The Rise of AI-Empowered Marketing
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With all of the noise around artificial intelligence for marketers, how do you understand what’s really needed to succeed today and tomorrow? Join guest IDC Analyst, Gerry Murray, and Marketo’s Senior Director of Product Marketing, Ariane Lindblom, to learn how AI empowers marketers to engage smarter, grow revenue, and save budget. View to learn how to: - Predict the right mix of programs for the right people to meet your goals - Personalize your campaigns at scale with confidence - Perform with precision, driving more value for your audience
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The Rise of AI-Empowered Marketing
- 1. The Rise of the AI-Empowered Marketer Ariane Lindblom Sr. Director, Product Marketing Marketo Gerry Murray Research Director IDC
- 2. INFINITE DEMAND DRIVERS FINITE ATTENTION The Demand Curve for Customer Attention
- 3. only consider brands that show they understand and care about ‘me.’ (Wunderman) of buying experiences are based on how customers feel they're being understood. (McKinsey) Buyer Expectations have RADICALLY SHIFTED 79% 70% 66% of customers expect their interactions with brands to be personalized. (Marketo)
- 5. Pivot from One-Size-Fits-Most to Segment of 1
- 6. Pivot from One-Size-Fits-Most to Segment of 1
- 7. Who wants to build a million journeys?
- 8. Artificial Intelligence: Built for Marketers Performs on Centralized Data Provides Control & Transparency 1 2 3
- 9. PREDICT PERSONALIZE PERFORM 34 78 28 18 ENGAGEMENT
- 10. What do you need to know to make the vision a reality?
- 11. What is it? Why now? AI Apps for Marketing Getting ready for AI Surprise! Action Plan Agenda © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 12. AI: What is it?
- 13. Deep learning: neural networks – image identification and tagging Machine learning: optimization algorithms Ambient computing: consumerizing AI Conversational systems: chatbots, virtual qualification agents Cognitive systems: strategic planning Artificial Intelligence: TBD Many flavors of AI © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 14. Cognitive: A multi-disciplinary world Source: SAS Data Mining Primer course in 1998 Computational Neuroscience Data Science Statistics Pattern Recognition Machine Learning AI Databases Data Mining Knowledge Discovery
- 15. Why now? (3 simple reasons)
- 16. An expanding universe of data #1 Cognitive Makes Marketers Smarter and Faster Vanishing windows of time Millions of customers with rising expectations © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 17. Modern marketing – a customer centric definition: “Deliver the most value to the best customers the fastest.” Modern marketing mission: “Raise customer expectations beyond competitors’ ability.” #1 Cognitive Makes Marketers Smarter and Faster © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 18. By 2020, 50% of companies will use cognitive computing to automate marketing and sales interactions with customers. #2 It’s going into everything Behavioral Interactional Performance Long form Geolocation News Personal data Healthcare Location Sports & Entertainment Social Corporate Logistics Financial Marketing Sales Procurement Asset mgmt. R&D Logistics HR Anti money laundering Retail pricing Patient outcomes Telco churn IT performance mgt. Retail Travel Media Healthcare Insurance Investment Commercial leasing Advertising Legal Driverless cars Smart home devices Self-flying drones Robotic systems Text analysis Video analysis Image analysis Predictive analytics NLP APIs ConnectorsData stores Hypotheses generation Machine learning Speech Recognition Dialogue Mgt. Finance Risk mgmt. Weather © IDC Visit us at IDC.com and follow us on Twitter: @IDC IDC’s Cognitive Software Ecosystem IDC FutureScape: Worldwide Chief Marketing Officer Advisory 2016 Predictions
- 19. Most marketers will consume AI within applications based on well defined use cases • Push button web content personalization • Push button lead scoring based on behavior and performance • Embedded in conversational applications • Automated content recommendation and optimization based on test case • And more But easy to use does not mean easy to understand and operate effectively AI Easy Button – it’s coming to apps you’re using right now © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 20. #3 It’s going to change consumer behavior forever – “B2Bot Marketing” By 2020, 40% of e-commerce transactions will be enabled by cognitive/AI personal shoppers and conversational commerce. © IDC Visit us at IDC.com and follow us on Twitter: @IDC IDC FutureScape: Worldwide Chief Marketing Officer 2017 Predictions
- 21. #3 It’s going to change consumer behavior forever Bot Persona Shopper bot: Tracks purchases, HH inventory, accepts offers, can purchase groceries <$25 Planner bot: Seeks deals on travel Recommender bot: Seeks info and offers on major purchases such as autos and homes Others: TBD Buyer Persona Name: Brenda Age: 36 Roles: Marketing VP, Market: Clothing, groceries, gas, dining, travel Drivers: past purchases, fitness, kids activities, adventure travel, music festivals © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 22. Applications for AI/ML in Marketing
- 23. Top 10 AI Apps for Marketing B2C B2B Signs you need it now 1 Chat bots Very high web traffic volumes and/or online support requests 2 Virtual sales rep/Email avatar avatar Unable or very costly to follow up on 100% of leads 3 Real time sentiment analysis analysis Large volumes of social traffic, powerful external influencers 4 Recommendation engines Complex buyer's journeys and content matching, delays in decision making 5 Live event monetization Need to optimize revenue and experiences onsite 6 Cognitive commerce Product discovery, personalized merchandising 7 Cognitive content Personalized real-time response generation at scale 8 Media mix optimization Large omni-channel advertising spend that is difficult to attribute to performance 9 Attribution analysis Omni-channel marketing in complex, long cycle customer acquisition models 10 Planning/budgeting Need to speed planning and budgeting process and allocate investments based on contribution to performance goals.
- 24. © IDC Visit us at IDC.com and follow us on Twitter: @IDC Fun with Chatbots
- 26. Live Event Monetization "Combining Ampsy's geofencing capabilities with their new AmpElite analytics powered by Watson has enabled us to identify super fans at live shows, engage with them in real-time or post- show, and micro-market to them on a level we've never seen before." Jesper Poulsen, VP of Artist & Brand Development, Epic Rights (Licensing Group for AC/DC, Aerosmith, KISS, and more) © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 27. © IDC Visit us at IDC.com and follow us on Twitter: @IDC Personalized Web Content Three dynamic content recommendations based on: • User profile • Session behavior • Automated content analysis Start with as few as 10 pieces of content
- 28. AI in eCommerce © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 30. The Cognitive Marketing Kitchen © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 31. Cognitive Marketing Team Business Analyst Project mgmt. Business assumptions Communications Data Scientist Data representation Featurization Model building Marketing Technologist Infrastructure mgmt System integration IT liaison Data Driven Marketer Business objectives Data cultivation Governance © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 32. 1 2 3 Key Stakeholders Role Benefit CMO Improved planning, budgeting, and visibility into marketing contribution to business performance Marketing finance Improved attribution analysis Marketing analysts Greater scale, scope and speed of analytics Content marketer Auto-generated content for simple interactions via SMS and email. Greater visibility into content effectiveness by segments and buyers' segments and buyers' journeys. Web marketer Cognitive commerce will make real time offer management systems more effective. Chatbots and virtual agents will increase engagement at increase engagement at lower cost. Email marketer Cognitively enabled content recommendation systems that match customer data, buyer's journey patterns, and content assets will improve content assets will improve email performance. Social marketer Greater insight into sentiments, influencer dynamics. And automated interactions. Ecommerce marketer Ability to discern real time insights on how web sessions are connected via content and behavioral patterns to help build communities and build communities and identify value added interaction opportunities Event marketer Real time sentiment analysis and on site monetization for large scale events. Source: IDC, 2017
- 33. Surprise! The Cognitive Consumer is just as smart as you
- 34. The Cognitive Consumer Microsoft Delve & Cortana Google Now and Google Assistant5.0? 10.0? Apple Siri © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 35. Everyday items will become data sensors Everything we touch, do, feel will be recorded More immediate, more intimate data collection Every step we take, every breath and heartbeat Cognitive and IoT and Buyer Behavior © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 36. The Super-Intelligent Marketer’s Dilemma: When you know everything about everyone all the time, what could possibly go wrong? © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 37. A simple thought experiment Weight Posture Fidgeting Hyperventilating Temperature Time Coughing Sneezing Rapid heart beat Falling asleep © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 38. A simple thought experiment © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 39. A simple thought experiment Weight Posture Fidgeting Breathing and Pulse Temperature Time Coughing Sneezing Ad Blocker © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 40. A simple thought experiment Weight Posture Fidgeting Breathing and Pulse Temperature Time Coughing Sneezing Falling asleep Ad “Streamer” Ad content should be like a music streaming service that learns what you like and what you’re in the mood/market for. © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 41. © IDC 41 The big philosophical debate (that hasn’t really started yet) Vs. Is consumer data just the new oil to be exploited by business? Is it the new currency to be spent by consumers? The issue is intent and its on this side.
- 42. 33 © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 43. 33 © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 44. 33 You bought diapers three weeks ago, you’re probably running low by now. Last time you bought Huggies, try Pampers for less. Save $10 © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 45. Customer expectations are evolving beyond product and price to privacy and personal value. Data as a service is the new model for marketers to go beyond messaging and targeting. Well defined use case is the #1 key to success with AI Focus on fit between use cases and data sources for AI/ML applications Leverage knowledge resources in OpenAI, Association for Uncertainty in Artificial Intelligence, the AI Forum, and others to learn about the impacts technologies. Avoid "black box" tools and models that defy understanding of how they work or reach decisions. Don't jump into deployment if the outcomes are both uncertain and potentially harmful. © IDC Visit us at IDC.com and follow us on 45 Action Plan © IDC Visit us at IDC.com and follow us on Twitter: @IDC
- 46. For More Information LinkedIn https://www.linkedin.com/company/idc Twitter https://twitter.com/@IDC www.idc.com Gerry Murray gmurray@idc.com https://www.linkedin.com/gerrymurray
- 47. QUESTIONS?
- 48. Marketo.com/AI To learn more, visit:
Notes de l'éditeur
- Hi everyone – [introduce self] Excited to have Gerry Murray from IDC here today, an AI expert – to talk to us about the Rise of the AI-Empowered Marketer
- [CHALLENGE WITH CUSTOMER ENGAGEMENT TODAY] Let me start with a question: How many of us are touching our customers with more email, more social, more everything this year? Obviously rhetorical when I ask in this forum, but when I meet with marketers, the universal answer seems to be, ”yes, I’m always doing more.” But that’s created a huge challenge for us as marketers – everyone else is doing more too. And our customers are less and less engaged with our messages because they’re bombarded. Can I take you back to undergraduate economics for a second? I like to think of this as supply and demand. We have this amazing universe of demand drivers… but the problem is the supply curve. There is a finite supply of attention that we can work with. We have always focused on creating demand – and that’s still the case, even as our world has evolved from one to one, to one to many, to digital. The problem is that the supply of attention is not only limited, but it may actually be shrinking: Part of the reason for this is simply how loud every conversation has gotten. If everyone is shouting, no single voice stands out. And buyers today are marketed to constantly at virtually every moment they are awake. Another reason is that buyers have far greater access to information than ever before, meaning they are more sophisticated and more empowered to make their own decisions. The buyer has a louder voice than the brand. We are in an arms race for finite attention.
- Because of all this, buyers expectations have dramatically changed… To get their attention, we have to do things differently now. Customers only want to work with brands that care about them. These days, they value experiences more than price, and feel that the best brands are delivering above their expectations across the whole customer journey.
- This is Engagement Economy Where everyone and everything is connected, expectations continue to rise, while attention is pulled in a million directions. In the Eng. Economy, the currency is attention. And we all run the risk of getting 0 attention by trying to get too much attention The risk for marketers in the Engagement Economy is IRRELEVANCY
- What’s the opposite of irrelevancy? Again, bit of a rhetorical question, but also obvious: it’s relevancy. We have to get relevant on a personal level, and as the data I shared a second ago clearly indicates, our customers EXPECT a high degree of personalization. Focusing as precisely as possible on value for each individual is paramount to our survival in a world where everyone is justifying “one more send” every day. I talk to plenty of marketers who send one more email because it costs practically nothing, but it’s a blast. Maybe to the whole database. Or maybe, you have precise demographic, firmographic segments – and again, you’re hitting send and crossing your fingers that on an individual level, you’re going to get a slice of finite attention. That’s the one-size fits most approach.
- But be relevant, we have to take the guess work out of engagement. We have to have a clear line of sight into what engages each individual in our database. We have to pivot to segments of one. This is how we will win.
- The other side of the equation is how much work the “segments of one” concept creates for you and your teams. It might be fine if you have ten customers, but there’s a reason we rely on segmentation – scale. In short, hand-tuning customer experiences doesn't have the speed or scale to keep pace with the scale more of us are dealing with. Setting up 10s of millions of pre-determined customer journeys just isn’t feasible – and still doesn’t get us to that desired state of marketing to a segment of 1 and being relevant in the moment, every time. It isn’t possible -- without help.
- AI is what gets us there. But, it has to be AI built for Marketers, think Marketer + Machine. An overlay to everything you do that amplifies your ability to Listen, Learn, and Engage to a whole new level. (Like Ironman’s mask.) 3 core tenets to our point of view on what AI for marketing looks like… It must be purpose-built for marketers (generic AI is not the answer) – because you have to understand the context for the technology in your day-to-day so you can deploy it effectively, make sure it’s being adopted, and measure KPIs requires a centralized place for all customer data, because AI is only as good as the customer data it has to work with… and having it all centralized makes the intelligent engagement that follows more real-time, accurate and completely informed must provide Transparency to marketers as to what inputs are driving the algorithms and Control on when to let AI work automatically so that marketers can test and trust the outcomes
- All of this provides a pathway to exponential growth by letting you: PREDICT the right programs for the right people: to achieve business goals & go from broad audiences to segment of one (input your goals, machine guides you) -> what are the programs and campaigns I should run and to which micro-segments in order to optimize my spend to achieve my goals. ( Provide insights into customer churn, loyalty, lifetime value, and ROI to Marketing using platform dashboards or interface) PERSONALIZE with confidence: right content, right channel, right moment, all with transparency and control so that I can test and trust the experiences being delivered PERFORM to the Nth degree: harness all your audience data, to continually auto-optimize millions of experiences with precision, to drive more value, while making your life easier
- [Hand off to Gerry] All of this is a really compelling vision, but Gerry, I want to turn it over to you now. What does the marketer need to know about AI to start toward making this vision a reality?
- Here’s Ampsy. They provide social marketing services to large rock concerts and sporting events. This is a rock concert at Gillette stadium where the Patriots play. It’s basically a pop up store with 100, 000 people in it. When the show’s over or the game ends everyone leaves and the stores closes, so its critical to optimize all the merchandising opportunities in real time. As we all know, every event has a hash tag they want everyone to use to tag their social streams. But not everyone remembers or types it in correctly. So Ampsy geo-fences the whole stadium and tags all the streams coming out of the event. They run those streams through Watson to analyze personalities, sentiments and to determine connections. They can then figure out who’s having a good time, who’s not, who’s influencing others, who’s commenting on who’s tags. They use this data to then send personalized offers via text and social media to people that have high propensities to buy or influence others to do so.
- Change mgmt. how to go from ad org working with agency to a business optimization team? Data Scientist MS in Applied Statistics, Mathematics, Econometrics, or other discipline related to Time-Series Analysis, Machine learning and Forecasting, or other related discipline with PhD strongly preferred Deep expertise in the design and fundamental principles of statistical modeling, predictive modeling, and applying statistical models and machine learning in a corporate or product context Experience in leading analytical product development or projects Documented experience working with large, complex data sets, advanced data modeling and designing analytical systems Minimum of 2 years of experience with one or more of the following statistical programing languages such as SAS, R, S+. etc * Minimum of 2 year of experience with large distributed systems like MySQL, Cassandra and Hadoop Experience with segmentation creation, time series modeling and report creation * Experience with machine learning and working with large datasets Intermediate to advanced proficiency with SQL, SAS, R, STATA or other high level data programming language Basic proficiency with Python, PHP, Perl, VB, JavaScript, C++ or other programming language Formal training or extensive applied experience with advanced statistical methods such as regression-type modeling, data-mining methods (e.g. classification trees) Proficiency with data visualization 2+ years developing data that merges relational tables, either within a relational database or related “big data” environments (e.g. SQL Server, Hadoop) Data Engineer What you'll do Continuously design, develop, and test data-driven solutions Help drive the optimization, testing and tooling to improve data quality Develop measurement approaches to evaluate performance continuously Span languages as needed, depending on the data processing framework in use Collaborate with software engineers, ML experts, and others, taking learning and leadership opportunities that will arise every single day Work in cross functional agile teams to regularly experiment, iterate, and deliver on new product objectives Work from our office in New York or Boston Who you areYou know how to work with high volume heterogeneous data, preferably with distributed systems such as Hadoop You are experienced with batch and real-time data processing frameworks like Crunch, Scalding, Storm, Kafka, or Spark You are knowledgeable about data modeling, data access, and data storage techniques You care about agile software processes, data-driven development, reliability, and responsible experimentation
- Audiences will be able to manage ads as a streaming service the same way they manage songs Buyers and sellers will: Have too much information Place a premium on timing and meaning Use cognitive systems to broker context and intent
- Update with new cover from visual brand deck.