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  • Know your customers by knowing who they know, and who they don'tLeveraging The Power Of Social InteractionsTim Manns

  • 2

    Overview

    Brief Definition Of Data Mining

    Data Processed Within The Teradata Warehouse

    Main Types of Customer Analysis Performed

    ROI Justification For Customer Analysis

    Identification Of Social Groups

    We Can Leverage The Social Interactions Of Our Customers

    Business Focused Examples And Benefits

    Some Generalisations For Other Industries

  • Brief Introduction To Optus

    Telco Challenger To Australias Incumbent Part Of SingTel Group Truly Convergent Telco

    Mobile (cell phones) Fixed (land phones) Fixed Broadband Mobile Broadband Business Networks Subscription TV Satellite

  • Definition Of Data Mining

    Jimi HendrixCome on (let the good times roll)

    Definition:The processing of large amounts of data

    in order to extract useful and insightful information

    Quote:People talking but they just don't know, What's in my heart & why I love you so. I love you baby like a miner loves gold. Come on sugar, let the good times roll!

    To understand the customer

    communications are targetedbehavioural driverswhat customers want

    happy customers = high value

  • Data Storage = 100% Data Warehouse

    Transactional Level DataCall Detail Records (cdrs)

    Some Fictitious Numbers 5 million customers 20 calls per day 100 million rows per day

    Enterprise Data Warehouse Usage, Downloads, Handset Billing, Product, Payments Point-Of-Sale, Contract Name, Address, Age, Tenure Customer Service, On-line

  • Business Data Mining Problems

    Predicting Churn/Attrition Customer Segmentation Revenue Stimulation (up-sell) Product Stimulation (cross-sell) Ad-Hoc Customer Profiling Product/Rateplan Pricing Deep-Dives Business Decision Evaluations Fraud Credit Risk

    ?

  • Bigger Piece Of The $ Pie

    Cost Of Losing Customers (Example) 5 Million Customers Average Monthly Spend $50 Voluntary Churn Is Approx 25k(0.5% Of Base Per Month)

    Revenue Loss Due To Churn $1.25 Million Per Month

    Increase Customer Value New Plan Or Offer Increases Spend To $55 (10% increase)

    In Just 10% of Customers Increase Revenue By $2.5 Million Per Month

  • Why Piece Together Social Groups?

    Identify Friends and Family Measure word-of-mouth Influence Of Customers and Individuals Of Outbound Communications Measure Impact Of refer-a-friend Behaviour In Customer Acquisition

    Better Understand Customer Value AndValue Of Prospects!

    Be Ahead Of The Shift Away From Brand Driven TV Commercials

    Because Friends Are Many Times More Influential Than Corporations

  • We Built An In-House Solution

    Process Weekly History Of All Customer Calls (approx 600 million records for 4 weeks)

    String Cleaning Of Phone Numbers SQL Queries Written To Summarise Every Customer Calling Relationship

    Outbound Calls To Other Inbound Calls From Other Join Inbound and Outbound To Confirm Reciprocal Relationship (And Select Frequency)

    Six Weeks. Project Conception To Completion Focus Is Customer Analysis (for legal reasons)

  • Ant sized view Data Manipulation!

    sms

    sms

    voice

    Call Type (voice, sms, picture)

    x 20 columns info..

    inbound

    inbound

    outbound

    Inbound / Outbound

    2009-10-20012345678046666666

    2009-10-200123456780403203383

    2009-10-190123456780403203383

    Date timefriendcustomer

    Transactional level (weekly approx 600 million rows)

    Main Result Table (approx a few million rows)

    5

    30

    Inbound Voice Call Count

    15

    5

    Inbound SMS Call Count

    x 20 columns info..

    20

    35

    Inbound Call Count

    012345678046666666

    0123456780403203383

    friendcustomer

  • Keeping It Simple Proved A Success

    Identify The Nature Of Customer Relationships Many Factors Can Be Considered

    Time Of Day, Day Of Week Voice, SMS, Picture Calls Voice Call Duration

    45yr WifeNew Phone

    Work ColleagueUses Email And Data

    Weekend BuddyNot A Customer

    Moving To Optus? John Doe

  • Customer Insights Gained Through Social Analysis

    Optus YNetworker

    Age 17 yrs (f)

    John DoeNetworker

    Age 47yrs?(m)

    John DoeData User

    Age 47yrs? (m)

    Jane Smith-DoeAlways In Touch

    Age 46 yrs (f)

    Exchange total 25 SMS per week Most calls made approx 5pm 7pm

    same accountsame address

    Exchange total 5 SMS per week 20 Voice Calls between 9am and 6pm Most calls made approx 3.45pm

    Minor communication

    Exchange total 10 SMS per week Exchange total 5 voice per week Most calls made approx 9am

    Optus XSaver

    Age 18 yrs (m)X 20

    Cheerleader (17 yrs)Computer Programmer

  • Save The Cheerleader. Save The World.

    The purchaser is not necessarily your customer Identify your leaders, your cheerleaders! A multi-million $ TV advertising campaign can be wreaked by a 17 yr old cheerleader

    Identify and target key influencers in your customer base and disproportionately benefit your brand

    The problem of customer churn is far worse than you think; Churned customer tells friends (prospects) Friends get influenced to churn also Prospects go to a competitor Win-back campaigns a wasted cost

  • Churn Is More Than Predictive Problem

    Customers In Social Groups With Recently Churned Customers Are More Likely To Subsequently Churn

    Reactive Trigger Event Campaign To RetainCustomers When A Friend Churns

    Have A Voice In The BBQ Chat!

  • Our Predictive Churn Models

    Our Ability To Predict Churn In The Subsequent Month Using Social Groups, Usage, Billing, Demographics, And Contract Data

    5% of Customer Base Achieves Lift Of 10

    0

    5

    10

    1 5

    20

    1 1 0 20 30 40 50 60 70 80 90 100P o p u l a t i o n %

    Magn

    itude

    Increa

    se

    C h u r n M o d e l P e r f e c t M o d e l

  • Conclusions

    Analysis Of Social Groups Using Our Detailed Transactional Data Has Enabled New Customer Insights

    Unparalleled Customer Targeting Improved Predictive Churn Analysis A Reduction In Churn Saves $m Enabled Better Family Identification Sell Household Products To Families Greater Share Of Family Wallet Measure Viral Impact Of Direct Marketing

  • Questions

    tim . manns optus . com . au