How to Successfully apply Data & AI in the Marketing Value Chain. August 30th 2018

Transcription

1 How to Successfully apply Data & AI in the Marketing Value Chain August 30th 2018

2 Suzanne Jansen Head Data & Analytics Benelux Global Practice Lead Analytics

3 Do you know?...the percentage of data that was created in the last 2 years?

4 90% of the world s data was created in the last 2 years

5 Do you know? What % of marketing organizations are implementing or expanding AI & machine learning in 2018? *According to Forrester research in Survey among 150 Martech professionals in the US.

6 84% Marketers have reached a point where their ability to capture data has exceeded their ability to take data-driven action They are confident that AI enhances human decisions and insights. Source: Forrester Research 2017

7 Do you know?...the amount of customer care interactions that will be managed by AI in 2020?* *as predicted by Gartner

8 88% Source: Gartner of customer care interactions will be managed by AI in 2020*

9 Data & AI The future is here 9

10 Vast amounts of data are being produced and processed every minute. 142M 1 MINUTE 50K $203K s App Downloads 347K 2.4M 1.3K Tweets Searches Uber rides Amazon sales Half a trillion digital moments across devices processed by Google Analytics each day 10

11 Accelerated growth of data production. We are here! Skyrocketing quantity of data: birth of data science 90% of the data available in the world has been generated between 2016 and 2018 information / volume 12 times the distance between planet earth and the sun if we stock all the data in book format Each person produces around 250 Gb Invention of Printing London library ( books) First even known written document 3000 BC Internet advent today time

12 Accelerated growth of science & technology.

13 Computing power + machine learning + data skyrocket innovation in marketing. Data is the Fuel AI Machine Learning algorithms are the engines

14 The big tech giants are leading the way in using data to drive full marketing automation. Automated media mix optimization Automated orchestration Attribution analysis Manual reporting Manual orchestration Automated single channel reporting Customer journey reconciliation

15 What is AI? The creation of computer programs (machines) that can (out)perform tasks that are currently completed more satisfactorily by humans Strong AI Weak AI

16 What is strong AI? A machine that can do everything a human can, including being self-aware Turing Test Timeline: 30 to 1000 years

17 What is weak AI? Intelligent programs developed for specific applications that either do or don't reproduce human intelligence 26/11/2016 That's the focus today

18 Todays examples of AI applications. Personal assistants Self-driving cars Natural language processing and use of web resources With Tesla taking the lead, they include all AI bricks Siri 2011 Now 2012 Cortana 2014 Alexa 2015 M 2016 Assistant 2016 Bixby 2017 Sensing: The camera turns video into objects and places Planning: I have to go from A to B via the best route Learning: I learn to manage any situation via millions of hours of driving Knowing & Reasoning: Moral driving rules Augmenting humans Off-the-shelf AI for a wide range of industries: Khresterion: Real-time voice analysis tech Watson: Can help with medical diagnoses Sentient Ascend: Tech to optimize the UX of e-commerce sites

19 Map of AI. AI Learning Learning from a set of examples, growing over time Supervised Unsupervised Reinforcement Sensing Processing signals from the outside world Learns to recognize spam in an inbox Planning Moving in an environment to attain a goal Computer Vision Speech recognition Natural Language Processing Feature construction Camera of driverless car a Monte-Carlo Tree Search Markov decision process* Genetic algorithms... The robot must go charge itself then leave home Knowing & Reasoning Deducing facts from other facts, rules, connections Rule-based engine Expert systems Ontologies. I can prove a mathematical theorem from axioms * Stochastic model used to study optimization problems using dynamic programming or reinforcement learning algorithms

20 What is currently possible, and what isn t (yet)? What AI can do... Input Challenge Are there any human faces (0/1)? Who s on there? Will they pay back the loan (0/1)? What is that sound? Who s talking? What s the position of other vehicles and objects? Will it crash? What AI can't do... Output In the years ahead, specialists will keep striving to let AI perform tasks that the human brain currently processes in a second.

21 We ve built AI solutions in order to inspire and free up time for customers and marketers, removing errors and repetitive tasks. Our AI roadmap Automated reporting Omni-channel & cross-device customer vision Siloed channels & devices customer vision Automated orchestration Marketing as an API Media AI decision making process AI-based content production

22 Short Break

23 Where to apply Data & AI in digital marketing? 23

24 Your challenge: What tasks are appropriate to automate and optimize with AI? 522 hours per year lost on repetitive tasks* 522 DUMB WORK hours per year Manual and time-consuming lost tasks on repetitive can disappear thanks tasks to AI * *DJS Research 2017 GUESS WORK AI can confirm or deny human intuition in the prediction of the optimal customer dialogue / journey

25 Thanks to AI, marketing departments can concentrate on higher value-added work: strategy and creativity

26 Tomorrow CMOs will formulate strategic and creative hypotheses and machines will do the rest of the job: it is our marketing as an API vision

27 Where to apply data & AI for marketing as an API? WHO - Audience segmentation Segment audiences based on: Behavioral / relational likeness Buying propensity Churn propensity Interest or channel affinity Lead scores (engagement / conversion)

28 Where to apply data & AI for marketing as an API? WHAT - Message / content / offer optimization Activate message, content and offer based on: Dynamic creative optimization Dynamic content creation Recommendation engine

29 Where to apply data & AI for marketing as an API? WHEN/WHERE - Channel optimization Reallocate and activate budget based on: Conversion attribution Budget allocation and distribution Reception recognition (offline impact) Brand perception Voice search / Personal assistants

30 Applications of AI & machine learning in the customer journey. REACH ACT CONVERT ENGAGE Customer Interactions and Value Who? What? Lead Scoring Where? Ad Targeting AI Generated Content Smart Content Curation Chat Bots Re-targeting Programmatic Media Bidding Voice Search Web & App Personalisation Predictive customer Service 1:1 Dynamic content s Dynamic Pricing Marketing Automation Predictive Analytics Repeat Customer Propensity Modeling 1st Purchase Demand generation and purchase intent Lapsed Customer Indecisive Customer Time Loyal Customer

31 Data & AI in the Marketing Value Chain 31

32 The marketing value chain is composed of repetitive tasks that are prone to error. Plan. Identify the best audiences to target Find the best budget allocation Setup. Ad creation Ad trafficking Consistent campaign tagging Control. Tracking consistency Data verification Data (PII) leakage Error tracking (payment, 404) Optimize. Attribute value across channels & reallocate budgets Optimize for the best audiences, creative, content & offer Automated reporting

33 Common challenges in the planning phase. Plan. Setup. Control. Identifying the best target audience Finding the best budget allocation and distribution Optimize.

34 We have automated audience clustering combined with creative optimization. USE STATISTICS & CROSS PLATFORM DATA TO FIND THE MOST RELEVANT CLUSTERS CREATIVE ASSETS PRODUCTION BASED ON AFFINITY INSIGHTS ACTIVATE THE BEST SEGMENTS WITH THE BEST MESSAGES RESULTS Conversions ROI Reach x2 x2,3 x1,4

35 We seek for patterns amongst convertors'.

36 How did we do it: Audience Builder

37 Common challenges in the setup phase. Plan. Setup. Control. Ad creation Ad trafficking Consistent campaign tagging Optimize.

38 Tasks performed by an Ad Trafficker in DoubleClick. Create a campaign Create placements Upload creative Create ads Download tags Verify impressions Time-consuming Manual Error-prone

39 Solution: Trafficking 2.0 A stand-alone interface

40 Trafficking 2.0: 3 steps to reduce complexity Automate 98% of your campaigns. 1 Turn media plans into campaigns Media plan is ingested and processed by our algorithm into a traffic sheet 2 Detect errors that impact performance Errors are automatically detected and detailed within the interface 3 Traffic campaigns at scale Automatic campaign setup: the algorithm creates ads and their backups. FASTER RELIABLE USER-FRIENDLY Automatically launch campaigns within minutes, in a few clicks Easily prevent human mistakes 1 easy-to-use interface

41 Common challenges in the Control phase. Plan. Setup. Control. Optimize. Tracking consistency Data verification Data (PII) leakage Error tracking (payment, 404)

42 PowerScan: validate quality of tag implementation through actionable reports. Automate tags verification at scale 1 SCAN ALL URLS ON YOUR WEBSITE Automatically scans thousand of URLs 2 DETECT TAG ERRORS Detect wrongly implemented tags and variable labels and values 3 GET A FULL REPORTING AND TAKE REQUIRED ACTIONS Detailed reporting with actionable insights: Errors: no call, wrong variable label, wrong value Cause: technical or analytics Evaluate and refine

43 Common challenges in the Optimize phase. Plan. Setup. Control. Optimize. Attribute value across channels & reallocate budgets Optimize for the best Audiences, Creative, Content & Offer Automated reporting

44 The creative optimization process. BEFORE 1 Demand is sent to the agency 2 The agency writes a new scenario 3 Preview link is sent to the client 4 Validation of the scenario by the client 5 The new scenario is activated 8 s 2 calls 3 days of process & work 3 mobilized resources

45 A creative editor facilitates manual testing of different scenarios. AFTER 1 person 1 hour

46 Intuition is being compared to historical performance and machine learning algorithm.

47 MyDCO: Manual and automated testing compared. 3 different creative recommendations to see what works best. 1 Easily test creative scenarios based on experience & intuition With no dependency on creative agency 2 A/B test with historical campaign data Test all different creative elements to find the best one: different images, call to actions, USPs etc. 3 Compare it with the algorithm Try the 3 different methods and see what works best based on past en predictive future performance

48 At Artefact, we have built a suite of AI-based products OUR PROPRIETARY TECHNOLOGY IS AT THE HEART OF OUR DAILY DECISIONS Plan Setup Control Optimize Audience Builder SEAds Generator PII Tracking Octopus Media Plan Recommendation URL Builder URL Checker SEA Optimization Trafficking 2.0 Activation SEA/SEO Synergies PowerScan SEA exclusion/targeting Display Optimization MyDCO Automated Reportings Infrastructure DPP Artefact Ingestion Tool

49 By automating tasks in all these phases... Plan. Identify the best audiences to target Find the best budget allocation Setup. Ad creation Ad trafficking Consistent campaign tagging Control. Tracking consistency Data verification Data (PII) leakage Error tracking (payment, 404) Optimize. Attribute value across channels & reallocate budgets Optimize for the best audiences, creative, content & offer Automated reporting

50 ...we gain time to re-focus on Data-Driven Strategy & Creativity 50

51 Thanks for your attention