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Capital One Case Study

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Case questions

1. What is their business strategy to grow profitably and compete over the long term?

Capital One Success Factors
Pilot Strategy

(first stages) • Initially, they began with a pilot strategy at Signet Bank to test their customer targeting systems • Successful and profitable within a couple years – created Capital One
Competitive Edge

(risk analysis)

(redemption offers)

(customer loyalty)

(targeted offers) • Recognized large customer base in high risk credit customers
• Developed IS with data analytics that determined probability of receiving money from high risk customers
• Targeted credit options through wide array of data (web streams, credit reports, club cards & memberships) *** • Successful in determining fraudsters and extremely high risk profiles
• Allowed a credit building option to people who weren’t allowed credit elsewhere
• Successfully expanded customer base through the internet by testing advertisements
Customer Retention

(customer service)

(long term retention) • Real-time data available to customer service agents that showed available credit options to individual customers
• Data analysis through SAS Institute and Brio to determine whether or not customers were lying about other offers in order to receive a lower APR • Capital One has lowest default rates among credit companies
• Data analysis can eliminate fraudsters and help retain truthful customers
Finding Profit with Risk • Advanced data analysis software can determine levels at which a high risk customer can still be profitable • Customers who buy a lot, but pay back slowly can create profit for Capital One

*** After visiting CapitalOne.com, I browsed available cards. I noticed that the html address included my clicks/stream to the page

2. Describe how Capital One uses information to implement their strategy? What kinds of information do they use and where does it come from (sources)?

• Credit Reporting Agencies (Transunion, Equifax, Experian) – access to potential customer credit cards and loan history – This information determines not only the overall risk of a client, but how likely they are to pay back their credit lenders
• Post Office – Can verify customer identity and perform background checks
• ‘Lifestyle’ – target specific customers with opportunities of interest – flyer rewards for frequent business flyers, small business owner discounts, environmentalist card design, the list goes on..

3. Describe their notion of a “scientific test”. Compare and contrast this approach to product development and launch with a more traditional approach that a manufacturing company might use.

Product Development and Launch
Traditional ‘Scientific Test” Capital One’s “Scientific Test”
Stakeholder Analysis (internal)
• Key players are CEOs, CIOs, and other executives within IT and business
• Product development directors and managers stay involved but do not provide end decisions
• Manufacturing/Design staff remain at a need to know basis Stakeholder Analysis (Internal)
• Key players are executives and project directors and managers
• IT staff as well as business decisions makers are present during initial stages
• All staff are welcomed to present new testing ideas (if results are promising it is implemented immediately)
Development
• Basic IT consultation and planning
• Phased testing and retesting before launching/introducing it into operations
• Staff are considered less
• IT staff are asked to complete projects without being part of initial process Development
• IT department works closely with business side to evaluate feasibility ahead of time
• 45,000 different tests performed annually (in 2000) – implies that testing is an open and immediate process at center of operations
Launching
• Advertising/Marketing – companies grab any slot they can and push products Launching
• Advertising/Marketing – advertising stream helps determine risk of clients – they act as a test themselves
• “Customers Find Us” approach

4. Describe the information technologies/systems used to support the “scientific test” approach. Are these investments justified?

• The Click-Stream Test – can partly determine whether or not a customer is a potential fraudster. Justifiable, but can impede on customer privacy
• Data Sponge – customer data is collected from virtually all over the web and whatever is accessible from tangible sources. Justifiable, but poses from ethical issues. Customer data is ‘given away’ without direct consent.
• Data Cleaner – software from Trillium to culminate relevant data, such as demographics, addresses, credit history, and interests
• Business Intelligence Software – SAS Institute and Brio – deep analysis of data from Trillium. Provides analytics such as customer behavior and chance of default (advanced risk calculator)

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