The State of Behavioral Targeting

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    The State of Behavioral Targeting - Presentation Transcript

    1. The Path to One-to-One Marketing: The State of Behavioral Targeting • Tuesday, July 31, 2:30-3:30 PANELISTS: Brent Hieggelke, VP of Strategic Marketing, Omniture Philippe Suchet, General Manager, Kefta/Acxiom Digital Geoff Atkinson, Marketing Chief of Staff, Overstock.com Tim Mahlman, Chief Revenue Officer, BlueLithium MODERATOR: Mary E. Morrison, Contributing Editor, BtoB
    2. Behavioral Targeting: What is it?
      • Observing customer or prospect’s online behavior and using that data to deliver relevant ads or Web site content
      • Identifying data such as: Web sites and pages visited; tools used; time, length, frequency of visit
      • Merging behavioral data with visitor data such as age, gender or ZIP code
    3.  
    4. Behavioral Targeting in the news
      • Google-DoubleClick
      • Yahoo!-Right Media
      • WPP Group-24/7 Real Media
      • Microsoft-aQuantive
      • AOL-Tacoda
    5. BlueLithium + Hyatt Hotels and Resorts Case Study
    6. Hyatt Hotels and Resorts
      • Situation:
      • Hyatt, a leading hotel and resort destination, wanted to increase visits to their resort/spas.
      • Their target resort/spa visitor is a female professional with a family, looking for a quick weekend getaway, usually at the last minute.
        • Different from luxury resort/spa visitors who book in advance, have longer stays and are less price sensitive.
      • Behavioral Targeting was chosen to find this very specific audience segment
    7. Hyatt Hotels and Resorts
      • Audience:
      • Target :
        • 1) Moms
        • 2) Females, ages 25-54
          • For both groups, HHI of $150,00+ and history of researching travel in past 30 days
      • Challenge:
        • Locate this very specific audience, while in market for resort/spa getaway.
        • Decision-making time often two weeks or less.
    8. Hyatt Hotels and Resorts
      • What we did:
        • Started with demographic targeting of Females 25-54 and Mom’s, with high HHI.
        • Overlaid AdPath Audience Targeting (“recent travel research segment”) to create a tight focus.
        • Scaled the segment using Selective Inventory Partnership (SIP).
        • Added AdPath Site Remarketing.
        • In parallel, we tested other audience segments:
          • Found that Female HHI $40K+ outperformed higher HHI, added to campaign to boost performance.
    9. Hyatt Hotels and Resorts Results: BlueLithium beat Hyatt’s targeted cost per customer by 74%
    10. Kefta Dynamic Targeting & Overstock.com Case Study Philippe Suchet - Acxiom Digital, Kefta GM Geoff Atkinson - Overstock.com, Marketing Chief of Staff
    11. Why are we talking about behavioral targeting?
      • Acquisition costs rising and conversion rates decreasing
      • Power switch from marketers to users: Push to pull
      • Key is put customers at the center of your marketing strategy, and move from mass market to behavioral targeting
    12. Key learnings
      • All about targeting and not just behavioral targeting
      • The Google lesson: Art and Science is key to success
      • Experience is far more important than the placement
    13. Overstock.com Case Study
      • Geoff Atkinson, Marketing Chief of Staff
      • Issues we faced:
        • Difficulty in fully realizing customer lifetime value:
          • Complexity of matching customers to constantly changing offers
          • Difficulty in creating an experience that can leverage differences between behavior and attributes of site visitors
      • Solution: Leverage power of behavioral targeting:
        • Provide value to prospects, customers, and bottom line
        • Provide organizational learning to feed back into marketing processes and shape future strategies
        • Provide consistent brand message between key online channels
    14. Overstock.com Case Study Website personalization Unified visitor profile Example programs 1-to-1 triggered email
    15. Overstock.com Case Study
      • Quantitative results
        • Double digit conversion lift for campaign
        • Increased efficiency of acquisition efforts
        •  
      • Qualitative results
        • Visitor centric learning we can apply to other marketing efforts
        • Minimal requirements on internal resources
        • Put power of marketing back into the hands of marketers
    16. On-site Behavioral Targeting Brent Hieggelke VP Strategic Marketing Omniture
    17. Large gap in off-site and on-site spending… Off-site Resources Email marketing Affiliate programs Behavioral Targeting Paid search management Banner advertising Call center referrals Search Engine Optimization Offline marketing to web In-store Web promotion $ $ $ $ $ $ $ $ $ $ $ $ On-site Resources On-site Resources Registration optimization Site testing Web analytics Usability testing Off-site Resources On-site Resources Large Investment Gap
    18. But the on-site engagement determines conversion success Off-site Marketing Spending On-site Experience Determines Conversion Rate Critical Engagement Layer Campaign Traffic Email marketing Affiliate programs Behavioral Targeting Referred Traffic Paid search management Banner advertising Call center referrals Direct Traffic Search Engine Optimization Offline marketing to web In-store Web promotion Campaign Landing Pages Home Page Successful conversion $$$ Conversion Process Product Category Pages Attrition losses Attrition losses
    19. How automated 1 to 1 targeting works: Visitor arrives at your website Visitor Profile Repository Call goes out to Visitor Profile Repository CMS (Serves content) build profile First-time visitor retrieve profile Repeat visitor Self-learning Predictive Modeling Engine Optimal content decision sent to CMS Content library
    20. What data is used to select the relevant offer? Offline Customer Variables Referring domain Campaign ID Affiliate PPC Natural search Search keywords (“loans”) Direct/bookmark Referrer Variables Customer/prospect New/return visitor Online banking login Tools usage Previous Product interests – low level Searches Previous online purchases Previous Campaign exposure Previous Campaign responses Site Behavior Variables IP address Country of origin Time zone Operating system Browser type Screen resolution Environment Variables Temporal Variables Time of day Day of week Recency Frequency Highly predictive anonymous visitor profile
      • On-site Behavioral Targeting was implemented with the specific goal of increasing conversion and sales across products
      • Other reasons:
        • Creative testing and optimization
        • Sales target management
        • Managing homepage politics
        • Real-time reporting
        • Easy to use automated system
        • Excellent customer service
        • Sophisticated targeting system
        • Reports that can prove the uplift in revenue each month
      Lloyds TSB Initial Goals
    21. Profile A
    22. Profile B
    23. Profile C
    24. Profile D
    25.  
    26. Targeting on the secure logoff page
    27. Lloyds TSB Targeting Report
    28. Lloyds TSB Targeting Report
    29. Thanks.
      • Brent Hieggelke
      • [email_address]

    + Marco DerksenMarco Derksen, 3 years ago

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