#ID2013 - Data Silos by @nxfxcom

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Benjamin Spiegel's presentation at #ID2013 (Interactivity Digital) in South Beach on Data Silos in the Digital Age - http://www.youtube.com/watch?v=A0Jop4fsDpc

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#ID2013 - Data Silos by @nxfxcom

  1. 1. #ID2013 DRIVING SEARCH WITH BIG DATA Benjamin Spiegel Director, Search Operations
  2. 2. #ID2013 Who am I? Benjamin Spiegel Director, Search Operations Catalyst Online Twitter: @nxfxcom Email: benjamin.spiegel@groupm.com URL: www.catalystsearchmarketing.com Likes • • • • Search Analytics Data Caffeine Dislikes • • • • PowerPoints Presentations Public speaking Plus…
  3. 3. #ID2013 Data Silos ORGANIC PAID SOCIAL
  4. 4. #ID2013 Data Sources and many more…
  5. 5. #ID2013 API Process 1. Determine the data sources – Translate Business needs into KPIs and determine who has the metrics 2. Build connecters & adapters – Develop automated collection methods to collect the raw data 3. Store and aggregate the data – Choose a flexible storage and aggregation method to manipulate and prepare the data. 4. Visualize & explore with BI Tools – Connect your data to a visualization / BI Tool do filter, segment and analyze.
  6. 6. #ID2013 So What Does That Mean For Me?
  7. 7. #ID2013 Key Phrase Strategy
  8. 8. Organic Rank #ID2013 Current CPC
  9. 9. #ID2013 Lets Dig A Little Deeper And Let’s Size Them By Interest
  10. 10. Organic Rank #ID2013 Current CPC
  11. 11. #ID2013 Okay, How About Coloring Them By Bounce Rate?
  12. 12. Organic Rank #ID2013 Current CPC
  13. 13. #ID2013 How About Incorporating Google Trend Forecast With Icons
  14. 14. Organic Rank #ID2013 Current CPC
  15. 15. Organic Rank #ID2013 Organic Paid Current CPC
  16. 16. #ID2013 CASE STUDY BrandX Wanted Visibility On 50% Of All Results For Primary Keyphrases Currently Visible on 20%
  17. 17. #ID2013 1. We Took ~4000 Key Phrases And Collected The Top 20 Rankings For Each Term Gave Us 67,000 Unique URLs
  18. 18. #ID2013 2. We Then Collected Audience Data For All Keyphrases From Compete, Comscore, And DoubleClick
  19. 19. #ID2013 3. We Analyzed The Sentiment Of All The Discovered URLs
  20. 20. #ID2013 4. Analyzed And Organized Inbound Links By Traffic, Quality, And Authority
  21. 21. #ID2013 5. This Leaves Us With Over 63 Points Of Data Per Domain
  22. 22. #ID2013 6. We Then Filtered The URLs To Remove Sites That • • • • Did not align with the target audience Had low engagement Could not be influenced Have low social or link authority
  23. 23. #ID2013 Visibility (Avg Rank | # Results) 7. This Left Us With Around 170 Highly Engaged & Highly Targeted Sites. Referral pages per Visit
  24. 24. #ID2013 Result Based On All Primary Keyphrases, ~60% Of All Results Contained Brand Mentions For Our Brand.
  25. 25. #ID2013 Thank you! Benjamin Spiegel Director, Search Operations

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