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IBM Customer Analytics Strategy

IBM Customer Analytics Strategy

This is a draft of the cross-business unit IBM Customer Analytics strategy that I led post Tealeaf's acquisition by IBM. This strategy included all of IBM's analytics assets at the time, Tealeaf, Coremetrics, Cognos, etc.

Geoff Galat

August 24, 2013
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  1. © 2014 IBM Corporation
    Predictive Customer Intelligence
    • Future Buying Insight
    • Anticipate and delight
    customers with solutions
    • Buying propensities and
    patterns
    • Product preferences
    • Related products
    Digital Analytics
    • Quantitative Insight
    • Web site and mobile traffic
    data
    • Customers in purchase
    funnel
    • Completed transactions
    • Conversion metrics
    Optimizing Customer Experience Requires Combining Digital,
    Behavioral, Sentimental & Predictive Analytics
    1
    Customer Behavior Analytics
    • Qualitative Insight
    • Surface Customer struggle
    on digital channels
    • Session replays to
    understand actual customer
    journey
    • Identify impacted customers
    Sentiment Analytics
    • Soclal Media Insight
    • Prevailing sentiments
    • Relevant relationships
    • Potential risks

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  2. © 2014 IBM Corporation
    Customer Analytics For The Enterprise
    Understanding The Context of All Customer Interactions Has Profound
    Business Impacts
    § Increased Revenue
    – Better Conversion/Adoption
    – Higher Lifetime Customer Value
    – Increased Share of Wallet
    – More Repeat Customers/Buyers
    § Higher Customer Satisfaction
    – Reduced Customer Struggle & Friction
    – Better Net Promoter Scores
    – Reduced Churn; Higher Customer Loyalty
    – Understanding Social Commentary &
    Sentiment
    § More Effective Customer Acquisition
    – Better Targeting Based on Intents/Interests
    § Reduced Operational Costs
    – Higher Call Avoidance/Deflection
    – Faster Site Maintenance, Problem
    Resolution
    2
    Customer
    WWW

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  3. © 2014 IBM Corporation
    CA Use Case 1
    Customer Acquisition - Retail
    March 2014
    INTERNAL USE ONLY – Do not Distribute

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  4. © 2014 IBM Corporation
    Step 1 - Analysis of Keywords data with Digital Analytics
    PPC and SEO keywords
    Site search keywords

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  5. © 2014 IBM Corporation
    Step 2 – Develop list of sites where the potential customers
    hangout with SMA using DA keywords list
    IBM Digital
    Analytics
    Keywords data
    IBM SMA
    Identify potential
    customers
    List of websites

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  6. © 2014 IBM Corporation
    Step 3 – Targeting the websites with targeted display ads
    List of websites
    Display ad
    targeting/retargeting

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  7. © 2014 IBM Corporation
    Step 4 – Measuring Attribution Digital Analytics

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  8. © 2014 IBM Corporation
    Step 4 – Measuring Attribution xxxx

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  9. © 2014 IBM Corporation
    Step 4 – PCI Optimizes Attribution
    9
    WWW
    WWW
    WWW
    PCI
    IBM Digital
    Analytics
    IBM SMA
    Attribution
    Marketing
    Center

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  10. © 2014 IBM Corporation
    Questions?
    10

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  11. © 2014 IBM Corporation
    CA Use Case 2
    Customer Retention - Telco
    March 2014
    INTERNAL USE ONLY – Do not Distribute

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  12. © 2014 IBM Corporation
    Step 1 – Building complete customer profile
    12
    Repeat customer
    clicks on a link
    from a trusted
    brand tweet
    •User lands on a TL and DA monitored site
    • DA matches cookie data to session ID
    •TL session ID synched with DA session ID
    •TL captures all behavioral data
    • Customer opted in with social media IDs
    Environmental data

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  13. © 2014 IBM Corporation
    Step 2 – Understand Customer Behaviors
    13
    Browsing and adding
    products to shopping cart
    TL captures customer behaviors
    Remove an item Check out

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  14. © 2014 IBM Corporation
    Step 3 – Understand Customer Profile
    14
    Browsing and adding
    products to shopping cart
    DA captures customer profile
    Check out

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  15. © 2014 IBM Corporation
    Step 4 – Understand User Sentiments
    15
    SMA captures customer sentiment:
    brands, preferences, and challenges
    Love the new
    Android phone
    from Telco
    Especially the
    gold one
    But will have
    to wait for
    sales…L

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  16. © 2014 IBM Corporation
    Step 5 – Complete Insights
    16
    TL, DA, and SMA provides complete insights
    Behaviors Sentiments
    Profiles

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  17. © 2014 IBM Corporation
    Step 6 – PCI improves Meaningful Engagement
    17
    Behaviors
    PCI
    Sentiments
    Profiles
    Xtify
    10% off on Gold
    Android phone from
    Telair
    10% off on Gold Android
    phone from Telair

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  18. © 2014 IBM Corporation
    CA Use Case 3
    Reduce Churn – Financial Services
    March 2014
    INTERNAL USE ONLY – Do not Distribute

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  19. © 2014 IBM Corporation
    Step 1 – Capturing All Interactions
    19
    Customer clicks
    on a link from an
    email from her
    bank
    Bank site deploys IBM CA that captures
    both Behavior and Profile data
    Environmental data
    Narrative:
    •Customer receives an email offer for a low rate for refinancing home loan from her
    bank
    • She is interested and clicks on the link from her smartphone to find out more
    information
    •Bank site is monitored by IBM CA that includes both Behavior and Profile data
    • All interactions are being captured by IBM CA (behaviors and profiles)
    •Being an existing customer, she as opted in with contact information including
    social media IDs

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  20. © 2014 IBM Corporation
    Step 2 – Understand Customer Behaviors and Profiles
    20
    Downloaded
    native app
    IBM CA captures customer behavior and lifecycle data
    Started the refinancing
    application process
    Stopped using
    the app
    X
    Called Contact
    Center
    Narrative:
    •She saw the call to action to down load the newly available mobile app. She
    proceed with the download and installation process.
    •She logs in using her username and password
    • She proceeds to start the quick quote option in the app
    •At the enter the house address field she keeps receiving an error messaging:
    invalid address
    •After several tries she called the contact center. She abandoned the process

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  21. © 2014 IBM Corporation
    Step 3 – Understand User Sentiments
    21
    IBM CA captures customer sentiment:
    brands, preferences, and challenges
    Looking into new
    refi rates from
    Finance1
    Especially the
    30 fixed rate
    But their app
    sucks…L
    Narrative:
    •She tweeted her friends about her experience.
    •With the opted in social media IDs IBM CA can monitor for customer sentiment

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  22. © 2014 IBM Corporation
    Step 4 – Complete Insight
    22
    IBM CA provides complete insight
    Behaviors Sentiments
    Profiles
    Narrative:
    •Combining Behavior, Profile, and Sentiment data IBM CA provides complete
    insight into customer interactions.

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  23. © 2014 IBM Corporation
    Step 5 – PCI Identifies Potential Churn Segments
    23
    Behaviors Sentiments
    Profiles
    PCI
    Narrative:
    •PCI provides deep insight analytics leveraging
    Behavior, Sentiment, and Profile data
    •Discovers that home loan is the key difference
    between churned and loyal customers
    •Need to improve the refinancing product and
    processes

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  24. © 2014 IBM Corporation
    Step 6 – IBM CA Uncovers Challenges
    24
    Home Loan is key
    loyalty metrics
    PCI
    Behaviors
    •Mobile app
    address error
    struggles
    •Website
    struggles
    Profiles
    •Churned
    segment profiles
    •Lifecycle data
    Sentiment
    •Mobile App
    issues
    •Quick quote did
    not work on site
    •Rates are good
    Narrative:
    •Sentiment uncovers 3 themes around
    mortgage:
    •Mobile app sucks
    •Website quick quote did not work
    •Rates are competitive
    •With data from Sentiment, Profile provides
    key segments on abandoned mortgage
    new/refinancing processes
    •Leveraging segments from Profile,
    Behavior analyzed specific interaction and
    found
    •Mobile app has non-descriptive error
    •Error was caused by “-” (program
    logics)
    •Quick quote from website has the
    same issue
    •Need to improve the refinancing product
    and processes

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  25. © 2014 IBM Corporation
    Step 7 – Actionable insight
    25
    Home Loan
    key metrics
    PCI
    Behaviors
    •Mobile app
    address error
    struggles
    •Website struggles
    Profiles
    •Churned
    segment profile
    •Lifecycle data
    IT
    •Fixed “-”
    program logics
    Sentiment
    •Mobile App
    issues
    •Quick quote did
    not work
    •Rates are good
    Social Media
    •Check out our new app
    •Same great rates
    Real time interactions
    •Check out our new app
    •Same great rates
    WWW

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