Rocket Fuel Advertising That Learns How AI Powers Real-Time Decisions
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The document discusses the challenges of big data and machine learning. It notes that with many attributes to segment audiences, the number of possible audience combinations becomes exponentially large, making human decision making at scale impossible. Machine learning can process large amounts of data at high speeds to make targeted decisions in milliseconds. An example is given of a Mars rover that autonomously scans terrain and optimizes decisions every second. The document promotes an artificial intelligence-powered advertising platform that learns from data to improve targeting and outcomes for advertisers.
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Rocket Fuel Advertising That Learns How AI Powers Real-Time Decisions
- 1. ROCKET FUEL ADVERTISING THAT LEARNS OU COMMENT TRAITER LE BIG DATA
- 2. FACE AU DILEMME DU DATA COMBIEN DE DONNEES…TROP DE DONNEES!?
- 3. LA COMPLEXITE DU BIG DATA PROBLEME: EXPLOSION COMBINATOIRE DE DONNEES # Attribute Segments 2 Genders 2 x # Attribute Segments 2 Genders 2 x 16 Household incomes 32 x # Attribute Segments 2 Genders 2 x 16 Household incomes 32 x 18 Age buckets 576 x # Attribute Segments 2 Genders 2 x 16 Household incomes 32 x 18 Age buckets 576 x 42 Psychographic profiles 24,192 x # Attribute Segments 2 Genders 2 x 16 Household incomes 32 x 18 Age buckets 576 x 42 Psychographic profiles 24,192 x 94 Lifestyle profiles 2,274,048 x # Attribute Segments 2 Genders 2 x 16 Household incomes 32 x 18 Age buckets 576 x 42 Psychographic profiles 24,192 x 94 Lifestyle profiles 2,274,048 x 225 Bizographic profiles 511,660,800 x # Attribute Segments 2 Genders 2 x 16 Household incomes 32 x 18 Age buckets 576 x 42 Psychographic profiles 24,192 x 94 Lifestyle profiles 2,274,048 x 225 Bizographic profiles 511,660,800 x 1,055 Interest categories 539,802,144,000x # Attribute Segments 2 Genders 2 x 16 Household incomes 32 x 18 Age buckets 576 x 42 Psychographic profiles 24,192 x 94 Lifestyle profiles 2,274,048 x 225 Bizographic profiles 511,660,800 x 1,055 Interest categories 539,802,144,000x 10,425 In-market intents 5,627,437,351,200,000x # Attributs Segments 2 Genre 2 x 16 Revenu du Ménage 32 x 18 Tranches d’âge 576 x 42 Centres d’Intérêt 24,192 x 94 Mode de Vie 2,274,048 x 225 Professions 511,660,800 x 1,055 Comportement d’achat 539,802,144,000x 10,425 Intention d’achat 5,627,437,351,200,000x 43,000 Geographie 6,241,979,806,101,600,000,000x # Attributs Segments 2 Genre 2 x 16 Revenu du Ménage 32 x 18 Tranches d’âge 576 x 42 Centres d’Intérêt 24,192 x 94 Mode de Vie 2,274,048 x 225 Professions 511,660,800 x 1,055 Comportement d’achat 539,802,144,000x 10,425 Intention d’achat 5,627,437,351,200,000x 43,000 Geographie 6,241,979,806,101,600,000,000x +++ 20’000 autres Combinatorial Explosion!
- 4. S’IL FAUT 10 SEC A CHAQUE PERSONNE POUR PRENDRE UNE DECISION CELA PRENDRAIT 119,764,735,724,180,000,000 DE VIES POUR PRENDRE LA BONNE DECISION DECISIONS A GRANDE ECHELLE PROBLEME: IL Y A 504,216,244,224,000,000,000,000,000 DE COMBINAISONS POSSIBLES
- 5. PROBLEME: 500,000 DECISIONS DOIVENT ETRE PRISES CHAQUE SECONDE VITESSE DE PRISE DE DECISION La technologie de l’I.A assure une vitesse et une efficacité maximales
- 6. AVEC OU CONTRE LA MACHINE?
- 7. IA + BIG DATA
- 9. Reçoit des info générales Scanne le paysage martien de manière autonomne Rapporte les résultats Optimise toute les secondes Travaille 24/7 RENCONTREZ LE MARS ROVER
- 10. Reçoit des info générales Scanne le paysage du Big Data de manière autonomne Rapporte les résultats Optimise toute les secondes Travaille 24/7 ET LE PROSPECT ROVER
- 11. 6M D’HUMAINS
- 12. 1/4th of a second 81,018 decisions RTB = TARGETING DECISIONS IN MILLISECONDS
- 13. L’INTELLIGENCE ARTIFICIELLE EN MARCHE… Age/Gender Occupation IncomeEthnicity Purchase Intent Online Purchases Offline Purchases Browsing Behavior Site Actions Zip CodeCity/DMA Search Sites Search Categories Recency Search Keywords Web Site/Page Referral URL Site Category Bizographics Social Interests Lifestyle Positive Lift Marginal Impact Negative Lift x + - -7 +17 X -2 +8 +14 X -9 -13 -12 X +19 +13 +11 X +11 X X X +25 +6 X -7 +17 -2 +28 X +11 X X -9 +14 +17 +19 +8 +11 X X -9 +17 -23 +6 X +17 -7 X -2 -13 -12 X +13 +6 +11 X X X -9 X +17 X +19 +8 +14 +18 -23 +17 -12 +11 -9 +8 +14 X +11 -13 -12 +13 +11 X X -7 +17 +8 +18X +11 X -12-10 +6 +14 X +8 +11 -10+13 +28 +6 +13 +19 X +8 +11 -10 +13 -12 +17 X -7 +8 X 60 LEARNING MODELS
- 14. ANALYSE PREDICTIVE Opportunité d’enchère Score: +164 -13 +14 -142 +153 +124 -12 +90
- 15. STATISTIQUES A L’APPUI COMPTEZ SUR VOTRE TABLEAU DE BORD POUR TOUT SAVOIR!
- 17. PARTENAIRE DE CONFIANCE LE TOP DES ANNONCEURS TRAVEL NOUS FONT CONFIANCE
- 18. OBJECTIVE » Drive bookings and revenue for Lufthansa » Drive traffic to website RESULTS » Drove CPA down by 50% » Increased conversions 11% above goal TRAVEL SUCCESS STORY: LUFTHANSA 50%DECREASE IN CPA 11%ABOVE GOAL Rocket Fuel has been a top performer in online ticket sales. Their results are so impressive that we’ve increased our budget with them each quarter. ” “ - Craig Koestler Account Supervisor, Mindshare
- 19. MERCI! De Votre Attention In the press Rocket Fuel named among America’s Most Promising Companies New at RocketFuel.com Whitepaper: Top 10 Questions About Programmatic Buying Download it here. (http://bit.ly/UBDYSl) The annual Forbes list saw Rocket Fuel move to No. 4, up from No. 22 in the 2012 rankings. Read more. (onforb.es/UYdmLH) 192% ROIPOUR LES ANNONCEURS (229% POUR LES AGENCES) Based on 3 year campaign Impact, Measuring the Total Economic Impact of Rocket Fuel, March 2013 Eric Clemenceau, MD France Just ask for: Additionnelles Success Stories Clarification sur notre unique méthodologie
Editor's Notes
- 1E+12 = 1 Trillion2.2E+12= 2.2 Trillion2.8E+14 = 280 Trillion3.5E+15 = 3.5 Quadrillion$280 Triilion US debt
- Technologiespecialementconcue pour exploiter et maitriser le big data et simplifier la complexite du marketing.
- The world developed algorithms that could learn and improve. Computers started wiping the floor with chess grandmasters…
- Development – example of Kasparov vs Deep Blue (image attached and article re this here http://www.nytimes.com/1996/02/18/us/it-s-man-over-machine-as-chess-champion-beats-computer-he-calls-tough-opponent.html) Why was this surprising? It’s like putting a marathon runner against a carhttp://www.telegraph.co.uk/news/matt/9885264/From-the-archive-Chess-computer-beats-Kasparov-in-19-moves.htmlBy Malcolm Pein, Chess Correspondent, New York12:13PM BST 12 May 1997
- - This is the Mars Rover. Rocket Fuel’s founder, George John, gained his PhD in artificial intelligence while writing the software for this robot.- Mars Rover is designed to scale the harsh Martian landscape by itself and look for water.- It can follow general instructions, but it takes 14 minutes for these to arrive.- So it needs a lot of intelligence to deal with rocks, ruptures and ravines on its own.
- - Several generations later, the technology team at Rocket Fuel built what you could call a prospect rover.- It is designed to scale the harsh data landscape by itself and look for conversions.- It could follow general instructions from the advertiser but these take weeks to arrive.That's why it has the intelligence to take most decisions itself in milliseconds.It never tires, works 24h a day, never goes to the bathroom and keeps getting smarter.
- - So smart, in fact, that it can now take as many decisions as 6M people.- With this capacity, prospect rover can take a systematic and scientific approach to make campaigns successful.
- The difference is like finding treasure buried in a desert.- Most of us would rely on a treasure map, and start digging “near the dead tree”. And they would probably find some treasure, so they would keep digging, making the hole larger and larger so that maybe they will find “lookalike” treasures.- Or do you take an army of metal detectors, scan the entire desert, and go digging at all places where you find something simultaneously?
- - The second revolutionary aspect of programmatic buying is Real-Time Bidding.- In the blink of an eye, about a quarter of a second, we make 81,018 decisions on how much to bid for which impression on which site for which advertiser- That translates into 28 billion biddable impressions per day
- And AI learns on its own, every 15 minutes
- It’s not just about the impression opportunities that are being evaluated now. Our platform is also conscious of what’s ahead.This means that even if an opportunity falls within a positive range for propensity, Rocket Fuel will project the quality of opportunities down the road before deciding how to best use your client’s budget.
- Rocket Fuel has built a technology platform, and a team around it, to tackle these problems head on. We’ve put these principles in motion to create what we call “Advertising that Learns.” Advertising That Learns takes Big Data and Artificial Intelligence, and uses them together to identify [click] moments of influence. Moments of influence drive true impact for advertisers.And it’s not just us saying that. [click] The independent market insights firm Forrester Research has studied the whole landscape, looked at lots of the DSPs and networks in terms of the value they provide. When they looked at the ROI of working with Rocket Fuel for a study we commissioned, they found 229%. That beat other DSPs by 60% over the same time period, and ad networks by 140%.