Light Customer Development ProjectLight Customer Development Project

Data AnalystMillie

Statistical Analyst Christian

Market Research AnalystSarah

Marketing StrategistNatvida

Summer 2013Summer 2013

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CONTENT TABLE

Methodology:

•objectives

•What variables we’ve chosen and why

•3 Steps to analysis the data

Findings

•General key findings

•Validation of the findings

•Our best customer profile

Recommendations

•how can we reach new customers

•How can we maintain and enhance the profit

level of existing customer

WHAT IS THE OBJECTIVE?

Profit is the fundamental goal of enterprises

-- Karl Marx

General Rule:Thus, as usual, we use RFM as the most important indicator of our analysis

WHAT VARIABLES DID WE CHOSE AND WHY

• recency_from_sub_end• frequency• ACCUM_AMOUNT

RFM Data

• lt_duration_yr• channel_0• PRODUCTS_RECENTLY_PURCHASE• IB_BUY_Beauty_Cosmetic_Aids• IB_BUY_Crafts_Hobbies• IB_BUY_Electronics_Gadgets

BEHAVIORAL DATA

• AGE• GENDER• IB_NUMBER_OF_LIFETRAITS• IB_OCCUPATION_CUSTOMER• IB_OWN_RENT_HOME• IB_MARITAL_STATUS• IB_NET_WORTH_ESTIMATOR• IB_PP_HOUSEHOLD_SIZE• IB_PP_NUMBER_OF_CHILDREN• STATE• ZIP_CODE• MAG_CUS_ACTIVE_MAGAZINES• MAG_CUS_ORIG_MAGAZINE• IB_VOTER_PARTY• personicx_group

DEMOGRAPHIC DATA

Why did we chose these data:Since we don’t have exact time of last purchase, recency_from_sub_end is the most close attributeAccum_amount is more significant than monetary since it’s not representative to just look at last purchaseDemographic, psychographic, behavioral data are 3 sets of data that marketers ususally use to identify target customers

VARIABLES THAT WE ABANDONED AND WHY

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• IB_WORKING_WOMAN_IN_HH• DIGITAL_INDICATOR_FLAG• LT_digital_title• lt_digital_sub_ind• lt_digital_print_auth_ind

INVALID DATA

• magnitude• order_year_0• order_month2_0• order_week2_0• MAG_CUS_ACCUM_AMOUNT

UNNECESSARY DATA

• IB_PRESENCE_OF_CHILDREN• IB_LT_Cat_Owner• IB_LT_Dog_Owner• IB_LT_Other_Pets

norm_renew_score• auto_renew_cc_score• auto_renew_bill_score• channel_internet_score• channel_traditional_score• EMAIL_PRESENCE_FLAG• IB_LENGTH_OF_CURRENT_RESIDENCE

COMBINED DATA

Why didn’t we chose these data:Life duration is used instead of order_year / month / weekMag_cus_accum_amount has the same dataset with accum_amountThere are too many missing data in invalid data setSome data can be combined together. E.g. if cat/dog/other pets owner can be combined to if pets owner

STEP1: RUN CORRELATION_GENERAL

STEP1: RUN CORRELATION_GENERAL

General Rule:Correlation are run between RFM Data and demographic / psychographic / behavior dataDidn’t use ANOVA or Regression. Since RFM may not be independent from each other

First used MONOVA to test under a DPB variable, whether RFM are independent from each otherThen used Discriminant function analysis to identify whether a DPB variable has influence over RFM* In order to save labor, also used Canonical analysis to run several DPB variable togetherLast but not least, run regression between that DPB variable and RFM

STEP 1: TAKE LT DURATION YEAR AS AN EXAMPLE

SAS CODE FOR LT_DURATION & RFM

STEP 1: TAKE LT DURATION YEAR AS AN EXAMPLE

MANOVA shows RFM are significantly independent from each otherWhile CANDISC indicates that at least one factor of RFM is affacted by lt_duration

STEP 1: TAKE LT DURATION YEAR AS AN EXAMPLE

The plot clearly showed that accum_amount and lt_duration is posstively correlatedWhile the p value indicates that the correlation is significant

STEP 1: TAKE LT DURATION YEAR AS AN EXAMPLE

Correlation coeffeciency between lt_duration and frequency is lowerBut still significantly related ( P value 0.0076 smaller than 0.05)

STEP 1: TAKE LT DURATION YEAR AS AN EXAMPLE

Recency is negatively correlated as you may see from the graphBut it’s reasonable since the smaller it is, the earlier you renewed the magazine. And loyalty customers tend to renew their magazine more actively

STEP 1: OTHER EXAMPLES

However, it’s not always true that DPB variables are correlated with RFMFor example. Recency has nothing to do with age. It makes sense, if the magazine is run by month, and customer subscribe to one year, it doesn’t matter if the customer is 80 yod or 18 yod

STEP 1: OTHER CODINGS

For categorical data, use glm and class instead of regression to run the correlation

STEP 2: RFM VALUE CALCULATION

RECENCY

FREQENCY

MONETARY

• If smaller than -1, rate it 5

• If smaller than -0.5, rate it 4

• If smaller than 0, rate it 3

If smaller than 1, rate it 1

If smaller than 2, rate it 2

If smaller than 3, rate it 3

If smaller than 4, rate it 4

• Divide accumulative amount by 10000

• If bigger than 7, use 7

• If equal to 0, rate it 2,

• If smaller than 1, rate it 1

• If bigger than 1, rate it 0

Through SAS analysis, we found that 50% DPB variables are related to monetary factor, while 30% are related to frequency, 20% related to recency. We use the ratio and calculated a new RFM Value, we call it customer valueAnd then run pivot table analysis between customer value and DPB data

50%

20%

30%

STEP 3: CUSTOMER VALUE & DPB VALUE PIVOT TABLE ANALYSIS

Then we run pivot table analysis among the variables and customer value to visualize the findings

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CONTENT TABLE

Methodology:

•What variables we’ve chosen and why

•How did we analysis the data

•What tools did we use

Findings

•General key findings

•Validation of the findings

•Our best customer profile

Recommendations

•how can we reach new customers

•How can we maintain and eenhance the profit

level of existing customer

KEY FINDINGS: 28-45 IS THE BEST RANGE FOR TARGET CUSTOMER

KEY FINDINGS: FEMALE CUSTOMERS ARE 15.6 TIMES MORE VALUABLE THAN MALE CUSTOMERS

KEY FINDINGS: CUSTOMERS WHO OWN THEIR HOUSE ARE 19.8 TIMES MORE VALUABLE THAN THOSE WHO RENT

KEY FINDINGS: MARRIED COUPLES ARE MORE VALUABLE THAN SINGLE CUSTOMERS

KEY FINDINGS: DEMOCRATS ARE MOST VALUABLE

If independent generates 1 unit of RFM value, democrats will contribute 7, while republican gives 17, vacancy gives 10

Vacancy Independent DemocratsRepublican

KEY FINDINGS: GEO DISTRIBUTION

KEY MARKETS THAT SHARE THE HIGHEST VALUEABLE CUSTOMERS: Tier 1: California, Texas, New YorkTier 2: Illinios, Pennsylvania, FloridaTier 3: Arizona, michigan, Ohio, Tennessee, Georgia, North Carolina

KEY FINDINGS: HIGH VALUALBE ZIP-CODES

Top Zip code Area is as follows: New York City has the top 2, which is coordinate with the geo distribution San Jose has relatively high income residents due to the insensitivity of high-tech companies Lancaster has well-educationed population, so does chicago, near northwestern univ.

SAS VALIDATION

SPSS VALIDATION

Findings Via Skype:53% of its circulation in the top ten U.S. metropolitan areas Average Income is $109,877 (2009)

BEST CUSTOMER PROFILE: CAREER WOMEN CINDY

Gender: Female

Age: 40 years old

Marital Status: Married (no kids)

Occupation: “Occupation 4”

Income level: High

Area of residence: Manhattan, New York

Zip Code: 10021 (Upper East)

Owner of home

Political Affiliation: Democrat

Beliefs: Liberal: Pro choice etc.

Favorite News Channel: MSNBC

Hobbies and Interests: Traveling, Reading,

Zoomba, Art Museums, Jazz Clubs

RUN CUSTOMER DEMO/PSCHO ON ETELMAR

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CONTENT TABLE

Methodology:

•What variables we’ve chosen and why

•How did we analysis the data

•What tools did we use

Findings

•General key findings

•Validation of the findings

•Our best customer profile

Recommendations

•how can we reach new customers

•How can we maintain and enhance the profit

level of existing customer

ACQUISITION: TV COMMERCIAL

How to enhance the influence among target audience most efficiently: TV Advertising in California, New York and Texas Buy commercial in tv programs our target customers are watching

How to enhance the influence among target audience most efficiently:Top magazines our target audience is reading Use up-seling and cross-sell to increase profit

CUSTOMER ACQUISITION: MAGAZINE

32Copyright © 2007 Accenture All Rights Reserved.Copyright @ 2007 Accenture. All rights reserved.

How to enhance the influence among target audience most efficiently:Radio is still one of the strongest influencersCommuting Radio in car is the best choice for our target audience

ACQUIRE NEW CUSTOMER: RADIO

33Copyright © 2007 Accenture All Rights Reserved.Copyright @ 2007 Accenture. All rights reserved.

How to enhance the influence among target audience most efficiently:Direct Mail Campaign in top 6 zip code areas Also, NCOA provide great opportunity to reach out to potential customers

ACQUIRE NEW CUSTOMER: DIRECT MAIL

ACQUIRE CUSTOMERS: OTHERS

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Other ways to enlarge customer database: Invite friends, earn credits Enable Subscription in store

RETAIN LOYAL CUSTOMER: 5 KEY METHODS

How to maintain customer : Loyalty Program ( Offers & Discounts, Benefits) Insert in magazine for renewSurvey & Questionnaire Event / Experiential marketingSocial Media Enagement