Brad TerrellMarketing in Real Time :     The Technology    & Data Imperative
“Innovation distinguishes between     a leader and a follower”          – Steve Jobs
SEPTEMBER 20, 2010, 9:34 AM ETIBM Buys Netezza for $1.7 Billion                                    3
Data-centric strategies create value
Data is a source of  Uniqueness  Uniqueness    is a source of      Competitive       Advantage
We made it!
Marketing and Data Analysis      are Intertwined
Digital Exhaust   benefits marketers
“75% of CMOs rearranging their teams in 2011to keep pace with the demands of digital media”       – Chris Stutzman, Forres...
“The sexy job in the  next 10 years will be statisticians” –  Hal Varian, Chief Economist, Google 10
A+ playersare hard to find
Extracting insights from exploding data volumes requires new technologies and methodologies
What initiated this trend?
Sampling can be a good thing…                       but not in                   digital marketing!
Throwing out impressionsbreaks attribution analysis
Massively.  Parallel.Computing.
“The company withthe most data wins”   – Tim O’Reilly
It’s not just about big…
Reducing data latencycreates significant marketing value
Real-time marketing is like being in thestands instead of watching it on TV later
Increasing consumer powermeans the stakes are higher
Relevance: because one size   does not fit all
The Data Aggregation Problem
The Segmentation Problem                          High            Age: 18-24           Income: High                       ...
The Matching Problem                                  Target                                 Segment  Your Logo Here      ...
The Bidding Problem                                                   Market X: Price/Volume CurvePrice/Volume Forecast   ...
Brad Terrell: Marketing in Real Time: Technology & Data Imperative
Brad Terrell: Marketing in Real Time: Technology & Data Imperative
Brad Terrell: Marketing in Real Time: Technology & Data Imperative
Brad Terrell: Marketing in Real Time: Technology & Data Imperative
Brad Terrell: Marketing in Real Time: Technology & Data Imperative
Brad Terrell: Marketing in Real Time: Technology & Data Imperative
Brad Terrell: Marketing in Real Time: Technology & Data Imperative
Brad Terrell: Marketing in Real Time: Technology & Data Imperative
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Brad Terrell: Marketing in Real Time: Technology & Data Imperative

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Brad Terrell, VP & General Manager, Digital Media at Netezza: Marketing in Real Time: The Technology & Data Imperative: Keys to creating marketing value opportunities with real-time data.

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Brad Terrell: Marketing in Real Time: Technology & Data Imperative

  1. 1. Brad TerrellMarketing in Real Time : The Technology & Data Imperative
  2. 2. “Innovation distinguishes between a leader and a follower” – Steve Jobs
  3. 3. SEPTEMBER 20, 2010, 9:34 AM ETIBM Buys Netezza for $1.7 Billion 3
  4. 4. Data-centric strategies create value
  5. 5. Data is a source of Uniqueness Uniqueness is a source of Competitive Advantage
  6. 6. We made it!
  7. 7. Marketing and Data Analysis are Intertwined
  8. 8. Digital Exhaust benefits marketers
  9. 9. “75% of CMOs rearranging their teams in 2011to keep pace with the demands of digital media” – Chris Stutzman, Forrester Research
  10. 10. “The sexy job in the next 10 years will be statisticians” – Hal Varian, Chief Economist, Google 10
  11. 11. A+ playersare hard to find
  12. 12. Extracting insights from exploding data volumes requires new technologies and methodologies
  13. 13. What initiated this trend?
  14. 14. Sampling can be a good thing… but not in digital marketing!
  15. 15. Throwing out impressionsbreaks attribution analysis
  16. 16. Massively. Parallel.Computing.
  17. 17. “The company withthe most data wins” – Tim O’Reilly
  18. 18. It’s not just about big…
  19. 19. Reducing data latencycreates significant marketing value
  20. 20. Real-time marketing is like being in thestands instead of watching it on TV later
  21. 21. Increasing consumer powermeans the stakes are higher
  22. 22. Relevance: because one size does not fit all
  23. 23. The Data Aggregation Problem
  24. 24. The Segmentation Problem High Age: 18-24 Income: High Age: 25-35 Recency: Low Income: High Income Recency: High Recency of visits to High YourWebSite.com Age: 50-65Income: LowRecency: Low Age: 36-49 Income: Low High Recency: High
  25. 25. The Matching Problem Target Segment Your Logo Here AwarenessA prominent logo willensure brand recall 2009 Best Product Award ConsiderationShowcase yourcompetitive advantage Free Accessories! Offer Ends Dec 15 IntentOffer incentives forcompleting a purchase
  26. 26. The Bidding Problem Market X: Price/Volume CurvePrice/Volume Forecast 1,200,000Curves Show the Optimal IMPRESSIONS PER DAY 1,000,000Bid in Each Market: 800,000 600,000 400,000max ((R − B) ⋅ N(B)) 200,000 0 0.00 1.00 2.00 3.00 4.00 5.00 R = revenue derived from showing ad CPM Bid B = ad’s bidN(B) = impression volume for bid B as Market X: Profit Curve predicted by P/V Curve 3,500 3,000 2,500 PROFIT 2,000 1,500 1,000 500 0 0.00 1.00 2.00 3.00 4.00 5.00 CPM Bid

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