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How AI Helps Brands Create Customer Empathy at Scale

Machine learning and automation are critical for brands today to turn big data into empathetic customer-centric experiences.

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empathetic customer experiences

To win the hearts and minds of today’s customers, brands today need to establish a foundation of empathy and genuine connection with their customers. Artificial intelligence (AI) and human-focused marketing may at first glance seem like complete opposites. However, machine learning and automation are critical for brands today to turn big data into empathetic customer-centric experiences. AI technology serves as a scalable empathy engine, that works to understand the context and intention behind each individual customer interaction. Empathy occurs when brands tap into each individual customer's wants and motivations and connects with them on a deeper level than just a one-off exchange of value. 

At Acquia Engage 2020, Marci Maddox, Research Director, Enterprise Content Strategies, at IDC, presented the session “Uniting Content & Data for Empathy at Scale” to discuss how infusing data and content across the entire customer journey will allow brands to see the world from their customer’s eyes and treat every action as part of a growing relationship, not a series of transactional exchanges.

Today’s customers have more sophisticated demands for digital experiences, and COVID-19 raised these standards even higher. It’s not enough to just have the information about what your customer has done, but businesses need to step into their customer’s shoes and anticipate their future needs or wants. Accomplishing this means analyzing your data to detect wider patterns and changes in preferences. Brands are learning that they cannot wait around for data scientists to explain what customers are telling them. They need to be active listeners and respond in real time. “Data literacy is your new central nervous system to how customer experience is built,” said Marci. You can achieve empathy in marketing by starting from a customer-centric viewpoint and acting on that insight to reflect what you’ve learned about that customer. 

However, with more interaction points, content types and digital moments in the mix, predicting customer behavior and the next best action to take becomes increasingly complicated. With billions of potential experiences to choose from, selecting the best sequence of events is an impossible task for a human to accomplish on their own. That’s why machine learning and artificial intelligence are the key to infusing empathy across all of your business functions. 

The Growth of Artificial Intelligence to Guide the Digital Experience Economy

A customer data platform (CDP) that leverages machine learning can help brands make sense of enormous volumes of customer data across multiple channels and offer sophisticated recommendations based on past customer interactions. Already, most businesses understand the importance of acquiring customer data and using analytics to inform their marketing strategy and know who their customers are. However, simply having a large swath of data points coming in from different sources isn’t enough to build a valuable and trustworthy relationship with your customers. The next step to achieving empathy at scale is to blend data intelligence with prescriptive AI and predictive machine learning techniques to get a view of your customers that extends beyond just one touchpoint and encompasses all of their previous history with your brand, whether that was on your website, browsing in-person or leaving a review on social media. Only once you’ve built this 360-degree view of the customer are you able to work toward improving each future interaction.

Today’s customers have more sophisticated demands for digital experiences, and COVID-19 raised these standards even higher. It’s not enough to just have the information about what your customer has done, but businesses need to step into their customer’s shoes and anticipate their future needs or wants. Accomplishing this means analyzing your data to detect wider patterns and changes in preferences. 

 

  • Is this customer a long-time in-store shopper who suddenly has been browsing your e-commerce site due to widespread store closures? Acknowledge their adjustment with a free shipping offer to lessen the inconvenience of needing to change their shopping channel to online. 
  • Has this customer showed a strong interest in a luxury item by repeatedly viewing it without purchasing it? AI can detect their pattern of behavior and alert them to a price drop for this item through a SMS notification.   
  • Has this customer recently called your customer service hotline to report a delayed package or wrongly delivered item? Send them an exclusive free shipping “apology” code for their next order.  

 

All of these actions go beyond customer acquisition and help you build trust with your customers. This kind of data-driven insight is simple to achieve with a CDP that leverages machine learning and unites data from across all customer touch points to shape a vision of your customers in real time. Predictive machine learning models allow marketers to be more proactive by aggregating and generating insights and recommendations from all your customer data. 

When a person trusts that a brand is using their data in a thoughtful and intentional way, rather than to just drive a sale, they are more likely to offer that brand more data to inform experiences in the future. Each meaningful experience will continuously generate more value for both the organization and the customer. This is why AI is the fuel in establishing an empathy engine at scale that will grow deeper connections and foster long-term customer loyalty.  

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See how you can reimagine customer loyalty and boost revenue in our e-book: Who Are Your Best Customers? Rethinking Customer Loyalty in a Digital-First World.

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