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Artificial Intelligence & Marketing - ULB Solvay Executive Master in Digital Marketing - 16 11 2017

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Lecture about Artificial Intelligence & Marketing by Hugues Rey & Hugues Bersini
16/11/2017
Examples & Cases
Part of the 17 days program of Education: Executive Master in Digital Marketing & Communication - ULB - Solvay Brussels School of Economics

Published in: Marketing
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Artificial Intelligence & Marketing - ULB Solvay Executive Master in Digital Marketing - 16 11 2017

  1. 1. A.I. & THE FUTURE OF MARKETING EXECUTIVE MASTER IN DIGITAL MARKETING 2017 – 2018 BRUSSELS – 16TH OF NOVEMBER 2017
  2. 2. Hugues Rey Ø1968 – Ixelles – Married to Geneviève ØSolvay Business School (1992) ØCEO Havas Media Group BeLux (2010) Ø+25 years of experience in communication agencies (WPP, IPG, Havas) ØActive in digital marketing since 1996 ØFounding Father of Interactive Advertising Bureau (IAB) (1998) ØCIM: President Strategy (2016 - …), Past-President Internet (2000-2011), TV (2012 -2013) ØTeach Marketing at Solvay Brussels School: Digital, International Marketing and Integrated Communication ØActive Blogger : I’am A Bridge – www.huguesrey.com Ø@huguesrey
  3. 3. Hugues Bersini Professor in Université Libre de Bruxelles and Co-Director of the IRIDIA laboratory. Teacher Artificial Intelligence, Object-Oriented technologies (UML, Design Patterns, Java, .Net, ...) and Web Programming (Django/Python) both for academics and for entreprises. Member of the Belgium Royal Academy of Science Main research interests are modelling and control of complex systems, neural networks and fuzzy control, data/graph/text mining, autonomous agents and dynamics of biological networks, computational chemistry, immune engineering, cognitive sciences, bioinformatics and object- oriented technology.
  4. 4. Agenda of today 1. Why Marketing needs Innovation ? 2. Artificial Intelligence Concepts & Principles 3. A.I. and Marketing: Let’s Maximize the consumer experience ! 4. Technical Approach and Solutions 5. What’s Next ? Ethical point of view 6. Will A.I. steel my Marketeer Job ? 7. How A.I. could empower each stage of the consumer decision journey ? 8. Conclusions Wrap Up
  5. 5. Marketing Professional Challenges
  6. 6. Why Marketing needs A.I. ? Real Time Ultra Large Scale Complexity
  7. 7. Complexity Marketing Channels Multiplication
  8. 8. Complexity – Frangmented Consumer Journey
  9. 9. Complexity - Data (Volume /Source)
  10. 10. Complexity Fragmentation of the technology stack
  11. 11. Real Time is the new norm
  12. 12. Digital impact the whole Marketing Process
  13. 13. Hyper Personalization vs Ultra Large Scale
  14. 14. EXAMPLE OF MARKETING EVOLUTION
  15. 15. What Consumers Really Think about AI ? (6000 interviews by Pega)
  16. 16. 1.Marketing meets Technical Innovation GARTNER CURVE
  17. 17. Le Soir 16/11/2017
  18. 18. Mapping Technologies Through the Gartner Curve Gartner Hype Cycles are a graphic representation of "the maturity and adoption of technologies and applications, and how they are potentially relevant to solving real business problems and exploiting new opportunities"
  19. 19. 5 Phases Innovation Trigger: A potential technology breakthrough kicks things off. Early proof-of-concept stories and media interest trigger significant publicity. Often no usable products exist and commercial viability is unproven. Peak of Inflated Expectations: Early publicity produces a number of success stories — often accompanied by scores of failures. Some companies take action; many do not. Trough of Disillusionment: Interest wanes as experiments and implementations fail to deliver. Producers of the technology shake out or fail. Investments continue only if the surviving providers improve their products to the satisfaction of early adopters. Slope of Enlightenment: More instances of how the technology can benefit the enterprise start to crystallize and become more widely understood. Second- and third-generation products appear from technology providers. More enterprises fund pilots; conservative companies remain cautious. Plateau of Productivity: Mainstream adoption starts to take off. Criteria for assessing provider viability are more clearly defined. The technology's broad market applicability and relevance are clearly paying off.
  20. 20. Cloud Computing Exemple
  21. 21. 3 Trends A.I. Everywhere Transparently Immersive Experience Digital Plateforms
  22. 22. AI will impact all industries Consumer & Marketing are the most impacted today & in 5 years
  23. 23. 1. Transformational technologies require exploration — and patience 2. AI invades marketing 3. Marketers take control of data to enhance experiences 4. Martech and adtech: An open relationship 5. Brand safety a top digital advertising priority
  24. 24. 1. Transformational technologies require exploration — and patience Real-time marketing, AI for marketing and customer journey analytics will bring more power and adaptability to help marketers effectively engage with prospects and customers. Although these three technologies are transformative and still in the Innovation Trigger phase, they will take 10 or more years to mature. The next decade will require a sense of exploration and experimentation. Action items: AI for marketing: Start learning about AI now and engage directly with your vendors to understand the role AI currently plays.
  25. 25. 2. AI invades marketing AI for marketing comprises systems that change behaviors without being explicitly programmed based on data collected, usage analysis and other observations, and includes enabling technologies such as machine learning, deep learning and natural-language processing. AI-enabled technologies and techniques have the potential to transform the practice of marketing as we know it. AI for marketing is in the Innovation Trigger phase, and vendors liberally promote “intelligent” capabilities within their offerings with varying degrees of precision and truth. Action items: AI for marketing: Be wary of lofty claims of AI-powered marketing. Establish test criteria and conduct pilots and proofs of concept to vet such assertions.
  26. 26. 3. A.I. Integration in Marketing Practices LET’S MAXIMIZE THE CONSUMER EXPERIENCE
  27. 27. 1. Chatbots (text / voice) 2. Recommendations / Content curation 3. Personalized pricing 4. Ad targeting 5. Computer vision 6. Speech recognition 7. Data analysis 8. Content Generation 9. Search 10. Business Forecasting 10 Major Trends of A.I. Usage in Marketing
  28. 28. 3.A. Marketing Data Available is Growing
  29. 29. 38 $$$ Advanced TV Online Video Display Search Social Digital OOH Landing Experiences Direct Channels Consumers Merchants Drive Awareness Retailer Distribution CROSS-CHANNEL MEDIA EFFECTIVENESS Social Signals Business data, e.g. orders, registrations, revenue etc. Other open & proprietary data: government incentives, market forecast, surveys… Web / Mobile site Search intent Real-Time Buying Teams Data Management Platform Where? (Media) Who? (Audience) Frequency Management Verification Delivery Audit Creative Segmentation Modeling Forecasting Profiles Day part Media Channel MEDIA INTELLIGENCE PLATFORM DATA RESULTSACTIVATIONAUDIENCE Offline MediaAudience data 1st party (client data) 2nd party (partner data) 3rd party (observed data, Experian, Acxiom, IXI…) Web / Mobile site SMART ONGOING EXPERIMENTATION & TESTING DMP Programmatic Desks Multiple Source of Data IOT Other Unstructured Data
  30. 30. 3.B. A.I. Ingredients for Marketing
  31. 31. 3.B.1 – (Chat)Bots & Robots
  32. 32. Research from Forrester showed 5% of companies worldwide said they were using chatbots regularly in 2016, 20% were piloting them, and 32% were planning to use or test them in 2017. Research from Gartner has predicted that 85% of customer service interaction will be done by means of artificial intelligence by 2020.
  33. 33. 28.2 trillion mobile messages are expected to be sent in 2017. This number is about double the amount of messages sent in 2012. The open rate for mobile messages is a near perfect 98%, which is exponentially higher than the 22 percent rate emails employ. 6 of the top apps used globally are messaging apps. Retention rate of messaging apps is about double the amount of other types of apps.
  34. 34. Bots to Create Seamless User Experience Uber Facebook Bot
  35. 35. Bots to Create Seamless User Experience HP Print Bot
  36. 36. Bots as Customer Support The deep learning AI chatbots possess allow them to access layers of data from neural networks, including customer information that has been built up over time. Real-time access to a customer’s preferences and purchase history gives customer support chatbots a significant edge over their human counterparts. A great example of this can be found in the hospitality industry with the Hyatt chatbot. As a branded Facebook Messenger bot, Hyatt customers can get up to date information in seconds.
  37. 37. Bots to help in the Sales Process H&M
  38. 38. Recommendation Having trouble finding your next read? Harper Collins' Epic Reads chatbot is here to help
  39. 39. Bots to Process Payments Capital One’s Eno bot is one of the oldest and most respected.
  40. 40. We Chat – 900 Millions users
  41. 41. DJ Hardwell (The Bot Plateform)
  42. 42. Let’s Meet Thédorore – The ULB Recruitment Bot
  43. 43. VDAB: DIGITAL PROJECTS CONVERGENCE A.I. + HUMAN 60
  44. 44. OBJECTIF 61 INSCRIPTION RASSURER Convaincre la cible de s’inscrire à l’ULB Faire sauter les barrières (craintes, questions, problèmes) retenant la cible potentielle de s’inscrire Eleves francophones inscrits en rhétorique en 2016-2017 dans un établissement belge, ayant obtenu leur CESS et désirant poursuivre leur formation dans un établissement d’enseignement supérieur. LA CIBLE On a décidé de se concentrer sur les étudiants, et non les parents avec adolescents car ces derniers sont, d’une part, plus difficiles à cibler et identifier, et, d’autre part, stratégiquement pour le budget donné, les performances seront meilleures sur les jeunes sur les réseaux choisis.
  45. 45. UNE STRATÉGIE, 3 AXES 62 CONVAINCRE DE REJOINDRE L’ULB INFORMER SUR L’UNIVERSITE S’INSCRIRE SUR LE SITE DE L’ULB Faire sauter les barrières et informer les étudiants sur la vie universitaire Convaincre les étudiants de s’inscrire à l’ULB, l’université pour leur futur. Aider et inciter les étudiants à s’inscrire à l’ULB avec une communication adaptée
  46. 46. LET’S INTRODUCE YOU TO OUR HOME MADE CHATBOT
  47. 47. In which situations would you be comfortable with a company using AI to give you better customer service ? (Source: Pega)
  48. 48. Bots Handy Guide (Source: Huffington Post)
  49. 49. 3.B.2 – Speech Recognition
  50. 50. Began in 2014 , the smart speaker battles are not really about the device
  51. 51. Voice assistant The new search engine Different Strategies: - Apple Siri is wherever you are. - Amazon Echo is only at home. They created the category and are the first that have a version with a camera and another one with a screen. - Google has experience in search. They take advantage of processing the information in the cloud. Some people do not like to give them their private information. - Microsoft tries to be everywhere but, by now, only excels in games.
  52. 52. Search is still key … According to Google, 20 percent of searches on its mobile app and on Android devices are voice searches. The total number of voice searches overall is actually much higher when you take into account personal assistants like Amazon’s Echo (aka Alexa), Google Home (a direct competitor of the Echo), Siri and Cortana — tools that are solely based on voice recognition.
  53. 53. Juniper estimates that smart speakers such as Amazon Echo, Google Home and the Sonos One will be installed in over 70 million US households by 2022, reaching 55% of all homes.
  54. 54. 2015 Campbell’s Is Offering Recipes via Amazon’s Voice-Control System
  55. 55. 2016 Amazon Echo Can Now Order Your Domino Pizza The process of ordering via Echo will first require that Domino’s customers set up a “Pizza Profile.” Multi-Plateform: desktop, mobile, SMS, Twitter, Samsung Smart TVs, Ford Sync, smartwatches like Android Wear and Pebble, and its own native application (where you can also speak to its virtual assistant, Dom, by voice).
  56. 56. Johnnie Walker: Educating consumers and promoting new products
  57. 57. GE started allowing Amazon Echo users to control their WiFi-connected appliances with voice commands
  58. 58. BURGER KING – “”Ok, Google …” - DAVID MIAMI
  59. 59. 3.B.3 – Conversional Marketing / Commerce
  60. 60. Having developed out of traditional channels over the past decades, conversational commerce leads the way towards a new era of individualized shopping.
  61. 61. 3 main conversational commerce to apply natural interaction to drive purchase decisions.
  62. 62. Higher customer engagement + individual offerings = higher conversion
  63. 63. Conversational Commerce Bot Market According to MarketsandMarkets, the conversational commerce bot market ◦ Grow from $703 million USD in 2016 to $3,172 million USD by 2021. ◦ Compound annual growth rate of 35.2%. Ubisend research shows a number of factors are driving this rapid growth. ◦ A change in consumer behavior from social networks to social messaging, ◦ The rise of the on-demand economy and demand for delivering a personal service at scale
  64. 64. Starbucks Conversional Commerce Allowing consumers to order coffee at home or in their car using smart devices such as Amazon Echo So far, it has made the feature available to roughly 100,000 customers in the US
  65. 65. Large players are operating the new conversational commerce channels successfully
  66. 66. In anutshell 5 Distinguishing Features of Conversational Marketing
  67. 67. 13/11/2017
  68. 68. Marketeer vs Consumer (Source: Pega)
  69. 69. Marketeer vs Consumer (Source:Pega)
  70. 70. Recommendation = From Product to Service
  71. 71. 3.B.4 – Image Recognition
  72. 72. CrowdEmotion CrowdEmotion offers an API that uses facial recognition to detect the time series of the six universal emotions as defined by Psychologist Paul Ekman (happiness, surprise, anger, disgust, fear and sadness). Their online demo will analyze facial points in real-time video, and respond with detailed visualizations.
  73. 73. No emotion is a bad emotion when it comes to creating content-led marketing campaigns BBC Case – Take Away: Trigger serious emotions to meet your campaign objectives e.g. puzzlement, fear and sadness increase positivity by 35 per cent. Don’t ignore the lighter emotions. Happiness and surprise increase desire to purchase, supporting brand image and consideration. Clearly label your brand – it adds credibility to the content à a positive impact on perception of the brand. Showcasing the right emotions will drive social media referrals. 55% of consumers who express happiness, puzzlement and fear are likely to share content.
  74. 74. You can’t always get what you want (with text search) à 74% of consumers say text-based keyword searches are inefficient for helping them find the right products online à 67% of consumers say quality of product images is very important in selecting and purchasing products à 90% of information transmitted to the brain is visual à Visual information is processed 60,000x faster than text
  75. 75. Slyce – The Want Engine !
  76. 76. ASOS Visual Search Monetize the ‘discovery’ phase of the shopping journey Turns the user’s smartphone camera into a discovery tool, allowing them to take a picture of a product. By identifying the shape, color, and pattern of the object, ASOS’ AI technology can then cross-reference its own inventory of products and serve up the most relevant results.
  77. 77. TheTake uses AI to identify products, locations in video
  78. 78. Sephora Visual Artist product à “try on” cosmetic products Powered by Modiface AI technology, the Visual Artist can map and identify facial features, then use augmented reality to “apply” the user’s selected product and shade. Moreover, it can automatically apply suggested shades based on the consumer’s skin tone.
  79. 79. Sephora Visual Artist product à The Visual Artist is also hosted on Messenger. Shoppers can send a picture to the Sephora chatbot and it will come back to them with a range of suggested products, along with an augmented reality image of how they look once applied.
  80. 80. 3.B.5 Recommendation
  81. 81. $6 billion on content this year ◦ If it just presented the most popular selections to everyone, many titles would remain unseen. ◦ Wasted content spend, Less time watching Netflix instead of other networks. Take-rate on top personalized video recommendations was 3 to 4 times higher than the most popular videos. ◦ Viewers were exposed to 4 times as many videos using personalized recommendations compared to a list of the most popular titles. Recommendations = surface niche titles that wouldn't find an audience on a traditional cable network, but that its viewers love ◦ Save money on its content & maximize the value of inexpensive titles. Recommendations lead to meaningful increases in overall engagement with the product (e.g., streaming hours) and lower subscription cancellations rates. ◦ Higher lifetime customer values and lower revenue volatility. ◦ Retention rates are already high enough that it takes a very meaningful improvement to make a retention difference of even 0.1%.
  82. 82. Netflix Recommendation à Generate a Long Tail Approach
  83. 83. Netflix – A.I. Expense Over the past few years, Netflix's technology and development budget has increased slightly faster than its overall revenue. 2015, it increased 38% to $651 million = 10% of revenue. Not only in recommendations engine. Technology and development expenses include "testing, maintaining and modifying our user interface, our recommendation, merchandising and streaming delivery technology and infrastructure."
  84. 84. The ROI of recommendation engines for marketing 1. Improving with use (positive feedback loop) ◦ With more data to train its algorithms on (more active users interacting), Netflix has the advantage of improving its offering faster and faster. This “winner take all” dynamic, is one of the reasons why “improvement with use” is so important. 2. Improving cart value (profit) ◦ Amazon has integrated many recommendation “entry points” into its online experience to maximize cart value ◦ Estimation: 35 percent of consumer purchases on Amazon come from product recommendations. In 2016, it offered its open-source AI framework called, DSSTNE for free to encourage the development of artificial intelligence apps. ◦ 11.11 Shopping Festival 2016, Alibaba used AI to display product recommendations on 6.7 billion personalized shopping pages à 20 % conversion rate improvement.
  85. 85. The ROI of recommendation engines for marketing 3. Improving engagement and delight (retention) ◦ YouTube’s recommendation engine has been powered by Google Brain since 2015 ◦ YouTube had plenty of experiments and redesigns before employing an algorithm that searches for similarities among different types of video content ◦ Some of the data points that it uses include a user’s viewing history, age of videos, search terms and location to decide which video will play next ◦ YouTube earns revenues when a viewer watches more than 30 seconds of an ad, or when a user clicks an entity on the screen or an ad listed on the page.
  86. 86. RankBrain is an artificial intelligence system that is designed to understand how people search and why they’re searching (or their intent when searching). It does this through a mathematical process and advanced (and evolving) understanding of written language semantics that’s intended to help RankBrain ultimately “understand” searchers on a deeper level than simply matching keywords
  87. 87. 3.B.6 Content Generation / Creative
  88. 88. Did a Human or a Computer Write This? MARCH 7, 2015
  89. 89. Did a Human or a Computer Write This? MARCH 7, 2015
  90. 90. Did a Human or a Computer Write This? MARCH 7, 2015
  91. 91. Did a Human or a Computer Write This? MARCH 7, 2015
  92. 92. 20 % of all business- oriented content will be generated by machines by 2018 (Gartner) Client reports Product descriptions Campaign summaries TV programming Announcements Ratings analysis, Online content for clients Social media updates … Wordsmith, a software platform lets you create sophisticated templates that turn raw data into unique pieces of writing about that data. Wordsmith is a natural language generation (NLG) platform.
  93. 93. 1. What kind of data does my brand have access to ? You’ll need to have some type of structured data—data commonly arranged in columns and rows, like in a spreadsheet. As an example, the Associated Press has access to a continuous stream of earnings data in a structured format. Once it uses an AI tool to create an automated template for that data, it can apply the template to new data as it’s generated, provided it’s in the same format. 2. What narratives can I tell with that data ? What stories are you already manually telling with your numbers? What stories would be profitable for you to tell if you had unlimited time or budget? Many different datasets have stories to tell, and many can be automated. But currently it takes human insight to determine which stories will be the most useful.
  94. 94. Saatchi & Saatchi L.A. Toyota Mirai – 1.000 ads The Saatchi LA team spent three months training it to write first in coherent sentences and then to customize the communication to a target demographic. The target demographic for the campaign was scientists, engineers and other early adopters of technology.
  95. 95. Saatchi & Saatchi L.A. Toyota Mirai Training ‘Watson’ is mandatory With more training scripts it became better until it finally produced the sentences, “Yes, it’s for fans of possibility.” Many more lines came afterward, each focused on target consumer profiles. The goal wasn’t necessarily to use Watson to produce higher quality or more creative output. Saatchi LA could have come up with compelling concepts and copy. The difference here was scale. While each video looks the same, the copy is tailored to more than 100 different demographics, resulting in thousands of pieces of content. The IBM Watson output was rough at first producing only unintelligible sentence and word combinations.
  96. 96. Programmatic creative: set of advertising technologies that add speed, scale, and automation to the creative process.
  97. 97. DCO CMP
  98. 98. A.I.Men – The Young Pope: The Papal Artificial Intelligence
  99. 99. A.I.Men – The Young Pope: The Papal Artificial Intelligence
  100. 100. It was funny to see how a 2,500-year-old text, the Holy Bible, could still be relevant in our modern and hyperconnected world, and show its timelessness in contemporary issues
  101. 101. 3.B.7 Dynamic Pricing
  102. 102. Uber: Till 2017 - Prices go up to encourage more drivers to go online. The increase in price is proportionate to demand
  103. 103. First degree price discrimination is … … the act of charging customers a different price for the same product or service, depending on who they are and how wealthy they seem, to capture as much consumer surplus as possible.
  104. 104. A.I. à From Price to Value
  105. 105. Dynamic pricing: Retailers using artificial intelligence to predict top price you'll pay You could be paying more than others Data used by pricing algorithms is gathered from seemingly benign sources such as loyalty cards and even post codes. But it also increasingly incorporates prior behavior. As with gambling, the house always wins In the long run, consumers are likely to be the biggest losers, because dynamic pricing plays on our desire to find that next bargain. Moral and ethical questions It has the potential to worsen social inequality, particularly as the determinations used by retail algorithms are intentionally non-transparent Algorithms to negotiate on your behalf Products like Amazon's Echo or Google's Home are the first tangible versions of the quest to make artificial intelligence butlers a common household feature. The goal is to persuade consumers that they can save time and energy by delegating mundane tasks like ordering groceries or booking tickets to these artificial agents.
  106. 106. 3.B.8 Predictive & Prescriptive Marketing
  107. 107. 146
  108. 108. Served grill video and purchased grill. Served geotargeted patio message Northern Market. Served geotargeted patio message Southern Market. Served STRONG promotional message Went to site but did not purchase. Served STRONG promotional message Ongoing personalized messaging CUSTOMER JOURNEY ANALYTICS DRIVE CONTENT CREATION
  109. 109. Research / Audience Management / Personae Generation
  110. 110. FACEBOOK KNOWS YOU BETTER THAN YOUR… FRIENDS FAMILY SPOUSE 70 150 300
  111. 111. So.Prism Smart data & advanced algorithmes to deliver relevant insights 2,000 criteria to describe an audience by psychographic (people's interests), demographics and mobile behaviours.
  112. 112. COMPETITIVE AVANTAGE Data Processing Real Personas Generation In Depth Mapping
  113. 113. Exemple - Leveraging social insights to detect appropriate TV contexts Discover unique insights about your consumers’ behavior through the power of social profiling. Collecting Customizing Matching Profiling Basic-Fit clients data base 18-45 y.o Create a custom audience based on client email adresses Match Basic-Fit Custom audience with Soprism total audience 18-45 y.o Identify interests in affinity with the audience Examples - The Voice: 125 aff - Cyril Hanouna: 135 aff - Ozark Henri: 116 aff - Pukkelpop: 144 aff - Viceland: 122 aff - …
  114. 114. Creating Persona Data collection and analysis of data Persona descriptions Scenarios for problem analysis and idea development
  115. 115. Persona Generation
  116. 116. Let’s Meet Lucy an invaluable member of the marketing team Lucy can à hunt down facts about a potential market à pull together customer profiles from social media à draw up media models in moments. She performs previously time- consuming tasks in an instant, empowering marketers to do much more in far less time, and the more she does the more she learns, growing and developing according to a campaign’s needs.
  117. 117. Lucy A new employee feeded by Data She is already populated with data from sources such as SEMRush, Spinn3r, SimilarWeb, US Census and Clearbit and can crunch reams of data to answer any marketing question. Her easy to use interface also means that marketers can ask questions in a free text format, simply and directly.
  118. 118. Communication Campaign Management
  119. 119. Cosabella is using multiple A.I. Media Campaign Tools … with success !
  120. 120. A.I. empower Cosabella CRM Campaign
  121. 121. Cosabella + Emarsys – Factor of succes The right structure Marketing team and merged with the e-commerce team & IT / digital director took over marketing From a design-led marketing to a technology-led marketing. ◦ determine how to crunch data, develop customer profiles, connect with audience in a rapidly changing marketplace.. ◦ How do we bring that function in-house without hiring 200 people ? à A.I. The right implementation strategy Knowing that non-technology people would be primarily responsible for using the platform day to day, it was important for Emarsys to gear the deployment to the team’s needs and knowledge levels. Ease of use and approaching the implementation using laymen’s terms were early priorities. Moving the needle to confidence The list of potential uses for AI in retail is almost limitless, and the technology is still maturing. Forget the human- driven guesses that have sculpted past marketing efforts; today’s AI is all about knowing.
  122. 122. A.I. empower Cosabella CRM Campaign How does it Work ?
  123. 123. Aditionally, Cosabella use Albert Autonomous Media Buying A.I. After processing high-level KPIs, parameters, and creative materials, Albert quickly identified emerging user behavior and patterns across paid search and social media. He then analyzed the behaviors to produce insights and suggestions for optimal performance and scalability. Most crucially, he then autonomously executed on the suggestions, delivering previously unseen results across channels including: ◦ Proactive creative and messaging insights & recommendations. ◦ Micro-campaigns of infinite campaign variables. ◦ Autonomous media buying using predictive analytics and deep learning.
  124. 124. A.I. Capacities = (Human Capacities) x A.I. (Albert) can create user segments based on: Contacts: People in the brand’s existing CRM, which can be broken down into segments such as ‘parents', 'highest lifetime value',' newsletter subscribers' or 'loyalty club members'. Visitors: Website visitors who, for example, added something to their cart, viewed a product, or made a purchase (these were not applicable in Dole's case). Lookalikes: New audiences resembling previous high-value customers. Based on its incessant testing, A.I. (Albert) can determine : What media to invest in, at what times and in what formats. How much budget to spend on each channel and for each ad format. Which creative + headline combinations to use for each micro-segment. Which ad combinations to place where. Which cities, audience types and audience behaviours to prioritize and target. Which cities, audience types, and behaviours to eliminate.
  125. 125. AI caused a fruit-cocktail sellout for Dole (APAC) blew through its primary KPI in half the allotted time; led to temporary sellout conditions in some stores; drove an 87% increase in store sales once stocks were replenished; and garnered the brand 60,000 additional Facebook followers.
  126. 126. Example actions that Albert took during Dole's campaign à Agnostic & Apolitic à After determining that the average cost per page "like" was 18 % better in one city than in another, allocated resources on social according to optimal performance and pricing. After discovering that user engagement on Facebook was 40 % higher for mobile users than desktop users, shifted resources to target mobile and adjusted bids accordingly. Noticed an over-index in responses in the Metro Manila region and therefore started focusing more spend in that area. Found that video ads on Facebook increased clickthrough rates and would expand reach to more potential customers, so requested more video ads for Facebook. Discovered that videos on organic pages (such as a Facebook profile page, as opposed to an ad) produced a 165 percent increase in page engagements over seven days, so recommended introducing more video posts to those pages. Identified Saturday and Sunday as performing lower than the rest of the week
  127. 127. Harley Davidson New York City use A.I. Challenge: Harley-Davidson of NYC (dealer) understood the impact digital could have on its business but was unable to realize the full potential on its own given the size of their team and the resources available. Solutions: With Harley-Davidson NYC’s KPIs, business logic and minimal past campaign performance data, Albert discovered trending behavior at a pace only a machine can handle, and used continuously incoming info to optimize and scale performance including: ◦ Identifying unknown audiences. ◦ Identifying top-performing creative and messaging combinations and prioritizing them across all digital channels. ◦ Pricing and budget allocation across all digital channels (on the fly marketing mix modeling).
  128. 128. A.I. Capacities = (Human Capacities) x Autonomous Test. Execute. Report.
  129. 129. Planning is A.I. Compatible … What about Strategy ?
  130. 130. 74% PEOPLE WOULD NOT CARE IF DISAPPEARED OF BRANDS 66% 27% LESS THAN NOTABLY IMPROVE OUR QUALITY OF LIFE OF BRANDS 26%
  131. 131. Should companies and brands play a role in improving our quality of life and wellbeing? Growing expectations 61% 70% 69% 75% Are companies and brands working hard at improving our quality of life and wellbeing? Weak performance 39% 30% 40% 30% … but few brands are delivering yet Increasing number of people want brands to be meaningful… 2015 2017
  132. 132. is not meaningful to consumers 60% of the content provided by brands And more than half of content fails to deliver
  133. 133. 6. A.I. Benefits in your Marketing MIX and Communication Process HOW A.I. COULD EMPOWER EACH STAGE OF THE CONSUMER DECISION JOURNEY ?
  134. 134. Consumer Decision Journey: 4 Battle Ground
  135. 135. Consumer Decision Journey: A.I. ?
  136. 136. - Bots - Recommendation Tools - Speech Reco - Image Reco - Voice assistant - Dynamic Pricing - Content Production - DCO - A.I. CRM - Predictive / - Prescritive Analytics
  137. 137. 7. Conclusion & Wrap Up
  138. 138. A.I. Is definitively moving 4P’s to S.A.V.E. in a Hyper Personalized Relation Product PlacePrice Promotion Service x Product = Bespoke Offer Value Based Pricing Access x (Learn + Apply) = Experience Engage, Entertain, Educate = Unique Relationship
  139. 139. Phygital vs Transhuman 187
  140. 140. General Conclusions àA.I. is already integrated in Marketing àConsumer is not completely perceiving that reality à We (Human) + A.I. = 3 à Let’s Human Concentrate on Strategy and Creative Big Idea à Test now is a must – Full productivity is about 10 Years
  141. 141. hugues.rey@havasmg.com @huguesrey + 32 496 26 06 88 www.huguesrey.com THANK YOU FOR YOUR ATTENTION !

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