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Infogroup Consumer Database

Infogroup Consumer Database. C. A. R. overage. ecency. ccuracy. Quality. Infogroup Data Assets. U.S. Consumer Database. www.infogroup.com. U.S. Database of 115 million households and 225 million individuals enhanced with individual & household-level demographic information

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Infogroup Consumer Database

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  1. Infogroup Consumer Database C A R overage ecency ccuracy Quality

  2. Infogroup Data Assets U.S. Consumer Database www.infogroup.com U.S. Database of 115 million households and 225 million individuals enhanced with individual & household-level demographic information Original Compiler with a proven track record since 1917. No really. 75 contributing sources and 3.5 billon records aggregated annually High value demographics include age, income, homeownership, home value, real estate details, phone, presence of children, lifestyles, and behavioral data. New Mover Database: 15 million recent movers, 2 to 3 weeks from move date New Homeowner Database: 3.2 million new homeowners over the last 12 months 2

  3. Infogroup’s Consumer Data Assets • Consumer Database: Database of 115 million households and 225 million individuals enhanced with demographic information. • Consumer Emails:24 million matched to CDB; 54 million on ‘combined’ acquisition email database; 183 million available for append; 300 million for reverse append. • Occupant File: Database of over 146 million addresses, used for saturation mailings. • Occupation File: Database of approximately 16 million licensed individuals, at work or home. • New Movers: Database of 16 million new movers over the last 12 months. • New Homeowners: Database of 3.2 million new homeowners over the last 12 months. • Public Record: Database of over 16 million U.S. business and residential bankruptcyfilings.

  4. Infogroup’s White Page Compilation Infogroup focuses on speed and accuracy • 4,000 Phone Books • 210 MM Listings • 90% received within 30 days of release • Compiled within 8-12 weeks • Updated Annually • Methodology • Scanning of White Pages (5 OCR engines) • 100% Key Entry • Computerized Review • Manual Resolution of Differences • 99.5% Accuracy

  5. PreviousMatches Updated File Single-Key Record Consumer Compilation Process Auto Parse: Data is “placed” into the correct field. OCR scanned images are converted to useable text. Each page is individually scanned. Phone Books Received Jomes, J. = Jones, J. Unmatched records are sent to “Single Key” process. Single-Key records are merged with original records. Final Parse:Records that cannot be Auto Parsed are done manually. Electronic Matching: Current months vs. previous month. Data Validation:Merged records are processed against USPS, FTC, DMA, Infogroup “flags” CONSUMER DATABASE (8-12 week process) Quality Assurance Check

  6. White Page Database Applications Reference Products -Internet Directory Assistance -CDroms Sources Over 4,000 Phone Books 80 Million Households - 88 Million Individuals White Pages

  7. Expanded White Page Database Applications Reference Products Sources White Pages plus additional individuals Expanded White Pages White Pages 80M Households - 88M Individuals 80 Million Households - 124 Million Individuals

  8. Consumer Marketing Database Applications Marketing -Telemarketing -Direct Mail -Modeling Sources 3.5 Billion records from 75 different sources Consumer Marketing Expanded White Pages 80M Households - 124M Individuals 80M Households - 88M Individuals 115 Million Households - 215 Million Individuals White Pages

  9. Universe Database Sources Records that do not qualify for Marketing: -No Solicitation Flagged -Haven’t been verified in the past 24 mos. -Records at the previous address -Deceased people -Rolling 5 years Applications Fraud Prevention Data Append Skip Tracing Modeling Universe File Consumer Marketing Expanded White Pages 80M Households - 124M Individuals 115 M Households - 215 M Individuals 80M Households - 88M Individuals White Pages 350 Million Households - 450 Million Individuals

  10. It’s All About The Sources More than 75 data sources & over 3.5 billion records aggregated annually

  11. Real Estate Data Infogroup continues to expand courthouse access to capture Deed Transfers and Tax Assessor data. • Current Coverage • Deed Transfer - approximately 1,766 Counties in 47 States (85% of population) • Tax Assessor – approximately 3,012 Counties in All States (95% of population) ……Goal: Universal Coverage to Facilitate Segmentation and Modeling Applications

  12. Utility Transaction Data • Infogroup focuses on data freshness and recency, receiving New Connects 3 – 4 days afterconnection occurs. • Types of New Connects • Service Provider Changes • Line Extensions • Reconnects • New Movers • Processing of New Connects • Comparison against Infogroup Consumer Database • Matching of More than 60% as Non-Movers • Identification of Actual New Movers

  13. Monthly Maintenance • Monthly Update Cycle • Over 75 Contributing Sources • Primary Sources – Can Create a Unique Record on Their Own • Secondary Sources – Enhance Existing Records or Create a Unique Record in Combination with another Secondary Source • Models Refreshed • Monthly File Maintenance • Area Code Changes • NCOALinkTM* • LACSLinkTM* • DPVTM* • Do Not Mail / Do Not Call Suppression Files * Infogroup is a Non-exclusive Licensee of the USPS National Change of Address, Locatable Address Coding, and Delivery Point Verification.

  14. Consumer Privacy • Infogroup uses only public or opt-in information to power its consumer databases. • Infogroup is not a credit bureau. We do not accept, maintain, or deliver data specific to credit history or activity. • Infogroup is an active member of the Direct Marketing Association and adheres to all industry guidelines and government laws regarding responsible use and distribution of personal information. • Do Not Call / Do Not Mail • FTC DNC downloaded daily (SAN required) • State DNC as delivered • DMA Mail Preference & Telephone Preference • Deceased Master • Internal Suppression File • Email: Global Suppression File

  15. Infogroup Consumer Database Three Levels of Demographic Data • Individual Level • Household Level • Neighborhood Level

  16. Individual Level Data Details for Household Members • Infogroup Unique Individual ID (IGID) • Identifies Each Household Member • Up to 8 Individuals • Demographics • Date of Birth / Age • Gender • Head of Household Indicator • Marital Status • Spouse Indicator • Ethnicity / Religion / Language • Credit Card Details • Political Affiliation • Lifestyles and Hobbies • Email Address

  17. Cultural Coding Infogroup’s Ethnic Identification Scheme • Identifies an individual’s affiliation with a particular racial or cultural group • Based upon extensive proprietary ethnic research and thousands of linguistic rules • 162 Ethnicities • 16 Ethnic Groups • 80 Language Preferences • 21 Hispanic Countries of Origin • 12 Religions • Based upon First Name, Middle Name, Surname, and Geography • Individual Level

  18. Cultural Coding 5-STEP Match Process • STEP 1: First name match against reference table containing over 70,000 names example: Nguyen O’Brien will be coded as Vietnamese – not Irish. • STEP 2: Where no first name match is found, a table of 470,000 surnames is referenced. • example: John Chen will be coded as Chinese, although English will be the assigned language. • STEP 3: Where no surname match is made, thousands of linguistic rules are applied, including geographical considerations. • example: All surnames ending with the four letters “OGLU” are Turkish. • STEP 4: Middle name is used as tie-breaker. • example: Peter Mei Yu is Chinese, but Peter Hak Yu is Korean. • STEP 5: Final first name pass to determine language spoken. • example: Pablo DeBrito, who has a unique Portuguese last name and a multi-ethnic first name, will be coded as a Portuguese speaker.

  19. Cultural Coding Completeness and Accuracy • Geography - Cultural Coding incorporates United States geographic coordinates at the ZIP+4 level to determine ethnic, religious and language group clusters to further enhance accuracy. • Quality Assurance - In order to measure and maintain the accuracy of Cultural Coding and the algorithms contained within, a national market research company is contracted to conduct quarterly telephone studies. Benefits • Enhanced Understanding of Customers • More Effective Targeted Marketing

  20. Lifestyle Dimensions • Driven by Actions, Transactions, and Survey data • Individual level indicators • Intensity Scores • 9 through 1 represents a positive interest • Recency, Frequency, Monetary Value, Number of Sources (RFM+S) • Used to populate household level equivalents and feed more traditional Y/N indicators already present • Almost 1.5 billion indicators of lifestyle • Across 108 Lifestyle Dimension categories • Golf, Gardening, Travel, Apparel, Automotive, Donors, Books, Internet Behavior, Catalogs, Entertainment, Cooking, Family, etc • Updated Quarterly

  21. Lifestyle Dimensions Created Using Real Data • Direct Mail – Catalog, Fundraising, Memberships • Internet – Web Purchases, E-mail Responses, Online Memberships • Retail – Specialty Stores • Print – Magazine Subscribers and Catalog Buyers • Telemarketing – Surveys, Inbound and Outbound Purchases • Scores are Not Modeled • 9 Highest RFM Intensity • 8 Very High RFM Intensity • 7 High RFM Intensity • . . • . . • General Transactions and Survey Data • 2 Traditional Lifestyle Data • 1 Reported Interest • No Transactions or Survey Responses • 0 No Known Interest

  22. Household Level Data Infogroup Unique Household ID (IGID) • Identifies All Household Members Location Attributes • Phone Numbers • Length of Residence • Dwelling Unit Size • Location Type • Physical Attributes • Latitude / Longitude • Mail Confidence Score Household Data • Number of Adults • Age of Head of Household • Occupation • Presence of Children • Children by Age • Marketing Targets • By age, gender, household size

  23. Household Level Data • Homeowner Data • Homeowner / Renter Indicator • Estimated Home Value • Estimated Home Equity • Mortgage Amount / Mortgage Date • Loan To Value • Income & Affluence Indicators • Estimated Household Income (FIND) • Purchasing Power Indicator (PPI) • WealthFinder • Potential Investors (PIC) • Special Interest Groups • Early Technology Adopters…… Early Internet Adopters • Heavy Internet Users……Internet Savvy Consumers • Credit Card Revolvers……Propensity to Switch • Home Based Businesses……SOHOs

  24. Household Level Data More You Should Know About • Mail Responsiveness • Current (past 2 years) • Recent (3 to 4 years) • Ever (remains “on” through life of HH) • Mail Order Buyers • Dog or Cat Present • Grandparent Present • Veteran Present • Donors • Health • Religious • Environmental • Political • Clustering Systems • PrizmNE (Nielsen Claritas) • Infogroup’s Cluster Spectrum

  25. TargetReady Categorical Models Real-time Marketing Answers in Rapidly Changing Market • Pre-built for Immediate Deployment: No time to wait for custom models • Household Level Targeting: Superior to neighborhood level clustering • Provide “Marketing Answers”: No need for users to plow through sea of data • Extensive Category List: Covers Behavioral & Attitudinal Elements • Simple to Use: 9 means good, 0 means bad • No charge for Model Development: For test friendly pricing

  26. Categorical Models in Action • NASCAR • Luxury Automobile Buyers • Higher Educational Degrees • Pets – Dog or Cat Products • Heavy Pay-per-View – Movies & Sports • Attitudinal Targets • Diet Products • Green • Conservative • Liberal • Leaning Conservative • Leaning Liberal • Opinion Leaders • Shopaholics • Impulse Buyers • And the list goes on… For Everyone in our consumer database: • Banking & Finance • High-value Stock/Security Investors • High Risk/High Return Investors • Low Risk/Low Return Investors • Safety & Security Conscience • Life Insurance (via agents/DM) • Travel • Frequent Business Travelers / Frequent Flyers • Cruisers • Foreign Travel for Vacation • Timeshare Owners • Avid Theme Park Visitors • Baby Products • Health • Diet Products • Organic Foods • Heavy Vitamin & Dietary Supplement Users • Physical Fitness Clubs

  27. Cluster Spectrum Infogroup’s Second Generation Clustering System • Group “like” households together • Household Level Analysis • Intended Benefits • Getting to know your customers • What makes your best customers your best customers • Turning prospects into more ‘best customers’ • Structure for Analyzing • Customer Behaviors • Consumer Preferences • Marketplace Trends

  28. Cluster Spectrum

  29. Cluster Spectrum

  30. Neighborhood Level Data Socio-Economic Status Indicator……SESI • Positions Neighborhoods on the Socio-Economic Continuum (Composite Score 00 – 99) • Income • Education • Occupation • Ownership • Environment Neighborhood Statistics: Aggregate List Statistics……ALS Proprietary Updates Formulated from the Consumer Database • Median Age of Head of Household • Median Income • Median PPI • % Households with Income $100,000+ 2000 => 2010 Census • Income • Age • Household Composition • Employment • Ethnicity

  31. Adding Value 18 additional data sources & more than 6.5 billion records aggregated annually

  32. New Mover Database Each year, nearly 20% of the population moves to a new residence! • 15 million recent moves • 3.1 million phone numbers • Over 1 million moves per month • Weekly feeds available • State/Federal Do Not Call records suppressed Compiled Using • Utility Data (Telephone Connections) • New Homeowner Data (Deed Transfers) • Change of Address Information • Magazine and Credit sources (FCRA Compliant) • Not NCOALinkTM moves Benefits • Speed to Market – received weekly (2-3 weeks from move date) for trigger processing • Quality – 80% have moved within last 90 days. De-duplication, standardization and matching to core file allow for higher approval rates.

  33. New Homeowner Database A subset of the New Movers database Compiled Using • Deeds of Warranty & Trust filed with county recorders • 100% owner-occupied residential properties Monthly and Weekly Feeds • 2 - 3 Million Confirmed Homeowners • 1 Million Probable Homeowners • 50,000 new homeowners weekly • 20% with telephones Selectability • Home Sale Price • Home Sale Date • Estimated Home Value • Interest Rate and Type • Mortgage Loan Amount and Type • Mortgage Lender Type

  34. Key Differentiators C A R • overage • Data aggregated from over 3.5 billon input records annually • 75 contributing sources • Continuing growth through key partnerships • Consistent population of attributes • Compiling all U.S. consumers since 1917 ecency ccuracy • Records added / refreshed 8-10 weeks from book receipt • Daily Utility Connects and Disconnects • Secure aging rules • Postal hygiene • Investment in our proprietary databases • Quality of source files • All white page records are manually keyed • 99.5% accurate at the source level • Addresses Standardized and Scored for “Deliverability” • All models rescored monthly and rebuilt regularly Quality

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