A.I. in the Enterprise: Predictive Personalization
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This document discusses how predictive personalization using artificial intelligence can make business more human. It argues that AI has the potential to amplify a business's ability to build empathy with customers at scale by uniquely tailoring interactions based on modeling individual customers' preferences and behaviors. The document provides examples of how AI could deeply understand a single customer by analyzing all their online activities, and then scale that level of personalized understanding to millions of customers. It also outlines how AI is becoming the new standard for customer experience due to rising expectations, and argues that getting started with AI is easier than many businesses think through available cloud and open-source options.
A.I. in the Enterprise: Predictive Personalization
- 1. How can A.I. make business more human? PREDICTIVE PERSONALIZATION
- 2. PREDICTIVE PERSONALIZATION ● It’s ready for prime time ● It’s a gateway application ● It’s making business more human ● It’s changing everything ● It’s the new standard ● It’s easier to use than you think O U R JO U R N EY
- 3. IT’S READY FOR PRIME TIME
- 4. And what better way to demonstrate that it’s ready for prime time, than to show it live... PS — this is an open source application written by yours truly
- 6. The app provides a list of items that ‘may be of interest’ because they are related to the primary item The app also provides a list of items that ‘may be of interest’ because they are often bought/consumed at the same time as the primary item The primary item These could be TV shows, videos, physical products, blog posts ...pretty much anything gigaom.com/2017/02/08/building-a-recommendation-engine-using-microsoft-azure
- 7. Recommendations Build FBT Build Model Application Training Catalog Training Usage HOW IT WORKS Related item recommendations Recommendations API Frequently bought together recommendations Note: You can make different types of predictions from the same dataset/model
- 8. ID NAME CATEGORY FEATURE #1 FEATURE #2 FEATURE #3 2005018 Clara Callan book Author=Richard Bruce Wright Publisher=HarperFlamingo Canada Year=2001 2255081 Spadework book Author=Timothy Findley Publisher=HarperFlamingo Canada Year=2001 2257203 Restraint of Beasts book Author=Magnus Mills Publisher=Harpercollins Uk Year=0 2558122 Angelas Ashes book Author=Frank Mccourt Publisher=Harpercollins Australia Year=0 6480764 Lost Girls book Author=Andrew Pyper Publisher=Harperperennial Year=0 6485200 The Piano Man's Daughter book Author=Timothy Findley Publisher=Britnell Book Wholesalers Year=1999 6485936 Dust book Author=Arthur G. Slade Publisher=HarperCollins Publishers Year=2001 6512062 Trials of Tiffany Trott book Author=Isabel Wolff Publisher=Harper Collins Publishers Year=1998 6514480 FUTON FEVER book Author=Dawn Anderson Publisher=HarperCollins Publishers Year=2000 6543545 The bookshop book Author=Penelope Fitzgerald Publisher=Flamingo Year=1989 6546684 Postcards book Author=E Annie Proulx Publisher=Flamingo Year=0 6547834 Miss Smillas Feeling for Snow book Author=Peter Hoeg Publisher=Flamingo Year=0 6550576 Red Leaves book Author=Paullina Simons Publisher=Flamingo Year=0 6550649 Cocaine Nights book Author=J G Ballard Publisher=Flamingo Year=0 20198906 Joshua book Author=Joseph F Girzone Publisher=Macmillan Year=1987 TRAINING DATA USER ID ITEM ID 85526 2005018 210926 2005018 116866 2005018 177458 2005018 8 2005018 123629 2005018 219008 2005018 41385 2005018 96054 2005018 11400 2005018 11676 2005018 263325 2005018 67544 2005018 200273 2005018 274004 2251760 It’s that simple! Catalog file. Usage file. docs.google.com/spreadsheets/d/19m--YY2qVPM1r23KLZ9Q9zP2u4i1OoJdZkCNDbTOoNk/edit docs.google.com/spreadsheets/d/1bpgBwp_KP6aYBFjeRqMxx6kzEkHeRRv7IeCQvQhKVsY/edit
- 9. PLAN PLAN LIMITS PRICE Free 10,000 calls / mo Free S1 Standard 100,000 calls / mo $75 / mo (overage at $0.75 / 1000 calls) S2 Standard 1,000,000 calls / mo $500 / mo (overage at $0.75 / 1000 calls) S3 Standard 10,000,000 calls / mo (overage at $0.75 per 1K calls) $2,500 / mo (overage at $0.75 / 1000 calls) S4 Standard 50,000,000 calls/mo $5,000 / mo (overage at $0.75 / 1000 calls) PRICING
- 10. WHERE IS THE A.I.? In the application’s ability to… ● ‘Understand’ what a specific customer likes & dislikes ● To predict what other items a customer may like As compared to ... ● Having people review past actions and generate manual recommendations, or ● Only personalizing at the group level Remember: A.I. is subjective
- 11. It’s here. It works. And it has a quick R.O.I. IT’S READY FOR PRIME TIME R EC A P
- 12. IT’S A GATEWAY APPLICATION
- 13. If you’re looking for a place to begin your A.I. journey, this is a good starting point...
- 14. THE EMPIRE BUILDER Personalization works...extremely well! Content recommendations Personalized search results Personalized advertising Personalized discussions Product recommendations
- 15. ONE OF THE QUICKEST R.O.I.’s Improving customer experience at the marketing and sales level. Marketing Support Product Admin Innovatio n Quickest R.O.I. Suggested implementation path
- 16. PEOPLE LIKE PERSONALIZATION ● 59% of consumers who have experienced personalization believe it has a noticeable influence on purchasing ● 67% of consumers who have experienced personalization are highly in favor of personalized coupons ● 69% of consumers believe a brand's consistency across channels affects their loyalty infosys.com/newsroom/press-releases/Documents/genome-research-report.pdf
- 17. AND THEY’RE HAPPY TO SHARE Source: salesforce.com/form/service-cloud/state-of-connected-customer.jsp
- 18. TREATED LIKE PEOPLE, NOT NUMBERS “Modern customers want to feel a real human connection with brands and want technology to enhance this connection, not to replace sales and service reps.” salesforce.com/form/service-cloud/state-of-connected-customer.jsp
- 19. FAMILIARITY AT EVERY TOUCHPOINT “When a local grocer or bookstore owner remembers a customer’s name, it means something — it makes that person want to come back.” salesforce.com/form/service-cloud/state-of-connected-customer.jsp
- 20. AND PROVEN BENEFITS ibm.com/watson/advantage-reports/market-report.html 600 decision makers worldwide, actively engaged in or planning A.I.-related initiatives
- 21. IT’S A GATEWAY APPLICATION This application provides an easy entry point with proven results and R.O.I. Not to mention an open source application to kickstart your project. And a ton of how-to guides to keep things moving. R EC A P
- 22. IT MAKES BUSINESS MORE ‘HUMAN’
- 23. WHAT MAKES US ‘HUMAN?’ Empathy. The ability to understand and share the feelings of another.
- 24. HOW DO WE SHOW EMPATHY? When communicating with others, we uniquely tailor how we speak with them. We demonstrate that we appreciate their unique wants, desires, circumstances, etc. In effect, we personalize the experience they have with us.
- 25. RELATIONSHIPS 101 And how do we build strong relationships? Listen to what they say, Take the time to understand who they are, and Find ways to make their life better.
- 26. IT’S A QUESTION OF SCALE Building deep meaningful relationships takes a lot of work. As human beings, we can only build great relationships with a handful of people. But A.I. can amplify that effort so you can build great relationships with millions.
- 27. FOR EXAMPLE... Pick one of your customers. Read every piece of content they’ve ever put out — every blog post, tweet, facebook update, Instagram image, etc. How well do you know them now? Pretty darn well — you understand them and can share their feelings. That’s empathy. And how well do you think you could market to them now?
- 28. A.I. is an amplifier. It allows you build empathy at a scale and depth that is simply beyond human capabilities. ● Model the habits, likes, dislikes and values of your customers, then ● Predict the behavior of those customers and personalize their communications accordingly NOW SCALE THAT UP
- 29. Computers can dig deeper and personalize at a scale that’s simply beyond human capacity. This allows A.I.-powered brands to build deeper relationships — with more customers — than was previously possible. MAKING BUSINESS MORE HUMAN R EC A P And just to clarify, I’m not saying A.I. develops better relationships. I’m only saying it amplifies the number of relationships you can develop.
- 31. A PARADIGM SHIFT PredictOptimize vs.React to signals Start with guesses Foresee behaviors Start with models Up to now, businesses have focused on “optimizing” their interactions. With A.I., we can now shift to “predicting.”
- 32. Behavior Prediction Interest Tracking PREDICTIVE PERSONALIZATION Pages & content they’ve visited Emails they’ve opened/clicked Resources they’ve used/downloaded Products they’ve viewed/wishlisted/bought Searches they’ve made Blog Store Find patterns Determine what they want to see/do/buy next (and when) Days/time they’re active App Search Devices they’ve used (& geo location) Email Social • Recommended posts • Recommended products • Delivery day/time • Dynamic content • Related posts • Sales offers • Related products • Cross/up sell • Dynamic pricing • Dynamic content • Sales offers • Functionality • Query suggestions • Results ranking • Sales offers • Content curation • Delivery day/time • Retweet/reshare Tribe • Recommended topics • Topic curation • Member introductions Your customer A.I.
- 33. CHANGING EVERYTHING No longer is business constrained to ‘after-the-fact’ reactions. You can now predict what your customers will want next before they even know it themselves. And you have the ability to leverage that type of prediction across any interaction you have with them. Welcome to the era of ‘predictive.’ R EC A P
- 34. IT’S THE NEW STANDARD
- 35. “Customer experience is the new battlefield.” ~ Gartner, 2015 accenture.com/us-en/insight-artificial-intelligence-ui EXPERIENCE ABOVE ALL
- 36. Customer expectations rise universally. You aren’t just competing against your direct competitors. You’re competing against the experiences your customers get from any of the other brands they use. AND...
- 37. PRODUCT RECOMMENDATIONS Amazon has gotten very good at delivering ultra-precise recommendations, uniquely personalized for each customer. And now those customers expect the same treatment wherever they shop.
- 38. CONTENT RECOMMENDATIONS Same with YouTube… Why should I have to search when YouTube does such a good job of presenting the stuff I like.
- 39. If your customers have a remarkable support experience with any brand they interact with...that remarkable experience immediately becomes the benchmark against which they judge all other brands. And there are plenty of brands out there already using predictive personalization systems. IT’S THE NEW STANDARD R EC A P
- 40. IT’S EASIER THAN YOU THINK
- 41. PICK YOUR STARTING POINT A.I. M aturity No training data required! Purpose-Built Platform, Their Training Data Commercial Platform, Their Training Data Commercial Platform, Your Training Data In-House Platform, Your Training Data
- 42. NOTHING NEW HERE Most of the major cloud providers have purpose-built A.I.-powered APIs. Many have a free tier. And they work exactly like every other API you’re already using.
- 43. R ESO U R C ESLOTS OF COMMERCIAL OPTIONS Jumping back to our demo above, here are some alternative commercial APIs… ● Amazon Machine Learning ● Oracle Cloud ● Google Cloud Prediction API
- 44. ● archive.ics.uci.edu/ml ● deeplearning.net/datasets ● mldata.org ● grouplens.org/datasets ● cs.toronto.edu/~kriz/cifar.html ● cs.cornell.edu/people/pabo/movie-review-data ● yann.lecun.com/exdb/mnist (handwriting) ● kdnuggets.com/datasets/index.html (long list) ● image-net.org (competition) PLUS OPEN SOURCE DATASETS
- 45. ● gallery.cortanaintelligence.com ● bigml.com/gallery/models ● predictionio.incubator.apache.org/gallery/template-gallery ● github.com/tensorflow/models ● algorithmia.com/algorithms * AND PRE-BUILT M.L. MODELS
- 46. Start with a pre-trained cloud API (no training data required). Maybe even an open source app. Most cloud providers offer a free tier. So start thinking about the different ways to use A.I. to personalize your customer recommendations. Then just start testing and see what you can do. IT’S EASIER THAN YOU THINK R EC A P
- 47. NEXT STEPS
- 48. HOW-TO GUIDES ● Building Voice-Enabled Products With Amazon Alexa ● Cognitive Customer Engagement Using IBM Watson ● Harnessing Visual Data Using Google Cloud ● Building a Recommendation Engine Using Microsoft Azure ● Predicting Marketing Campaign Response Using Amazon Machine Learning ● Unleashing A.I.-Powered Conversation With IBM Watson ● Get into the Mind of Your Customer Using Google’s Sentiment Analysis Tools ● Discover Your Customers’ Deepest Feelings Using Microsoft Facial Recognition ● Give Your Products the Power of Speech Using Amazon Polly ● Computers Are Opening Their Eyes — and They’re Already Better at Seeing Than We Are ● How to Predict When You’re Going to Lose a Subscriber ● The Future of Business is a Digital Spokesperson — Let’s Build a Preview Using Microsoft’s Bot Framework ● Predicting Personality Traits from Content Using IBM Watson R ESO U R C ES How to build the demo app in this session
- 49. JOURNEY’S END ● Predictive personalization is ready for prime time ● It’s a gateway application ● It’s making business more human ● It’s changing everything ● It’s the new standard ● It’s easier to use than you think R EC A P
- 50. THAT’S ALL FOLKS! Laying the foundation ● Cutting Through the Hype 2 A.I. Technologies that will have the greatest impact ● Computer Speech ● Computer Vision 2 A.I. Applications with the quickest R.O.I. ● Predictive Engagement ● Predictive Personalization
- 51. QUESTIONS OR COMMENTS? Gigaom A.I. Team: ai@gigaom.com Workshop Facilitator: chris.mohritz@10xeffect.com C O N TA C T
- 52. THANK YOU