions About Optimal DesignCorrecting Misconceptions About Optimal Design
Correcting Misconceptions About Optimal Design
JMP software from SAS
 

Viewers also liked (20)

IKT előadás
IKT előadásIKT előadás
IKT előadás
 
Perk acties a6
Perk acties a6Perk acties a6
Perk acties a6
 
Photobooooooooth
PhotoboooooooothPhotobooooooooth
Photobooooooooth
 
Webquest on output_devices[1]
Webquest on output_devices[1]Webquest on output_devices[1]
Webquest on output_devices[1]
 
Advanced Use Cases of the Bootstrap Method in JMP Pro
Advanced Use Cases of the Bootstrap Method in JMP ProAdvanced Use Cases of the Bootstrap Method in JMP Pro
Advanced Use Cases of the Bootstrap Method in JMP Pro
 
Localization 140704162405-phpapp02
Localization 140704162405-phpapp02Localization 140704162405-phpapp02
Localization 140704162405-phpapp02
 
Jeopardy (output devices)
Jeopardy (output devices)Jeopardy (output devices)
Jeopardy (output devices)
 
Perk laskrant
Perk laskrantPerk laskrant
Perk laskrant
 
Vicios del lenguaje
Vicios del lenguajeVicios del lenguaje
Vicios del lenguaje
 
Cld 495 final
Cld 495 final Cld 495 final
Cld 495 final
 
Tips mengadakan majlis perkahwinan ros
Tips mengadakan majlis perkahwinan rosTips mengadakan majlis perkahwinan ros
Tips mengadakan majlis perkahwinan ros
 
Washington presentation 3.1
Washington presentation 3.1Washington presentation 3.1
Washington presentation 3.1
 
впн в россии
впн в россиивпн в россии
впн в россии
 
Localization with Mozilla
Localization with MozillaLocalization with Mozilla
Localization with Mozilla
 
কীভাবে হালনাগাদকৃত কেবি লোকালাইজ করবেন
কীভাবে হালনাগাদকৃত কেবি লোকালাইজ করবেনকীভাবে হালনাগাদকৃত কেবি লোকালাইজ করবেন
কীভাবে হালনাগাদকৃত কেবি লোকালাইজ করবেন
 
Angloingles
AngloinglesAngloingles
Angloingles
 
Building Models for Complex Design of Experiments
Building Models for Complex Design of ExperimentsBuilding Models for Complex Design of Experiments
Building Models for Complex Design of Experiments
 
Exploring Variable Clustering and Importance in JMP
Exploring Variable Clustering and Importance in JMPExploring Variable Clustering and Importance in JMP
Exploring Variable Clustering and Importance in JMP
 
Washington, d.c. presentation
Washington, d.c. presentationWashington, d.c. presentation
Washington, d.c. presentation
 
Correcting Misconceptions About Optimal Design
Correcting Misconceptions About Optimal DesignCorrecting Misconceptions About Optimal Design
Correcting Misconceptions About Optimal Design
 

Similar to Statistical Discovery for Consumer and Marketing Research

What is the Value of SAS Analytics?
What is the Value of SAS Analytics?What is the Value of SAS Analytics?
What is the Value of SAS Analytics?
SAS Canada
 
Leveraging Your Data Report
Leveraging Your Data ReportLeveraging Your Data Report
Leveraging Your Data Report
NAED_Org
 
Big Data Analytics in Government
Big Data Analytics in GovernmentBig Data Analytics in Government
Big Data Analytics in Government
Deepak Ramanathan
 
High Performance Analytics - The Future of Analytics is Here
High Performance Analytics - The Future of Analytics is HereHigh Performance Analytics - The Future of Analytics is Here
High Performance Analytics - The Future of Analytics is Here
SAS Institute India Pvt. Ltd
 
SAS an open ecosystem for Artifical Intelligence - Dean Zouari
SAS an open ecosystem for Artifical Intelligence - Dean ZouariSAS an open ecosystem for Artifical Intelligence - Dean Zouari
SAS an open ecosystem for Artifical Intelligence - Dean Zouari
Institute of Contemporary Sciences
 
SAS Visual Analytics Overview
SAS Visual Analytics OverviewSAS Visual Analytics Overview
SAS Visual Analytics Overview
SAS Institute India Pvt. Ltd
 
Business Partner Product Enablement Roadmap, IBM Predictive Analytics
Business Partner Product Enablement Roadmap, IBM Predictive AnalyticsBusiness Partner Product Enablement Roadmap, IBM Predictive Analytics
Business Partner Product Enablement Roadmap, IBM Predictive Analytics
Arrow ECS UK
 
Embracing data science
Embracing data scienceEmbracing data science
Embracing data science
Vipul Kalamkar
 
Better Living Through Analytics - Strategies for Data Decisions
Better Living Through Analytics - Strategies for Data DecisionsBetter Living Through Analytics - Strategies for Data Decisions
Better Living Through Analytics - Strategies for Data Decisions
Product School
 
Big Data Analytics in light of Financial Industry
Big Data Analytics in light of Financial Industry Big Data Analytics in light of Financial Industry
Big Data Analytics in light of Financial Industry
Capgemini
 
Big Data Analytics: Challenge or Opportunity?
Big Data Analytics: Challenge or Opportunity?Big Data Analytics: Challenge or Opportunity?
Big Data Analytics: Challenge or Opportunity?
NUS-ISS
 
1 kwyfvb
1 kwyfvb1 kwyfvb
ForresterPredictiveWave
ForresterPredictiveWaveForresterPredictiveWave
ForresterPredictiveWave
Timothy M. Caffrey, MBA
 
Deliver World Class Customer Experience with Big Data and Analytics
Deliver World Class Customer Experience with Big Data and AnalyticsDeliver World Class Customer Experience with Big Data and Analytics
Deliver World Class Customer Experience with Big Data and Analytics
Raul Goycoolea Seoane
 
The Zen of DataOps – AWS Lake Formation and the Data Supply Chain Pipeline
The Zen of DataOps – AWS Lake Formation and the Data Supply Chain PipelineThe Zen of DataOps – AWS Lake Formation and the Data Supply Chain Pipeline
The Zen of DataOps – AWS Lake Formation and the Data Supply Chain Pipeline
Amazon Web Services
 
Delivering Value Through Business Analytics
Delivering Value Through Business AnalyticsDelivering Value Through Business Analytics
Delivering Value Through Business Analytics
Social Media Today
 
Sgcp14dunlea
Sgcp14dunleaSgcp14dunlea
Sgcp14dunlea
Justin Hayward
 
High performance analytics customer stories
High performance analytics   customer storiesHigh performance analytics   customer stories
High performance analytics customer stories
Sarabjeet Singh
 
AWS Summit Webinar Edition | Modern Data Architecture | Microsoft Application...
AWS Summit Webinar Edition | Modern Data Architecture | Microsoft Application...AWS Summit Webinar Edition | Modern Data Architecture | Microsoft Application...
AWS Summit Webinar Edition | Modern Data Architecture | Microsoft Application...
Amazon Web Services
 
Business Visualization: Dashboard & Storyboarding
Business Visualization: Dashboard & StoryboardingBusiness Visualization: Dashboard & Storyboarding
Business Visualization: Dashboard & Storyboarding
NMIMS Global Access School of Continuing Education (NGA-SCE)
 

Similar to Statistical Discovery for Consumer and Marketing Research (20)

What is the Value of SAS Analytics?
What is the Value of SAS Analytics?What is the Value of SAS Analytics?
What is the Value of SAS Analytics?
 
Leveraging Your Data Report
Leveraging Your Data ReportLeveraging Your Data Report
Leveraging Your Data Report
 
Big Data Analytics in Government
Big Data Analytics in GovernmentBig Data Analytics in Government
Big Data Analytics in Government
 
High Performance Analytics - The Future of Analytics is Here
High Performance Analytics - The Future of Analytics is HereHigh Performance Analytics - The Future of Analytics is Here
High Performance Analytics - The Future of Analytics is Here
 
SAS an open ecosystem for Artifical Intelligence - Dean Zouari
SAS an open ecosystem for Artifical Intelligence - Dean ZouariSAS an open ecosystem for Artifical Intelligence - Dean Zouari
SAS an open ecosystem for Artifical Intelligence - Dean Zouari
 
SAS Visual Analytics Overview
SAS Visual Analytics OverviewSAS Visual Analytics Overview
SAS Visual Analytics Overview
 
Business Partner Product Enablement Roadmap, IBM Predictive Analytics
Business Partner Product Enablement Roadmap, IBM Predictive AnalyticsBusiness Partner Product Enablement Roadmap, IBM Predictive Analytics
Business Partner Product Enablement Roadmap, IBM Predictive Analytics
 
Embracing data science
Embracing data scienceEmbracing data science
Embracing data science
 
Better Living Through Analytics - Strategies for Data Decisions
Better Living Through Analytics - Strategies for Data DecisionsBetter Living Through Analytics - Strategies for Data Decisions
Better Living Through Analytics - Strategies for Data Decisions
 
Big Data Analytics in light of Financial Industry
Big Data Analytics in light of Financial Industry Big Data Analytics in light of Financial Industry
Big Data Analytics in light of Financial Industry
 
Big Data Analytics: Challenge or Opportunity?
Big Data Analytics: Challenge or Opportunity?Big Data Analytics: Challenge or Opportunity?
Big Data Analytics: Challenge or Opportunity?
 
1 kwyfvb
1 kwyfvb1 kwyfvb
1 kwyfvb
 
ForresterPredictiveWave
ForresterPredictiveWaveForresterPredictiveWave
ForresterPredictiveWave
 
Deliver World Class Customer Experience with Big Data and Analytics
Deliver World Class Customer Experience with Big Data and AnalyticsDeliver World Class Customer Experience with Big Data and Analytics
Deliver World Class Customer Experience with Big Data and Analytics
 
The Zen of DataOps – AWS Lake Formation and the Data Supply Chain Pipeline
The Zen of DataOps – AWS Lake Formation and the Data Supply Chain PipelineThe Zen of DataOps – AWS Lake Formation and the Data Supply Chain Pipeline
The Zen of DataOps – AWS Lake Formation and the Data Supply Chain Pipeline
 
Delivering Value Through Business Analytics
Delivering Value Through Business AnalyticsDelivering Value Through Business Analytics
Delivering Value Through Business Analytics
 
Sgcp14dunlea
Sgcp14dunleaSgcp14dunlea
Sgcp14dunlea
 
High performance analytics customer stories
High performance analytics   customer storiesHigh performance analytics   customer stories
High performance analytics customer stories
 
AWS Summit Webinar Edition | Modern Data Architecture | Microsoft Application...
AWS Summit Webinar Edition | Modern Data Architecture | Microsoft Application...AWS Summit Webinar Edition | Modern Data Architecture | Microsoft Application...
AWS Summit Webinar Edition | Modern Data Architecture | Microsoft Application...
 
Business Visualization: Dashboard & Storyboarding
Business Visualization: Dashboard & StoryboardingBusiness Visualization: Dashboard & Storyboarding
Business Visualization: Dashboard & Storyboarding
 

More from JMP software from SAS

The Straight Way to a Final Result: Mixture Design of Experiments
The Straight Way to a Final Result: Mixture Design of ExperimentsThe Straight Way to a Final Result: Mixture Design of Experiments
The Straight Way to a Final Result: Mixture Design of Experiments
JMP software from SAS
 
Grafische Analyse Ihrer Excel Daten
Grafische Analyse  Ihrer Excel DatenGrafische Analyse  Ihrer Excel Daten
Grafische Analyse Ihrer Excel Daten
JMP software from SAS
 
Building Better Models
Building Better ModelsBuilding Better Models
Building Better Models
JMP software from SAS
 
JMP for Ethanol Producers
JMP for Ethanol ProducersJMP for Ethanol Producers
JMP for Ethanol Producers
JMP software from SAS
 
Exploring Best Practises in Design of Experiments: A Data Driven Approach to ...
Exploring Best Practises in Design of Experiments: A Data Driven Approach to ...Exploring Best Practises in Design of Experiments: A Data Driven Approach to ...
Exploring Best Practises in Design of Experiments: A Data Driven Approach to ...
JMP software from SAS
 
Exploring Best Practises in Design of Experiments
Exploring Best Practises in Design of ExperimentsExploring Best Practises in Design of Experiments
Exploring Best Practises in Design of Experiments
JMP software from SAS
 
Statistical and Predictive Modelling
Statistical and Predictive ModellingStatistical and Predictive Modelling
Statistical and Predictive Modelling
JMP software from SAS
 
Evaluating & Monitoring Your Process Using MSA & SPC
Evaluating & Monitoring Your Process Using MSA & SPCEvaluating & Monitoring Your Process Using MSA & SPC
Evaluating & Monitoring Your Process Using MSA & SPC
JMP software from SAS
 
Everything You Wanted to Know About Definitive Screening Designs
Everything You Wanted to Know About Definitive Screening DesignsEverything You Wanted to Know About Definitive Screening Designs
Everything You Wanted to Know About Definitive Screening Designs
JMP software from SAS
 
Basic Design of Experiments Using the Custom DOE Platform
Basic Design of Experiments Using the Custom DOE PlatformBasic Design of Experiments Using the Custom DOE Platform
Basic Design of Experiments Using the Custom DOE Platform
JMP software from SAS
 
Visual Analytic Approaches for the Analysis of Spontaneously Reported Adverse...
Visual Analytic Approaches for the Analysis of Spontaneously Reported Adverse...Visual Analytic Approaches for the Analysis of Spontaneously Reported Adverse...
Visual Analytic Approaches for the Analysis of Spontaneously Reported Adverse...
JMP software from SAS
 
Introduction to Modeling
Introduction to ModelingIntroduction to Modeling
Introduction to Modeling
JMP software from SAS
 
New Design of Experiments Features in JMP 11
New Design of Experiments Features in JMP 11New Design of Experiments Features in JMP 11
New Design of Experiments Features in JMP 11
JMP software from SAS
 
When a Linear Model Just Won't Do: Fitting Nonlinear Models in JMP
When a Linear Model Just Won't Do: Fitting Nonlinear Models in JMPWhen a Linear Model Just Won't Do: Fitting Nonlinear Models in JMP
When a Linear Model Just Won't Do: Fitting Nonlinear Models in JMP
JMP software from SAS
 
The Bootstrap and Beyond: Using JSL for Resampling
The Bootstrap and Beyond: Using JSL for ResamplingThe Bootstrap and Beyond: Using JSL for Resampling
The Bootstrap and Beyond: Using JSL for Resampling
JMP software from SAS
 

More from JMP software from SAS (15)

The Straight Way to a Final Result: Mixture Design of Experiments
The Straight Way to a Final Result: Mixture Design of ExperimentsThe Straight Way to a Final Result: Mixture Design of Experiments
The Straight Way to a Final Result: Mixture Design of Experiments
 
Grafische Analyse Ihrer Excel Daten
Grafische Analyse  Ihrer Excel DatenGrafische Analyse  Ihrer Excel Daten
Grafische Analyse Ihrer Excel Daten
 
Building Better Models
Building Better ModelsBuilding Better Models
Building Better Models
 
JMP for Ethanol Producers
JMP for Ethanol ProducersJMP for Ethanol Producers
JMP for Ethanol Producers
 
Exploring Best Practises in Design of Experiments: A Data Driven Approach to ...
Exploring Best Practises in Design of Experiments: A Data Driven Approach to ...Exploring Best Practises in Design of Experiments: A Data Driven Approach to ...
Exploring Best Practises in Design of Experiments: A Data Driven Approach to ...
 
Exploring Best Practises in Design of Experiments
Exploring Best Practises in Design of ExperimentsExploring Best Practises in Design of Experiments
Exploring Best Practises in Design of Experiments
 
Statistical and Predictive Modelling
Statistical and Predictive ModellingStatistical and Predictive Modelling
Statistical and Predictive Modelling
 
Evaluating & Monitoring Your Process Using MSA & SPC
Evaluating & Monitoring Your Process Using MSA & SPCEvaluating & Monitoring Your Process Using MSA & SPC
Evaluating & Monitoring Your Process Using MSA & SPC
 
Everything You Wanted to Know About Definitive Screening Designs
Everything You Wanted to Know About Definitive Screening DesignsEverything You Wanted to Know About Definitive Screening Designs
Everything You Wanted to Know About Definitive Screening Designs
 
Basic Design of Experiments Using the Custom DOE Platform
Basic Design of Experiments Using the Custom DOE PlatformBasic Design of Experiments Using the Custom DOE Platform
Basic Design of Experiments Using the Custom DOE Platform
 
Visual Analytic Approaches for the Analysis of Spontaneously Reported Adverse...
Visual Analytic Approaches for the Analysis of Spontaneously Reported Adverse...Visual Analytic Approaches for the Analysis of Spontaneously Reported Adverse...
Visual Analytic Approaches for the Analysis of Spontaneously Reported Adverse...
 
Introduction to Modeling
Introduction to ModelingIntroduction to Modeling
Introduction to Modeling
 
New Design of Experiments Features in JMP 11
New Design of Experiments Features in JMP 11New Design of Experiments Features in JMP 11
New Design of Experiments Features in JMP 11
 
When a Linear Model Just Won't Do: Fitting Nonlinear Models in JMP
When a Linear Model Just Won't Do: Fitting Nonlinear Models in JMPWhen a Linear Model Just Won't Do: Fitting Nonlinear Models in JMP
When a Linear Model Just Won't Do: Fitting Nonlinear Models in JMP
 
The Bootstrap and Beyond: Using JSL for Resampling
The Bootstrap and Beyond: Using JSL for ResamplingThe Bootstrap and Beyond: Using JSL for Resampling
The Bootstrap and Beyond: Using JSL for Resampling
 

Recently uploaded

Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
AnnySerafinaLove
 
Creative Web Design Company in Singapore
Creative Web Design Company in SingaporeCreative Web Design Company in Singapore
Creative Web Design Company in Singapore
techboxsqauremedia
 
Training my puppy and implementation in this story
Training my puppy and implementation in this storyTraining my puppy and implementation in this story
Training my puppy and implementation in this story
WilliamRodrigues148
 
Authentically Social Presented by Corey Perlman
Authentically Social Presented by Corey PerlmanAuthentically Social Presented by Corey Perlman
Authentically Social Presented by Corey Perlman
Corey Perlman, Social Media Speaker and Consultant
 
How MJ Global Leads the Packaging Industry.pdf
How MJ Global Leads the Packaging Industry.pdfHow MJ Global Leads the Packaging Industry.pdf
How MJ Global Leads the Packaging Industry.pdf
MJ Global
 
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta MatkaDpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
➒➌➎➏➑➐➋➑➐➐Dpboss Matka Guessing Satta Matka Kalyan Chart Indian Matka
 
amptalk_RecruitingDeck_english_2024.06.05
amptalk_RecruitingDeck_english_2024.06.05amptalk_RecruitingDeck_english_2024.06.05
amptalk_RecruitingDeck_english_2024.06.05
marketing317746
 
Industrial Tech SW: Category Renewal and Creation
Industrial Tech SW:  Category Renewal and CreationIndustrial Tech SW:  Category Renewal and Creation
Industrial Tech SW: Category Renewal and Creation
Christian Dahlen
 
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdfModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
fisherameliaisabella
 
The Influence of Marketing Strategy and Market Competition on Business Perfor...
The Influence of Marketing Strategy and Market Competition on Business Perfor...The Influence of Marketing Strategy and Market Competition on Business Perfor...
The Influence of Marketing Strategy and Market Competition on Business Perfor...
Adam Smith
 
Organizational Change Leadership Agile Tour Geneve 2024
Organizational Change Leadership Agile Tour Geneve 2024Organizational Change Leadership Agile Tour Geneve 2024
Organizational Change Leadership Agile Tour Geneve 2024
Kirill Klimov
 
Authentically Social by Corey Perlman - EO Puerto Rico
Authentically Social by Corey Perlman - EO Puerto RicoAuthentically Social by Corey Perlman - EO Puerto Rico
Authentically Social by Corey Perlman - EO Puerto Rico
Corey Perlman, Social Media Speaker and Consultant
 
Building Your Employer Brand with Social Media
Building Your Employer Brand with Social MediaBuilding Your Employer Brand with Social Media
Building Your Employer Brand with Social Media
LuanWise
 
3 Simple Steps To Buy Verified Payoneer Account In 2024
3 Simple Steps To Buy Verified Payoneer Account In 20243 Simple Steps To Buy Verified Payoneer Account In 2024
3 Simple Steps To Buy Verified Payoneer Account In 2024
SEOSMMEARTH
 
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
SOFTTECHHUB
 
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdf
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfThe 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdf
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdf
thesiliconleaders
 
Structural Design Process: Step-by-Step Guide for Buildings
Structural Design Process: Step-by-Step Guide for BuildingsStructural Design Process: Step-by-Step Guide for Buildings
Structural Design Process: Step-by-Step Guide for Buildings
Chandresh Chudasama
 
Best practices for project execution and delivery
Best practices for project execution and deliveryBest practices for project execution and delivery
Best practices for project execution and delivery
CLIVE MINCHIN
 
ikea_woodgreen_petscharity_dog-alogue_digital.pdf
ikea_woodgreen_petscharity_dog-alogue_digital.pdfikea_woodgreen_petscharity_dog-alogue_digital.pdf
ikea_woodgreen_petscharity_dog-alogue_digital.pdf
agatadrynko
 
Observation Lab PowerPoint Assignment for TEM 431
Observation Lab PowerPoint Assignment for TEM 431Observation Lab PowerPoint Assignment for TEM 431
Observation Lab PowerPoint Assignment for TEM 431
ecamare2
 

Recently uploaded (20)

Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
 
Creative Web Design Company in Singapore
Creative Web Design Company in SingaporeCreative Web Design Company in Singapore
Creative Web Design Company in Singapore
 
Training my puppy and implementation in this story
Training my puppy and implementation in this storyTraining my puppy and implementation in this story
Training my puppy and implementation in this story
 
Authentically Social Presented by Corey Perlman
Authentically Social Presented by Corey PerlmanAuthentically Social Presented by Corey Perlman
Authentically Social Presented by Corey Perlman
 
How MJ Global Leads the Packaging Industry.pdf
How MJ Global Leads the Packaging Industry.pdfHow MJ Global Leads the Packaging Industry.pdf
How MJ Global Leads the Packaging Industry.pdf
 
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta MatkaDpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
 
amptalk_RecruitingDeck_english_2024.06.05
amptalk_RecruitingDeck_english_2024.06.05amptalk_RecruitingDeck_english_2024.06.05
amptalk_RecruitingDeck_english_2024.06.05
 
Industrial Tech SW: Category Renewal and Creation
Industrial Tech SW:  Category Renewal and CreationIndustrial Tech SW:  Category Renewal and Creation
Industrial Tech SW: Category Renewal and Creation
 
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdfModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
 
The Influence of Marketing Strategy and Market Competition on Business Perfor...
The Influence of Marketing Strategy and Market Competition on Business Perfor...The Influence of Marketing Strategy and Market Competition on Business Perfor...
The Influence of Marketing Strategy and Market Competition on Business Perfor...
 
Organizational Change Leadership Agile Tour Geneve 2024
Organizational Change Leadership Agile Tour Geneve 2024Organizational Change Leadership Agile Tour Geneve 2024
Organizational Change Leadership Agile Tour Geneve 2024
 
Authentically Social by Corey Perlman - EO Puerto Rico
Authentically Social by Corey Perlman - EO Puerto RicoAuthentically Social by Corey Perlman - EO Puerto Rico
Authentically Social by Corey Perlman - EO Puerto Rico
 
Building Your Employer Brand with Social Media
Building Your Employer Brand with Social MediaBuilding Your Employer Brand with Social Media
Building Your Employer Brand with Social Media
 
3 Simple Steps To Buy Verified Payoneer Account In 2024
3 Simple Steps To Buy Verified Payoneer Account In 20243 Simple Steps To Buy Verified Payoneer Account In 2024
3 Simple Steps To Buy Verified Payoneer Account In 2024
 
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
 
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdf
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfThe 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdf
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdf
 
Structural Design Process: Step-by-Step Guide for Buildings
Structural Design Process: Step-by-Step Guide for BuildingsStructural Design Process: Step-by-Step Guide for Buildings
Structural Design Process: Step-by-Step Guide for Buildings
 
Best practices for project execution and delivery
Best practices for project execution and deliveryBest practices for project execution and delivery
Best practices for project execution and delivery
 
ikea_woodgreen_petscharity_dog-alogue_digital.pdf
ikea_woodgreen_petscharity_dog-alogue_digital.pdfikea_woodgreen_petscharity_dog-alogue_digital.pdf
ikea_woodgreen_petscharity_dog-alogue_digital.pdf
 
Observation Lab PowerPoint Assignment for TEM 431
Observation Lab PowerPoint Assignment for TEM 431Observation Lab PowerPoint Assignment for TEM 431
Observation Lab PowerPoint Assignment for TEM 431
 

Statistical Discovery for Consumer and Marketing Research

  • 1. Copyright © 2013, SAS Institute Inc. All rights reserved. STATISTICAL DISCOVERY IN CONSUMER AND MARKET RESEARCH 08 JULY 2014 | SHANGRI-LA HOTEL AT THE SHARD, LONDON
  • 2. Copyright © 2013, SAS Institute Inc. All rights reserved. WELCOME TO THE SHARD
  • 3. Copyright © 2013, SAS Institute Inc. All rights reserved. WHO’S HERE? FROM JMP Bernard Julie Malcolm Luke
  • 4. Copyright © 2013, SAS Institute Inc. All rights reserved. APPLICATIONS MAKE BETTER DECISIONS, FASTER WITH JMP
  • 5. Copyright © 2013, SAS Institute Inc. All rights reserved. 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
  • 6. Copyright © 2013, SAS Institute Inc. All rights reserved. AGENDA Time Topic Presenter 09:40 Introduction: Statistical Discovery in Consumer and Market Research Ian Cox 10:10 Case Study: Using Visualisation to Inform the Analysis of Large Survey Data Robert Anderson 10:50 Case Study: Predicting Behaviour from Ethnographic and Usage Data Ian Cox 11:20 Break 11:50 Case Study: Linking Sensory and Taste Panel Data to Make Better Products Ian Cox 12:20 Case Study: Targeting Offers More Effectively Using Uplift Modeling Robert Anderson 12:50 Conclusion Bernard McKeown 13:00 Lunch
  • 7. Copyright © 2013, SAS Institute Inc. All rights reserved. TODAY’S PRESENTERS Robert AndersonIan Cox
  • 8. Copyright © 2013, SAS Institute Inc. All rights reserved. AGENDA Time Topic Presenter 09:40 Introduction: Statistical Discovery in Consumer and Market Research Ian Cox 10:10 Case Study: Using Visualisation to Inform the Analysis of Large Survey Data Robert Anderson 10:50 Case Study: Predicting Behaviour from Ethnographic and Usage Data Ian Cox 11:20 Break 11:50 Case Study: Linking Sensory and Taste Panel Data to Make Better Products Ian Cox 12:20 Case Study: Targeting Offers More Effectively Using Uplift Modeling Robert Anderson 12:50 Conclusion Bernard McKeown 13:00 Lunch
  • 9. Copyright © 2013, SAS Institute Inc. All rights reserved. HELP US TO HELP YOU . . .
  • 10. Copyright © 2013, SAS Institute Inc. All rights reserved. (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
  • 11. Copyright © 2013, SAS Institute Inc. All rights reserved. (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
  • 12. Copyright © 2013, SAS Institute Inc. All rights reserved. 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
  • 13. Copyright © 2013, SAS Institute Inc. All rights reserved. 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
  • 14. Copyright © 2013, SAS Institute Inc. All rights reserved. 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
  • 15. Copyright © 2013, SAS Institute Inc. All rights reserved. STATISTICAL DISCOVERY IN CONSUMER AND MARKET RESEARCH
  • 16. Copyright © 2013, SAS Institute Inc. All rights reserved. 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.
  • 17. Copyright © 2013, SAS Institute Inc. All rights reserved. BROAD AREAS IN WHICH DATA ARISE Descriptive Research Usually 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 Research Ill-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 Research Establishing cause requires an explanatory theory, a statistical relationship, correct time ordering, and adequate control of any other Xs considered as extraneous. Sensory Studies Aim to understand how our human senses will contribute to the overall experience of consuming or using a product. Predicting Behaviour Y'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.
  • 18. Copyright © 2013, SAS Institute Inc. All rights reserved. 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.
  • 19. Copyright © 2013, SAS Institute Inc. All rights reserved. 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
  • 20. Copyright © 2013, SAS Institute Inc. All rights reserved. FUNCTIONAL ASPECTS OF WORKING WITH DATA . . . Data Access Data Management Analysis Reporting UserInterface Particularly in Marketing applications, in which users tend not to be (and should not be?) “statistical experts”, the User Interface is very important
  • 21. Copyright © 2013, SAS Institute Inc. All rights reserved. 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”
  • 22. Copyright © 2013, SAS Institute Inc. All rights reserved. 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
  • 23. Copyright © 2013, SAS Institute Inc. All rights reserved. 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’.
  • 24. Copyright © 2013, SAS Institute Inc. All rights reserved. AGENDA Time Topic Presenter 09:40 Introduction: Statistical Discovery in Consumer and Market Research Ian Cox 10:10 Case Study: Using Visualisation to Inform the Analysis of Large Survey Data Robert Anderson 10:50 Case Study: Predicting Behaviour from Ethnographic and Usage Data Ian Cox 11:20 Break 11:50 Case Study: Linking Sensory and Taste Panel Data to Make Better Products Ian Cox 12:20 Case Study: Targeting Offers More Effectively Using Uplift Modeling Robert Anderson 12:50 Conclusion Bernard McKeown 13:00 Lunch
  • 25. Copyright © 2013, SAS Institute Inc. All rights reserved. BREAK
  • 26. Copyright © 2013, SAS Institute Inc. All rights reserved. AGENDA Time Topic Presenter 09:40 Introduction: Statistical Discovery in Consumer and Market Research Ian Cox 10:10 Case Study: Using Visualisation to Inform the Analysis of Large Survey Data Robert Anderson 10:50 Case Study: Predicting Behaviour from Ethnographic and Usage Data Ian Cox 11:20 Break 11:50 Case Study: Linking Sensory and Taste Panel Data to Make Better Products Ian Cox 12:20 Case Study: Targeting Offers More Effectively Using Uplift Modeling Robert Anderson 12:50 Conclusion Bernard McKeown 13:00 Lunch
  • 27. Copyright © 2013, SAS Institute Inc. All rights reserved. APPLICATIONS MAKE BETTER DECISIONS, FASTER WITH JMP
  • 28. Copyright © 2013, SAS Institute Inc. All rights reserved. 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
  • 29. Copyright © 2013, SAS Institute Inc. All rights reserved. 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
  • 30. Copyright © 2013, SAS Institute Inc. All rights reserved. www.SAS.com