DISCOVERING NEW CONSUMER INSIGHTS

USING PARTITION ANALYSIS

Using JMP Partitioning as a treasure map of your data

Diane Navin, Mike Creed, Amy Phillips, Jen Schutte 9/21/16

AGENDA

About P&G

What is JMP Partition?

When to use Partitioning

How to run JMP Partition

2015 Company Overview

Our Purpose We will provide branded products and services of superior quality and value that improve the lives of the world’s consumers, now and for generations to come.

As a result, consumers will reward us with leadership sales, profit and value creation, allowing our people, our shareholders, and the communities in which we live and work to prosper.

About P&G … Founded in 1837

William Procter James Gamble

1879 - Introduced Ivory Soap

…Started with STAR

Candles P&G is the 4th oldest

Entity of the Fortune 50

Our Values

P&G is its people and the values by which we live.

Countries of Operations ~70

Countries Where Our

Brands Are Sold 180+

P&G At A Glance

2015 Net Sales BY BUSINESS SEGMENT

Beauty

Grooming

Health Care

Fabric Care and Home Care

Baby, Feminine and Family Care

18%

11%

10%

32%

29%

*Results exclude net sales in Corporate. Results for the Beauty segment exclude sales for several Beauty categories P&G plans to exit, as the Company announced on July

9, 2015. P&G referred readers to the informational 8-K furnished on September 8, 2015 and the revised Form 10-K for FY15 furnished on October 26, 2015, which provide more details of the impacts to its financial results due to this change.

2015 Net Sales BY GEOGRAPHIC REGION

North America

Europe

Asia Pacific

Latin America

IMEA

Greater China

41%

10%

24%

8%

8%

9%

Results exclude sales for several Beauty categories P&G plans to exit, as the Company announced on July 9, 2015. P&G referred readers to the informational 8-K furnished

on September 8, 2015 and the revised Form 10-K for FY15 furnished on October 26, 2015, which provide more details of the impacts to its financial results due to this change.

A Company of Leading Brands

Innovation – The Lifeblood of Our Business • P&G invents brands and products that create and

transform categories.

• We’re rededicating ourselves to product innovation that “wins from the top” – offering:

– the best-performing products in the category,

– with the highest quality,

– at a modest price premium,

– yielding superior consumer value.

JMP AT P&G:

BUILDING A MODELING CULTURE

Easy to Use for the non-Expert

Easy to Understand and Communicate

JMP Categorical

Power of JMP

WHAT IS JMP PARTITION?

A version of classification and regression tree analysis

A treasure map that shows you the best places in your data to hunt first for treasure! It helps you find key relationships like:

Which variables, or combination of variables, best differentiate

likers vs dislikers Which demographics describe them?

Which performance variables did they answer

most differently from each other?

HOW DOES JMP PARTITION WORK?

It is like running many breakouts at once and identifying the variable that results in the largest swing (high….low) in the dependent variable

That variable becomes the first node in the tree

This is repeated for each branch finding the next variable and split that will result in the largest impact on each subsequent node

It can handle variables of different types (nominal, ordinal, or continuous) and it can handle data on different scales (agreement scales, demographics, segmentation, dipolar, yes/no, etc)

WHEN TO USE JMP PARTITION ?

• Interactive Data Mining

• Find new insight in mined data – What pops!

• Early in data analysis to identify key areas to dig deeper

• Understand impact of habits / practices / attitudes / verbatims / attribute evaluation

• Find combinations of variables that predict another variable

• Quickly testing ideas

• It handles large problems easily

• The results are very interpretable

PARTITIONING EXAMPLE

What are different variables we could measure to help us differentiate men from women? (in a work-appropriate way)

Height?

Hair length?

Facial hair?

Pierced ears?

Shoe size?

Wearing heels?

But which of our variables, or combinations of variables, are the BEST at differentiating men from women?

PARTITIONING EXAMPLE

We have created a model of gender.

The model says that:

Women tend to …

Men tend to…

Gender

Long Hair

No Facial Hair

Facial Hair

Short Hair

No Facial Hair

Wearing heels

Not Wearing Heels

Facial Hair

USE JMP PARTITION

POKÉMON GO

OVERNIGHT SUCCESS!

BUT, THERE WERE CONERNS…

HYPOTHETICAL RESEARCH QUESTION:

Should I advertise Tide on Pokémon Go?

FIND THE SURVEY DATA

“Privacy and Information Sharing” Jan/Feb 2015

Publically Available: Pew Research Center

• 87 Questions

• 461 People

• Attitudes & Demographics

The Pew Research Center bears no responsibility for the interpretations presented

or conclusions reached based on analysis of the data.*

Note: Survey data was transformed to Triple-S prior to import to JMP.

“PRIVACY AND INFORMATION SHARING”

9 Attitudes about Privacy

7 Scenerios: Grocery Store Free Loyalty Card

Health Information Website

Social Media for High School Reunion

Gaming App Insurance Company Device in Car

Workplace Cameras

Thermostat Sensor

Demographics

JMP PARTITIONING: HOW TO

Before you begin

Clean and organize

your data

Left Click

JMP PARTITIONING: HOW TO

Before you begin

Clean and organize

your data

JMP PARTITIONING: HOW TO

Before you begin

Clean and organize your data

Select: Rows Delete Rows

JMP PARTITIONING: HOW TO

Before you begin

Clean and organize your data

Make sure variables are categorized correctly

(nominal, ordinal, or continuous)

Make sure your dependent variable is coded

according to the levels you want it to split on.

Right Click

Select: Analyze Modeling Partition

SELECT PARTITION

SELECT VARIABLES AND OPTIONS

Select your Dependent variable (the variable you want to model) and click “Y, Response” button

Select the Independent variables you want your Partition to use and click the “X, Factor” button

Uncheck Informative missing to prevent JMP from treating missing as a separate category

Check Ordinal Restricts Order to maintain the ordinality of the responses when determining splits

Select Decision Tree as Method

Click OK button to run

Select Color Points button to color

code your data

SELECT COLOR POINTS

SELECT COLOR POINTS

SELECT VALUE COLORS

VALUE COLORS = STOPLIGHT

SELECT: ANALYZE MODELING PARTITION

Select the red triangle for the Partition

window to set Display Options.

Check Show Split Counts

Now the data we are most interested in will

show up inside each node

SET DISPLAY OPTIONS

HOW TO READ THE PARTITION

• This Count shows the total number of panelists in this branch of the tree

• The color of the bars are the same color coding as the panelists in the partition.

• The size of the bars represents the fraction of that

type of panelist in that branch

• Rate shows the percentage of panelists in each level of that branch

• This Count shows the number of individual panelists in each level in that branch

HOW TO GROW THE TREE

• To grow the tree one level

click “Split”

• To reduce the tree one level

click “Prune”

GROWING THE TREE

JMP looks at all your

independent variables and

determines which one

variable is best at

differentiating between

people who said Yes or No.

In this case that variable is

Not having someone watch or

listen to you...

GROWING THE TREE

GROWING THE TREE: CANDIDATES

GROWING THE TREE: SPLIT SPECIFIC

LET’S LOOK AT DEMOGRAPHICS

DEMOGRAPHICS TREE

Who is the group who finds the Gaming App Scenerio acceptable?

• Younger

• Not Head of Household

RECAP WHEN TO USE JMP PARTITION

• Interactive Data Mining

• Find new insight in mined data – What pops!

• Early in data analysis to identify key areas to dig deeper

• Understand impact of habits / practices / attitudes / verbatims / attribute evaluation

• Find combinations of variables that predict another variable

• Quickly testing ideas

• Who are Likers / Dislikers?

• Which performance variable was most correlated to liking

• Are there trends in demographics/segments

• Trouble shooting problems

KEY TAKEAWAYS ON JMP PARTITION

JMP Partition helps you find key relationships in your data that are a good

place to start your exploration

It builds a classification tree model that helps you understand your data better

It’s especially good when you need to explore the relative impact of variables

that are different types or variables on different scales

Now you have another tool in your toolbox!

QUESTIONS?