AI for CRM

AI for CRM: A Field Guide to Everything You Need to Know

Introduction What Is Artificial Intelligence? Technology is evolving faster than ever. Cloud computing, care of mundane and forgotten tasks and reminding us of social media, and mobile devices are ubiquitous. Everyone important ones. AI can connect the various nodes of our (and everything) is getting connected: 3 billion internet users, lives (home, work, travel) into one experience that moves 5 billion mobile users, and 6 billion connected devices make seamlessly with us from house to car to office. Much of that up a network of information and interaction never before experience comes through our phones. Within a few years, AI seen in history. But that’s just the beginning. will be infused in everything digital. Artificial intelligence (AI) is the next major wave of innovation, As consumers, we are already using AI without even realizing driven by advances in computing power, the ability to store it. Google harnesses AI to autocomplete search queries, large volumes of data in the cloud at minimal cost, and easier predicting what you are searching for with great accuracy access to advanced algorithms. And it will be more disruptive and without human involvement. Facebook news feeds and and powerful than any previous shift in technology. Amazon product recommendations are tailored for you via machine-learning algorithms. Self-driving cars apply various AI is often represented by various related terms: machine AI techniques to avoid collisions and traffic congestion. learning, deep learning, natural language processing, All of these consumer apps have trained consumers to predictive analytics, and so on. All of these terms point to a expect more from businesses: The new standard for every future in which our platforms and systems are smart enough customer interaction is a smart, fast, seamless customer to learn from our interactions and data, not only to help us experience engagement. with what we ask, but also to anticipate our needs, taking 2

Introduction: What Is Artificial Intelligence? At a high level, AI is both understanding historical data and applying what is learned to current contexts to make predictions. This has the potential to make every business “smarter.” Today, every company faces an imperative to integrate AI into the fabric of their business in order to succeed. Until now, however, AI has largely been out of reach for businesses. The high cost to implement AI solutions, combined with a shortage of data scientists and incomplete data, has made it challenging for all but a few companies. That’s where we come in. In 1999, Salesforce launched the first-ever cloud CRM platform, making customer relationship management accessible to businesses large and small. $153 billion Since then, we’ve grown into a complete Customer Success Platform, with solutions across sales, service, marketing, estimated market community, analytics, commerce, IoT, and apps. Now, we’re making our platform even smarter with Salesforce Einstein. for AI solutions Designed to enable companies large and small to be smarter and more predictive about their customers, Salesforce by 2020 Einstein discovers insights, predicts outcomes, recommends next steps, and automates tasks for business users — all while — Bank of America Merrill Lynch getting smarter and smarter along the way. 3

Introduction: What Is Artificial Intelligence? To help you seize the AI opportunity, we’ll explore a few themes in this e-book: • What AI, machine learning, and deep learning • How AI will impact specific business functions, including: actually mean Sales (Chapter 3) • How AI has evolved, and why it’s suddenly a hot topic Sales Customer Service (Chapter 4) • What AI means for business, including key challenges Service and opportunities Marketing (Chapter 5) Marketing IT (Chapter 6) Platform Commerce (Chapter 7) Commerce Read on to explore how you can take advantage of a smarter future. 4

Glossary: How to Talk About AI Artificial Intelligence (AI) is the concept of having machines “think like humans” — in other words, perform tasks like reasoning, planning, learning, and understanding language. While no one is expecting parity with human intelligence today or in the near future, AI has big implications in how we live our lives. The brains behind artificial intelligence is a technology called machine learning, which is designed to make our jobs easier and more productive. Machine Learning is the core driver of AI, and involves computers learning from data with minimal programming. Essentially, instead of programming rules for a machine, you program the desired outcome and train the machine to achieve the outcome on its own by feeding it data — for example, personalized recommendations on Amazon and Netflix. (Learn more here.) Machine learning is a broad term that encompasses related AI techniques, including: Deep Learning which uses complex algorithms that mimic the brain’s neural network to learn a domain with little or no human supervision. Consumer apps like Google Photos use deep learning to power face recognition in photos. Natural Language Processing (NLP) uses machine learning techniques to find patterns within large data sets in order to recognize natural language. One application of NLP is sentiment analysis, where algorithms might look for patterns in social media posts to understand how customers feel about a specific brand or product. Big Data is the raw fuel of AI — large amounts of structured or unstructured information that provide the inputs for surfacing patterns and making predictions. Internet of Things (IoT) is a network of billions of digitally connected devices, from toasters to cars to houses and jet engines, that collect and exchange data and can communicate with one another to better serve users. Predictive Analytics is a branch of advanced analytics that is used to make predictions about unknown future events, based on patterns in historical data. You might see this in marketing offers that become more relevant to you each time you take action (or don’t) on an email offer. 5

CHAPTER 1 2 3 4 5 6 7 The Path to a Smarter World Computing has always been about data. It’s written into the Oxford Dictionary’s definition of a computer: “an electronic device for storing and processing data.” From the beginning, computers were designed to fill in gaps in human intelligence by storing, classifying, retrieving, and applying huge amounts of data to help us solve problems faster. AI for CRM: Everything You Need to Know 66

In the beginning, these were very simple problems. One of the earliest computing prototypes, sketched out by Belgian thinker Paul Otlet in 1934, “would allow people to search and browse through millions “Many, many of interlinked documents, images, audio and video companies now find files,” according to The New York Times. It was an early vision of the internet with a poetic name: the themselves with “Mundaneum,” a means of storing and processing huge amounts of “mundane” data. The premise huge amounts of of computing is to do what the human mind is designed not to do: remember every little detail, data. What are we storing it so that every data point can be easily accessed when it’s needed. (The human brain, going to do with it?” by contrast, is designed to focus its processing power on what’s important, as Nobel Prize-winning Ascander Dost economist Daniel Kahneman explains in his book Senior Software Thinking, Fast and Slow.) Engineer & Linguist, Salesforce AI for CRM: Everything You Need to Know 7

From the beginning, though, we dreamed of computers This is why, while the idea isn’t new, true AI is only now that could do more than the mundane. In 1956, Prof. John becoming a reality. The data models came first, with McCarthy coined the term “artificial intelligence,” describing simple if-this-then-that logic evolving into increasingly a world in which machines could “solve the kinds of complex problem-solving algorithms. The idea of problems now reserved for humans.” machine learning is simple: But in order to move from simple computing to true AI, computers needed three things: start with a data model, feed it tons of data, Data models Raw data Processing and let to intelligently to feed the power it learn. classify, process, models so to drive fast, and analyze data they can keep efficient improving computing The more data the machine processes, and the more computing power it has, the faster and smarter it gets. AI for CRM: Everything You Need to Know 8

Here’s a classic example. Let’s say you want to train a machine to recognize pictures of cats. So you feed it two data points: It might conclude that a cat is Or what about this one? a furry thing with pointy ears, almond-shaped eyes, whiskers, and paws. But what happens = cat when it comes across this image? JStone / Shutterstock.com catwalker / Shutterstock.com = cat This is a cat, but without the telltale pointy ears or paws. Using only two images to “teach” a machine how to identify a cat probably wouldn’t equip that machine to accurately classify Garfield as such. However, feeding it billions of different images of cats — in nearly every color, size, and position possible — would make it much more likely to correctly classify an image like this: AI for CRM: Everything You Need to Know 9

Early data models lacked the volume of clean data taught itself how to identify an image of a cat. It was an required to perfect their data models and effectively astounding achievement for AI — and one that wouldn’t “learn.” Only recently, with the surge of data readily have been possible just a few years earlier, without easy available via the internet, do the models have access access to those millions of thumbnail images. to the data they need to get smarter. In 2009, Stanford University computer scientist Andrew Ng and Google But there was another limiting factor: processing power. Fellow Jeff Dean led a Google research team to create a In the earliest days of computing, machines filled entire massive “neural network” modeled after the human brain, rooms in university buildings. Improved ability to put more comprising thousands of processors and more than 1 transistors on integrated circuits meant processing capacity billion connections. Then, they fed the machine random doubled every two years (thank Gordon Moore and his images of cats, pulled from millions of online videos. By handy law for that observation), which packed more power identifying commonalities and filtering the images through into smaller boxes, taking computers out of universities and its brainlike neural network, the machine essentially businesses and putting them in consumers’ hands. “F eed enough cat photos into a neural net, and it can learn to identify a cat. Feed it enough photos of a cloud, and it can learn to identify a cloud.” — Wired, January 2016: “Artificial Intelligence Finally Entered Our Everyday World” AI for CRM: Everything You Need to Know 10

The personal computing era opened up a market for consumer and business software, games, gadgets, and Data upgrades. When the Internet followed the computer models out of the university and government buildings, we saw that market explode. Instant connection changed everything at an interpersonal level all the way up to an international one. Cloud computing meant companies didn’t have to worry about physical infrastructure to AI scale. The rise of mobile built on the success of Apple’s Processing Big Data iPhone and then Google Android, expanding the power market of software and games (and giving the world “the app”). Mobile also freed us from those computing nodes at home and office and, essentially, created a virtual world of communication and commerce on top of the physical one. Today, we have reached the intersection of the three ingredients needed to create true artificial intelligence: smarter data models, easy access to virtually unlimited $16.5 billion expected amounts of data, and cheap and powerful cloud computing. As mentioned previously, AI is present in our market for AI in 2019 daily lives when we search Google, ride in an Uber, or buy products on Amazon. — International Data Corp AI for CRM: Everything You Need to Know 11

CHAPTER 1 2 3 4 5 6 7 What AI Means for Business Remember how computers have gotten smaller and smarter? each other, and businesses, and consumers. We’re talking They’ve also gotten cheaper, resulting in a surge of smart about a lot of connected things: 6 billion of them that, says devices that are generating a growing body of business data Gartner, will be requesting support by 2018. Those billions that, in turn, can power machine learning. The Internet of of connected things mean huge volumes of customer data — Things encompasses an entire world of digitally connected indeed, 90 percent of the world’s data was created in the last devices — toaster, toothbrushes, thermostats, lightbulbs, cars, 12 months alone. and much more — that are now being networked, talking to AI for CRM: Everything You Need to Know 1212

Businesses need to be smart about the way they gather, digest, and apply that data, which is the lifeblood of IoT — provided it can be properly used. But the impact of AI doesn’t stop there. Behind each of those devices, of course, is a real customer — and the next generation of customers expects a cohesive, intelligent experience every time they interact with a business. When a delivery order is delayed, they expect to be contacted with an updated ETA and a make-good offer — such as a $5 credit or free shipping on their next order — without having to pick up the phone and talk to a service agent. AI makes it possible to create an entire universe of business apps to deliver smarter customer experiences across sales, service, and marketing interactions. For many businesses, however, AI has been largely out of reach. Historically, companies have faced four key challenges when it comes to adopting AI for business: Data Expertise Infrastructure Context AI for CRM: Everything You Need to Know 13

Below, we’ll explore how companies can address each of these challenges in new ways. The Data Challenge For businesses, it’s not just the volume of data that matters — it’s also how all of those critical data points are organized. Business data often resides within a hodgepodge of internal and external sources that rely on a mix of cloud and on-premise systems. Often, these systems don’t talk to each other, leading to siloed datasets and inconsistent data quality. Cloud-based CRM solutions like Salesforce are designed to connect all of that data to create a single view of each individual customer — and this connected approach to data is essential to taking advantage of the AI opportunity. The Expertise Challenge Beyond the data, companies must have the tools and expertise to analyze and act on it. This is difficult considering two common problems: siloed data storage and a scarcity of data scientists. According to a McKinsey Global Institute report, there’s a shortage of 190 thousand data scientists. Today, advances in AI tools are making it possible for businesses to work smarter without a legion of data scientists. The Infrastructure Challenge Just as discrete and siloed data sources limit companies’ ability to properly leverage their data, so too do fragmented infrastructure systems. The high cost of on-premise hardware and computing systems that have the power to run machine-learning algorithms has prevented many companies from jumping in. Now, however, cloud computing has made AI more accessible and affordable. The Context Challenge For many businesses, AI may seem not only out of reach, but also irrelevant. Popular culture has imagined AI in the image of R2D2 and C3PO, rather than an essential component of modern business processes. Read on to learn more about our vision for how AI will transform sales, service, marketing, and IT by automating mundane tasks and empowering every human employee to add more value. AI for CRM: Everything You Need to Know 14

The result of un-analyzed, underleveraged data isn’t just along a spectrum: the most basic tools require you to “pull” missed opportunity. It’s a significant failure to connect with information out of them, while the most intelligent tools modern consumers in the way they expect (and demand). “push” information to you, anticipating what you’re going Currently, half of all business decisions are made with to want to know. With machine learning, computer systems incomplete information, which disconnects the business from can take all this customer data and build on it, operating the product and, therefore, from the customer. For all the data not just on what’s been programmed but also adapting to customers are creating, less than 1% is analyzed, such that changes. Algorithms adapt to data, developing behaviors 77% of customers say they are not engaged with businesses. not programmed in advance. Learning to read and recognize context means a digital assistant could scan emails and Now, however, companies have the opportunity to change extract what it knows you’ll want to know. Inherent in this this — to close the gap between business intelligence and learning is the ability to make predictions about future customer experience. New tools reveal useful insights behavior, to know the customer more intimately, and to be about the customer. These tools illustrate how AI exists proactive rather than reactive. 6 billion connected things will proactively request support by 2018 — Gartner AI for CRM: Everything You Need to Know 15

Companies that embrace the AI opportunity will be able imagine being able to analyze every data point, pulling to create the modern experiences their customers expect, together data from Salesforce, external sources, and the connecting with them on all their devices, analyzing Internet of Things to create a complete view of every their data to get to know them better, and being able to customer. This, in turn, enables us to predict the best anticipate and predict in order to better serve them. next sales, marketing, or service interaction for each customer, and then automate everything from routine What does AI for CRM look like? Imagine being able to tasks to real-time customer engagement. It’s a whole new capture real-time signals, wherever they occur — from a way of connecting to your customers and prospects, with customer’s support request to a prospect’s tweet. Then intelligence powering a new era of customer success. AI for CRM: Everything You Need to Know 16

AI has implications for every line of business. Sales will be able to anticipate opportunities and focus on the best leads. Customer service teams will deliver the next generation of proactive service, preventing machine 61%of employees failure or addressing FAQs in a customer community before they have a chance to become service cases. expect artificial Marketing can build predictive journeys for every customer, personalizing experiences like never before. intelligence that IT can embed intelligence everywhere, creating smarter apps for employees and customers. Retailers can drive automates or assists more revenue with AI-powered insights that provide consumers with personalized shopping experiences. in work-related Read on to learn what AI means for your business. activities to have a major or moderate impact on their daily work lives — Salesforce Research AI for CRM: Everything You Need to Know 17

CHAPTER 1 2 3 4 5 6 7 Sales Smarter Sales Imagine you’re a sales rep named James. Every morning when you wake up, the first thing on your mind is all of your upcoming sales calls. However, you don’t have to think too hard because you wake up in a connected world. You check your smartphone and your CRM automatically displays an itinerary of your day. All of your key customer meetings are organized in priority of opportunity value. Your smartphone also displays each customer’s three primary pain points, along with directions to reach the customer’s site on time, already pre-programmed into your car’s GPS. A quick cup of coffee, and you’re ready to start your day. AI for CRM: Everything You Need to Know 1818

But just as you’re about to reach your first client, your smartphone sends you an important notification: a news update that your client has just acquired a data analytics company. Your sales assistant surfaces a summary of key findings from top trending news articles, along with product recommendations that integrate with your client’s recent acquisition to help you move the deal forward. Within seconds, you have full context of your deal, in-context market updates, and a conversation starter — all of which are surfaced automatically and embedded within your CRM experience. After you finish talking to your client, your smartwatch vibrates, “Great job, James! Sounds like your client liked your product recommendation. We suggest you move this deal to stage 5. Would you like me to move forward?” With a single tap, you move the opportunity from “Deal Qualified” to “Discuss Pricing.” When you return to the office, you receive a push notification reminding you, “Your meeting notes have been uploaded successfully. The system has automatically extracted the following action items, and suggests this follow-up email. Would you like to send an email to the customer now?” In one click, you’ve successfully sent an email to secure your next meeting, without manually logging customer data or key action items into your CRM. AI for CRM: Everything You Need to Know 19

Salespeople will benefit from AI in three ways: Data is automatically captured, enabling reps to “Y ou could say to your discover best next steps and closest connections phone, ‘Show me leads I’m Predictive sales helps reps prioritize leads and supposed to talk to today,’ respond faster to high-value opportunities and it does those operations Digital assistants will help maintain the for you: analyzes which ones relationship once it’s established by scheduling calls and issuing reminders are at which stage, finds the The move toward making business applications hot leads, and gives you and sales tools more accessible and relevant to our a ranking of which ones digital lifestyles will continue to expand, especially as smartwatches and other wearable devices are further you should talk to first, a integrated into our daily operations and interactions. probability of converting, User-interaction time will shorten from minutes to seconds as contextually aware push notifications bring and the expected monetary speed and intelligence to every sales experience. value when converted.” Chalenge Masekera Data Scientist, Salesforce AI for CRM: Everything You Need to Know 20

CHAPTER 1 2 3 4 5 6 7 Service Smarter Service Here’s a vision from the present: Maria orders a gift online and pays for two-day delivery to get it to her brother in time for his birthday. When she calls him on his birthday, however, she learns that the package hasn’t arrived. She calls the vendor, but has to meander through an endless series of push-button options to find the department she needs. Eventually, she ends up speaking to an agent. It’s as if none of the options she selected were recorded: She has to tell the story from the beginning. That agent transfers her to another agent, who asks her to tell him what happened — from the beginning — then puts her on hold. Ultimately, she hangs up in frustration. AI for CRM: Everything You Need to Know 2121

But with AI, service can actually anticipate a customer’s needs, rather than simply reacting to them. Long before Maria calls her brother, an AI-driven CRM would have been monitoring her package’s progress, and notified a 25% of customer service agent the moment it was delayed. That agent, in turn, could have reached out to Maria proactively, letting service leaders were her know when the package would arrive and offering her free same-day shipping on her next order. using predictive This is possible because the interaction doesn’t start analytics or when the customer picks up the phone, but rather happens on a constant, ongoing basis. The conversation best-next-action between customer and business is an interaction joined by the data the customer is producing on every digital functionality channel (from smartphone to connected devices to social media), and the solutions the company finds based in 2015 on that data. This solution may come before a problem even arises — and the customer. doesn’t have to make a — Salesforce Research call because service is right there already. AI for CRM: Everything You Need to Know 22

The AI-driven interaction will automatically recommend the customer and a superior experience that builds brand loyalty. right content to the agent at the right time, including suggested Smarter service also allows a company to identify customer solutions, relevant cases, and best next actions. The agent can churn risks and thereby prevent customer attrition. Predictive introduce these actions to the customer in an organic way, intelligence can identify customers who are at risk for churn, rather than bombarding her with offers she doesn’t need. so that reps can renew or upsell with personalized offers. Once the issue is resolved, the agent could put a note in the Feeling neglected or ignored by a company, or forced to wade customer record instructing the system to reconnect with the through inefficient systems, is a sure way to alienate customers. customer on a regular basis and suggest relevant upsell and Companies that fail to apply AI to CRM will seem hopelessly cross-sell offers when appropriate. The continuous flow of mired in the past. customer data translates into a greater understanding of the “Ev entually, helpful AI features will be on the phone, in chat, email, and any other type of communication people use. These kinds of things will become commodities, and if you have highly accurate and helpful AI, people will love your services.” Richard Socher Chief Scientist, Salesforce 23

CHAPTER 1 2 3 4 5 6 7 Marketing Smarter Marketing A new level of precision and personalization, brought about by smarter machines using data more intelligently, applies to marketing as well. An AI-enabled marketer can reach every customer at the right time, knows the best audience for every campaign, and delivers the perfect content for every customer. AI for CRM: Everything You Need to Know 2424

Today’s marketers have a wealth of data and insight at their disposal — but that doesn’t always translate into intelligent customer and prospect interactions. Traditionally, marketers have lumped audiences into 74% of marketers broad groups based on attributes like location or industry. Often, that’s because marketers don’t know enough about leveraging dynamic each person — or even if they do, it’s too labor-intensive to engage people individually with the perfect message, content (powered content, or offer. by predictive intelligence), rated it as absolutely critical or very important in helping them create cohesive customer journeys — Salesforce Research AI for CRM: Everything You Need to Know 25

The AI-enabled marketer will be able to: Leverage smart scoring to predict each customer’s likelihood to convert “L et’s say you are a Use predictive intelligence to segment and build marketer and you audiences based on likely future actions send out specific Automatically adapt the journey for each individual customer emails at specific Deliver the best next product, content, times, and you don’t or offer — every time want to go through Send messages at the right time, when a customer is most likely to engage the same repetitive “Market research” once relied on taking the temperature of steps over and over broad chunks of society. AI enables marketers to focus at a granular, individual level. This depth of audience insight again. A bot could will allow marketers to create and test campaigns virtually, ensuring the ability to target and convert audiences more do that for you.” effectively by surfacing the right offer to the right person at the right time. Chalenge Masekera Data Scientist, Salesforce AI for CRM: Everything You Need to Know 26

CHAPTER 1 2 3 4 5 6 7 Platform Smarter IT We are entering what Salesforce CIO Ross Meyercord calls “the continuum of code”: an era in which low-code and no- code platforms are becoming more robust and ubiquitous, enabling business users to be developers. This isn’t the end of code, but it does mark the democratization of app-building — an important development as apps become increasingly central to every business function. AI for CRM: Everything You Need to Know 2727

Business apps, in particular, are held to ever higher In order to enable developers — and non-developers — standards. Consumer apps are setting the bar for intuitive to build predictive apps, the best platforms must be: user interfaces, seamless integrations, and intelligent Data-Ready interactions. Business apps must be just as smart, just Platforms like Salesforce offer native as fast, and just as simple to use. Collaborating with a data prep, saving time and resources by partner or updating a sales quote should be just as easy eliminating the need for ETL. This means as hailing an Uber. So the question for IT becomes: your CRM data is ready to go whenever your How do we enable a new generation of developers — and app is. non-developers — to build more intelligent apps, faster? Modeling-Ready The answer lies in the platform. Just as Heroku enables Machine learning should be built into the fabric of your platform, rather than being developers to quickly build open-ended apps in modern something you have to add on later. With languages, so too should AI platforms enable developers Salesforce’s trusted multi-tenant cloud, to build predictive apps with minimal coding and no IT automated machine learning is already hassle. With the power of AI, citizen data scientists can built in. embrace low-code solutions and build any predictive app they dream up, even CRM-driven apps like fraud detection Production-Ready Eliminate the need for dev ops with smart or risk scoring. model management and monitoring tools, so IT can focus on building the best apps and deliver immediate results. With an AI-first platform like Salesforce, companies can build intelligent apps across the entire continuum of code — and rest assured that intelligent data modeling, tracking, and monitoring are built into every app. AI for CRM: Everything You Need to Know 28

CHAPTER 1 2 3 4 5 6 7 Commerce Smarter Commerce As you can see, AI is already changing the way we connect to customers in profound and positive ways. The retail industry, in particular, has been significantly impacted by this technology. AI for CRM: Everything You Need to Know 2929

Shopper needs change each time they shop. AI detects these changes and personalizes the experience based on real-time shopper clicks. For example, if a customer “P ersonalization is king these begins shopping for a swimsuit, the website may assume that she is going on a beach vacation and can make days, so anything we can personalized recommendations of other items she may personalize we’re going to need: flip flops, a hat, or a beach towel. look into, especially if we For the shopper, this is a more efficient shopping don’t have to go with an experience, minimizing scrolling and searching, especially on a mobile device. outside provider. We really For the retailer, it cuts out the guessing game and the trust Salesforce.” tedious manual merchandising process. But most important of all, it increases the bottom line by driving Adam Smart conversion and average order value. Senior Web Merchant, Black Diamond AI for CRM: Everything You Need to Know 3030

With AI, retailers and brands can can tap into the power of data to deliver: Personalized product recommendations Icebreaker found that throughout the ecommerce site and in store its shoppers clicked on Data driven insights that power smarter Commerce Cloud powered merchandising, product bundles, promotions, and Product Recommendations store planning 40% more often, leading Optimized search results and category pages for to 28% more revenue from each unique shopper --anonymous or logged in recommended products and an 11% overall Implementing AI is easier than you think. You don’t have increase in average order to be a data scientist! AI features are directly embedded into the Commerce Cloud to empower retailers and brands value (AOV). to supercharge one-to-one personalization across the entire buying journey. Retailers finally have access to their customer data, enabling smarter merchandising decisions and even the automation of manual tasks such as grid merchandising and search term optimization. 31

Conclusion Customer-Focused AI: Salesforce Einstein AI for everyone. “The bea uty of Salesforce is that it has tons of different applications across various verticals At Salesforce, we’ve focused on creating a set of AI platform services and solving customer problems across and lines of business: marketing, sales, service, sales, service, marketing, and IT in a whole new way. IoT, healthcare, and so on. Salesforce touches on so many different areas and has a general With Salesforce Einstein, we are solving for these kinds platform. Hence when we solve a problem of questions: once in a principled way the solution can be Are you selling the right product to the right applied to so many different companies, customer at the right time? improving their processes and helping them Are you servicing customers on the right focus on what’s actually important and exciting. channel by the right agent? For example, a customer service expert can Are you marketing on the right channel at focus on helping you with tough questions the right time with the best content? specific to your org — and not on how to recover Are you building apps that leverage the a forgotten password for the 50th time.” predictive power of AI? Richard Socher Are you delivering a smart and Chief Scientist, Salesforce personalized shopping experience? 32

AI Has the Power to Transform CRM SALES SERVICE MARKETING Sales Service Marketing • Spends time visiting customers, • Recommends a solution before • Can reach every customer at the not entering data a customer asks right time • Predicts the best next step for • Offers cross-sells and upsells at • Knows the best audience for every customer the right time every campaign • Understands what customers • Predicts when things will break, • Delivers the perfect content for need and when they need it before they do every customer IT COMMERCE Lightning Commerce • Can build predictive, smarter apps • Offers shoppers personalized product — faster recommendations • Leverages the power of open-source • Empowers retailers with data driven frameworks insights for smarter merchandising • Empowers everyone to build with AI, • Drives smarter search results and faster category pages for every shopper AI for CRM: Everything You Need to Know 33

Salesforce Einstein enables everyone to discover new Given our scalability and deep understanding of CRM, insights; predicts likely outcomes to power smarter decision- Salesforce is uniquely positioned to deliver AI that making; recommends best next steps; and automates transforms the customer experience. Einstein makes AI workflows so you can focus on building meaningful available to the rest of us by: relationships with every customer. It’s not bolted onto Salesforce — it’s an integral part of our platform. Salesforce 1) Democratizing AI so every business user can get smarter Einstein enables every business user to: and more predictive Discover. With AI inside of Salesforce, sales reps, 2) Bringing intelligence to all Salesforce apps and making service agents, and marketers will discover new the Customer Success Platform smarter insights about customers, faster and more easily. Predict. Knowing the likely outcome of a series of 3) Allowing developers to embed intelligence in every app interactions gives you an AI-powered competitive Customers will now experience the pervasive benefits of advantage. automated workflows, timely and relevant suggestions, and Recommend. What’s the next best step in a sales adaptive applications throughout every customer touch- process, a customer service case, or a marketing point across Sales, Service, Marketing, and IT to redefine nurture journey? AI offers it up so you can focus on customer success as we know it today — so that it looks the relationship. more like tomorrow. Automate. When certain processes are repeated over and over with the same solution, often that task can be automated. AI learns from past actions and automates those tasks. Visit Einstein.com Salesforce Einstein is the first comprehensive AI for CRM, to learn more. designed to help every business be smarter and more predictive about their customers. Einstein is powered by machine learning, deep learning, predictive analytics, natural language processing, and data mining. AI for CRM: Everything You Need to Know 34

Rights of ALBERT EINSTEIN are used with permission of The Hebrew University of Jerusalem. Represented exclusively by Greenlight. The information provided in this e-book is strictly for the convenience of our customers and is for general informational purposes only. Publication by salesforce.com does not constitute an endorsement. Salesforce.com does not warrant the accuracy or completeness of any information, text, graphics, links, or other items contained within this e-book. Salesforce.com does not guarantee you will achieve any specific results if you follow any advice in the e-book. It may be advisable for you to consult with a professional such as a lawyer, accountant, architect, business advisor, or professional engineer to get specific advice that applies to your specific situation. © 2017 salesforce.com, inc. All rights reserved.