Data-Mining Social                   Audiences to Impact a                   Brand’s Marketing Mix                   Matt ...
Social Media and Data: Biggest Problems for CMOs    Brands see shifting user demographics and need to use social data - an...
Social Media + Analytics: CMOs to Increase Spend!    Chief Marketing Officers of the world’s largest companies globally ha...
Facebook Targeting: The Big Picture        US Facebook audience           addressable by:   Gender            99%   Age   ...
Facebook Targeting: Some Highlights        • Younger people are more addressable than older people:           • A 14 year-...
Likes & Interests: Age Distribution        Young people are much easier to address with keywords than older people        ...
Likes & Interests: Reach Distribution        Few keywords have very large audiences, and many keywords have small audience...
Data = The Currency of Advertising and Attention         We are the first company to bring together rich data from both so...
SocialPredict Provides a Unique Data Foundation         XA.net uses 3+ years of historical social graph data to make audie...
Optim.al: Proprietary Audience Segmentation                                Gardening          Gardening     Automated Sugg...
Facebook: Keyword Selection Process        1. Translate an AdWords list from purchase intent to people               a.   ...
Facebook: Keyword Selection Process – Proof               Targeting Method              CTR                Conversion Rate...
Our Proprietary Data: A Visual Social Graph               http://optim.al/blog/ConfidentialConfidential
What Does All This Mean to a Brand?        Data drives their Strategy and Execution, both Online and Offline              ...
Data-Mining Social                   Audiences to Impact a                   Brand’s Marketing Mix                   Matt ...
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Matt Esslinger Presentation

  1. 1. Data-Mining Social Audiences to Impact a Brand’s Marketing Mix Matt Esslinger, COO of XA.net (matt@xa.net) October 21, 2011 ConfidentialConfidential
  2. 2. Social Media and Data: Biggest Problems for CMOs Brands see shifting user demographics and need to use social data - and take user feedback into account earlier - in the market planning and product processes Source: IBM Global Chief Marketing Officer Study (n=1,734)ConfidentialConfidential
  3. 3. Social Media + Analytics: CMOs to Increase Spend! Chief Marketing Officers of the world’s largest companies globally have been taken by surprise by the explosion in consumer data and the transformative potential of social media – and need technology to address it % of CMOs reporting under preparedness Plans to increase the use of technology Source: IBM Global Chief Marketing Officer Study (n=1,734), Oct 2011ConfidentialConfidential
  4. 4. Facebook Targeting: The Big Picture US Facebook audience addressable by: Gender 99% Age 95% Status 63% Education 36% Workplace 6%ConfidentialConfidential
  5. 5. Facebook Targeting: Some Highlights • Younger people are more addressable than older people: • A 14 year-old is twice as likely as a 45 year-old to like something on Facebook • Women are more addressable than men: • 19% more likely to share interests; 13% more likely to be married; 6% more likely to be engaged • Exception: men are 12% more likely to list as single • Addressable data is sticky, and sticky across types: • Users who like any single keyword overindex for 94% of all other keywords • Users who list a workplace overindex for 92 % of all keywords • Users who list a workplace are 24% more likely to share a relationship statusConfidentialConfidential
  6. 6. Likes & Interests: Age Distribution Young people are much easier to address with keywords than older people Interest Addressability Index by Age 200 150 100 50 - 13 18 23 28 33 38 43 48 53 58 63 AgeConfidentialConfidential
  7. 7. Likes & Interests: Reach Distribution Few keywords have very large audiences, and many keywords have small audiences Keyword Count by Audience Size (log-log) 100,000 10,000 Mid-Tail 1,000 100 Popular 10 1 1,000 10,000 100,000 1,000,000 10,000,000 Audience SizeConfidentialConfidential
  8. 8. Data = The Currency of Advertising and Attention We are the first company to bring together rich data from both social media (ads, apps etc.) + real-time display sources and give marketers a way to take immediate action to reach those users with the optimal message Advertiser targeting 3rd party Interest/demographics 25-34 Female Proprietary Audience Response Database Portland 25-34 Female Portland Social Predict TM Strollers Hyperlocal data Ad targets + category intentConfidentialConfidential
  9. 9. SocialPredict Provides a Unique Data Foundation XA.net uses 3+ years of historical social graph data to make audience predictions Content-Specific Metadata …creates structure among… 650,000+ Targetable Interests …of users organized into… 300,000 Networks …providing a view into… SocialPredict …which has 370 million unique edges and is growing every day…Confidential
  10. 10. Optim.al: Proprietary Audience Segmentation Gardening Gardening Automated Suggestions garden olive garden Data from millions of plants olive garden bread sticks optim.al vs. Facebook landscaping plants antiques bread sewing home improvement bird watching gardener audience profiles Swimming Swimming Proprietary Facebook lifeguards swimming pool water polo olympic swimming tanning lifeguarding diving tubing hot tubs hot pools water polo triathalon datasets combined with More. Chess scrabble Chess nil external data: Relevant. backgammon monopoly Targeting. Company Lists ping pong mathematics card games Musician Musician Likes & Interests recording Anthony Hamilton performing guitarist Saul Williams Neo-Soul Schools & Majors drummer producer Semantic Scrapes songwriter Ayn Rand Ayn Rand Atlas Shrugged Atlas Shrugged The Fountainhead Anthem Libertarian Objectivism George OrwellConfidentialConfidential
  11. 11. Facebook: Keyword Selection Process 1. Translate an AdWords list from purchase intent to people a. NLP: tokenization and stemming to facilitate Facebook keyword discovery “realtor”  “realtor marketer”, “national association realtors”… b. Categorical Expansion: amplify with vertical keywords “Bloomberg”  “CNBC”, “Motley Fool”, “Yahoo Finance”… c. Audience Suggestion: add highest indexing keywords among a core user base “Barack Obama”  “The Daily Show”, “NPR”, “Coffee” 2. Filter the keyword list, based on stated reach and CPC objectives 3. Slice into minimally overlapping segments and create a controlled environment for testing and optimizationConfidentialConfidential
  12. 12. Facebook: Keyword Selection Process – Proof Targeting Method CTR Conversion Rate CPA Facebook Broad Category: Small Business Owners .015% 3.9% $28.65 Search Keyword-Driven (Intent+Behavior) Precise Interests .033% 11.6% $10.71 1. Broad Category Targeting (BCT) does not pass the smell test • BCT identifies165,000 Small Business Owners under the age of 17 2. Only Precise Interest Targeting allows for deep relevance and segmentation 3. Search keywords (properly translated) can identify highly-qualified, precisely target-able audience segmentsConfidentialConfidential
  13. 13. Our Proprietary Data: A Visual Social Graph http://optim.al/blog/ConfidentialConfidential
  14. 14. What Does All This Mean to a Brand? Data drives their Strategy and Execution, both Online and Offline A luxury auto brand learned that most category fans are young + aspirational & Online not likely buyers, but they also found the Strategy loyal owner segment within their base Analyzed millions of US fans to discover interest-based clusters of underserved Offline consumers by ZIP Code. These deep and Strategy surprising insights were revolutionaryConfidentialConfidential
  15. 15. Data-Mining Social Audiences to Impact a Brand’s Marketing Mix Matt Esslinger, COO of XA.net (matt@xa.net) October 21, 2011 ConfidentialConfidential

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