Speaker 0: Welcome, everyone. Today, we are diving into the topic that’s redefining how businesses connect with their customers, elevating customer experience with the data, AI, and CRM in the AI era. My name is Vandana Naik, and as a field CTO at Salesforce, I have seen firsthand how powerful these tools can be in transforming customer relationships. In a world where expectations are higher than ever, it’s no longer enough to simply meet customer needs. We need to add speed them, personalize every interaction, and create seamless experiences across every channel. That’s exactly what we’ll explore today. How combining data, AI, and CRM can help us not just keep up, but truly lead in delivering unforgettable customer experiences. Let’s get started.

And before we jump in, thanks to our incredible sponsors for this opportunity. Today, we are going to explore how data and AI can transform customer experiences at every touch point. First, we will look at how these technologies help us create seamless personalized interactions that meet high level expectations of today’s customers. Then we’ll dive into building their strong data and AI strategy, addressing common challenges, leveraging the data flywheel, and using different types of AI to drive meaningful engagement. Finally, we’ll bring it all together by showing practical applications across the customer lifecycle. Let’s get started.

So the AI opportunity is huge. Imagine freeing up 30% of your team’s time. That’s the power of AI, taking repetitive tasks off our hands so we can focus on what really matters. And it’s not just about saving time. AI is reshaping how we connect with our customers. 84% of leaders say it’s helping them sell customers better, bringing personalization and speed that today’s customers expect. And here is the big picture. AI is set to add a massive $4,400,000,000,000 to the economy, fueling growth, creating jobs, and driving innovation. So AI isn’t just a tool. It’s a game changer for productivity, customer success, and growth.

Today’s customers expect every interaction with the brand to be seamless and personalized as the best experience they have ever had, whether it’s ordering a coffee or streaming their favorite show. In fact, there is a saying that captures it really perfectly. That last best experience that anyone has anywhere becomes the minimum expectation for the experiences they want everywhere. Isn’t that true? We all want that. Right? But there is a challenge here. Research shows 81% of the customers expect companies to anticipate and adapt to their needs. They want businesses to know them, understand them, and respond proactively. And when we ask customers if companies are actually meeting these expectations, the reality falls short. Only 54% of the customers feel that the brands are delivering on their products. That’s a significant gap between what customers expect and what companies are able to provide today. This disconnect represents both challenge and an opportunity. It’s a clear signal that customers want more. They want experiences that are personalized, seamless, and effortless. So the question is, how do we bridge this gap? How do we elevate every interaction to meet and even exceed these expectations? And that’s where data, AI, CRM come together. By using data strategically, powered by AI insights, and supported by a unified CRM, we have the tools to close this gap and turn customer expectations into realities.

Let’s look at how we can make this all happen. So how do you drive that personalization? How do you ensure your company provides those experiences to customers that would make them love your brand? But wait. What is critical for these personalized experiences? That’s right. It’s data. You have heard data is the new oil in the world of AI. It’s a fascinating concept. It’s very similar to a child learning to identify animals. Their parents show them pictures of different animals and tell them what each one is. Over the time, the children are able to identify animals on their own. This is how humans learn, and this is not too far different than how AI learns. Data is the teacher that is helping AI basically to learn. AI uses algorithms and statistical tasks to perform the, uh, actions. To do this, AI needs to learn from data. This process is called training. More diverse complete data and better AI becomes its tasks. And data needs to be secured. It needs to be clean. You need to know that data you are leveraging is clean and accurate, and it’s timely. It needs to be right data at the right time, at the right place, right channel.

And then once you have the data, that’s when the AI comes in. And it’s there are different flavors of AI. There’s predictive AI, generative AI. Predictive, all about using historical data to basically come up with the recommendations. When you go to Netflix, what movie are you going to like? That’s a good example of predict AI. And generative, on the other hand, helps generate content. And you use AI models, different AI models, depending on the business needs. And then it all comes down to where do you render those personalized experiences, be it in CRM application, be it on the website, mobile, SMS, any of those all different touch points providing those personalized experiences, be it through channels, be it through humans, or it could be through the agents, digital worker. That’s the new third wave of AI, which is all about augmenting humans with the digital workers.

Then moving on, imagine how do we really build that interaction with the data through data flywheel? This is where we use basically start by collecting the customer data. It’s all the data that is sitting in different systems, structured data, unstructured data, such as social media comments, knowledge articles, voice recording, videos, images, all that collecting all that data that is rich and that you can use to gain insights. Then we move into the right, which is about unifying data into a single view of customer. That way you are able to identify the customer irrespective of what channel they are shopping at or what channel they’re interacting with, what email IDs they have used, irrespective of different short names they have used or different addresses they might have used or variation of all of this. And then finally, activating those AI driven insights. Once you are able to unify all that customer data and you know everything about the customer, you can then use AI to gain insights about the customer and then activate them. And then based on the outcome, you basically learn that way. It becomes it’s in a loop as over time you optimize the engagement. So basically, we use data to get even smarter. The brand tracks how customers are responding for the insights that were rendered. And over time, it’s basically either improving and making it better or it’s ignoring certain thinking if the outcome is not what was expected.

So we are building more than just a customer engine. We are building a powerful data platform. And as we saw in the prior slide about data fly available continuously collecting, unifying, activating, and optimizing the insights, all designed to elevate customer experience. Now let’s take a look at how it really works. What you see here is three different things. First thing is about data. This is where about unifying the data. Salesforce Data Cloud provides tools to bring data from all different systems through out of the box connectors, including data that might be sitting in SharePoint, or it could be Excel spreadsheet. There’s a or a legacy system. Doesn’t matter where the data is sitting. We have tools to bring that data in. And for unstructured data, Data Cloud provides vector database where you can chunk and load the unstructured data and gain insights from that unstructured data as well.

And on top of it, you have different AI tools that are helping you with visualization, providing actionable insights, helping you with the natural language processing so you can talk to the data. You can segment your audience, learn more about it, and also generate content, which could be generating messages, generating replies, email replies, or it could be generating call summaries, even generating images. All the different AI capabilities we provide.

And on top then, finally, it’s like using this data, using the insights to personalize the moments. So personalize the moments on multichannel journeys, or it could be a sales conversation, commerce transactions, or loyalty across all different touch points irref irrespective of what stage the customer is in. That’s the tool Salesforce provides that is taking bringing data, AI, CRM all together in one platform.

So how does Salesforce data cloud help retailers address the data, all the data challenges and real time providing those real time experiences? So our Salesforce approach goes beyond the initial consumer interest, which which is like ChargeGPT. Enterprise AI is very different than using ChargeGPT. So it’s about giving companies a secure platform to build on. This is where predictive AI or generative AI or autonomous AI all come into play. So with the enterprise AI strategy, we are using AI to directly help and serve our customers better. And as you see, there are several examples of different kind of AI. It’s not one or the other. It’s all working together to meet specific business requirements.

And also what we are thinking about is from a human our goal is to have both our assistive and autonomous agents to maximize human potential for any organization. This is where Salesforce announced Agent Force, which is designed to augment human capabilities, making employees more efficient and productive as well as augment the organization by automating things.

So how does agent force work? Our goal is basically to take that natural language prompt or utterance and, yeah, agent will be able to process that. And it uses knowledge to determine what really needs to be done against the prompt or utterance that was pro supported by the customer. And then we define the actions. What are the actions the agent can take? The way actions work is they’re different than the chatbots, where chatbot, you have to code every individual, uh, rule. Everything the customer could ask for, everything had to be coded. But with agents, it’s natural language processing, and our reasoning engine is able to process that and interpret that request and ask follow-up questions and perform action. Actions could be creating a case, placing an order, initiating a return, any of these different actions. And, also, agents have guardrails. That way you can ensure that the agents are not performing tasks that they are not supposed to. And then it uses different models to come up with the plan and performs the action.

So how does it all come together? We spoke about several things. We spoke about using the data, using AI, using CRM, different channels, customer touch points about personalizing those interactions. And this is where Salesforce platform brings it all together. What you see in the center is the data cloud. That’s heart of the AI processing. It surfaces relevant data to humans and agents and also through all the customer three sixty applications you are familiar with. So Salesforce platform brings it all together. How does it do that? It starts with the Salesforce platform that is built to address all the needs around security, compliance, data residency. And then you have data cloud, which basically surfaces trusted data to humans and agents. That way, the interactions are going to be easy and just realized as data cloud provides that context for AI to use that, uh, data and provide relevant information. And on top, you have the agents that are helping. It could be self-service agents or assistive agents helping customers have those personalized experiences.

So we saw different things around data AI. How does it all work together in a for a customer? Customers go through different life cycle starting with the awareness phase. AI helps us identify and reach high audience, uh, right audience more effectively. Imagine a customer who is browsing online product that’s similar to what you’re selling With the targeted advise advertising and look alike modeling, we can place relevant products in front of them just when they are most interested. We are not just getting their attention. We are increasing the likelihood that they will connect with our brand from the start.

And then first, the awareness phase is the, uh, conversion phase. This is when AI allows us to create a smooth and tailored shopping experience. Think about a customer who is exploring options and maybe even hesitating on a purchase. We can use AI to follow-up with personalized offers, reminders, or even related product recommendations that encourage them to complete their journey. This kind of timely personalization makes all the difference in converting interest into action.

Next comes engagement. AI empowers sales teams to reach out with insights that make conversations relevant and impactful. For example, our predictive tools enable sales rep to recommend products that align with customers’ unique interest, increasing both engagement and average order value. It’s about building relationships that feel meaningful and personalized.

Then we have the retention, where proactive service is a key, using AI to anticipate issues like restocking a popular item or notifying customers about potential delay in shipping their item. These things lets us address their needs before they even reach out. This builds trust, reduces returns, and keeps them coming back. It’s about showing that we are not just here for the sale. We are here for the long haul, committed to making every interaction with the customer valuable.

And finally, it’s about loyalty, where AI helps deepen the connections with our most engaged customers. We can reward top referrals or recognize VIPs with special offers and personalized loyalty programs based on each customer’s preference. These actions aren’t just transactional. They create sense of belonging, turning satisfied customers into advocates who drive our brand’s value.

So as we bring this session to a close, think about how these use cases illustrate the potential of data, AI, and CRM across every stage of the customer life cycle irrespective of what business it is. With the right strategy, we are not only meeting our customers where they are, we are enhancing every step of their journey, building relationships that last. The future of customer experience is here, and it’s powered by seamless integration of data, AI, and CRM. Thank you.