The way we connect with customers is changing. Kim Rae laxide Learn what brands need to do to take advantage of AI-enabled CRM tools.
Data is at the heart of a good AI-enabled CRM strategy, explains Le (Christiann Koepek/Unsplash)
Automation is firmly embedded in modern marketing, allowing organizations to manage and personalize marketing communications throughout the customer lifecycle. Brands can now send triggered communications based on customer behavior, but artificial intelligence appears to be taking this to a whole new level. By combining AI and market automation, marketers can identify customer behavioral patterns across multiple touchpoints and automatically personalize messaging content.
Many e-commerce brands are increasingly integrating marketing automation into their CRM strategies as a core driver of revenue, repeat purchases, and customer lifetime value. They are building automated lifecycle journeys that communicate with customers at key moments in their relationship with a brand. Importantly, advances in generative AI and machine learning are now enabling brands to automate highly personalized email experiences at these critical moments through CRM.
As consumer behavior and expectations change, CRM is expanding beyond email to managing multichannel, personalized communications across touchpoints that customers actually interact with, such as SMS and push notifications. However, email is still the backbone of CRM. Triggered email programs are often the best-performing campaigns in e-commerce CRMs because they directly respond to customer behavior.
Although AI enables advanced personalization, strong segmentation remains the core of an effective CRM strategy. This ensures that your messages are relevant to different customer groups, rather than treating all customers the same. Modern e-commerce segmentation, enabled by AI, increasingly incorporates behavioral and predictive data.
Laying the foundation for effective segmentation means building the structure, data, and strategy needed to divide a broad audience into meaningful groups that can be targeted.
These are five key steps to establishing that foundation.
Evaluate how data is integrated across data collection points and systems
Before you can personalize communications with CRM, you need to understand where your customer data comes from and how it’s connected.
Most e-commerce brands collect customer data across multiple systems, including e-commerce platforms, marketing automation and email tools, loyalty programs, and customer service systems. Without proper integration, these systems create data silos.
Reviewing your data collection points can help you identify where customer data is generated, how it flows between systems, and which teams have access to it. Many organizations are moving to a single customer view, where behavioral, transactional, and engagement data is unified to automate more precise personalization across channels.
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Common issues to resolve at this stage include the sign-up form not capturing data correctly, the form being missing, or the form not being GDPR compliant.
Understand data availability and compliance
Effective CRM relies on responsible use of customer data. Brands must ensure they are collecting and using customer data in a way that is both transparent and compliant. Regulations such as GDPR allow businesses to ensure clear customer consent to communications, defined data retention policies, and transparent privacy policies.
Brands should also consider internal access and governance. Which teams have access to customer data? What systems is it stored on? How is the data protected?
As AI tools increasingly analyze customer data, data governance becomes even more important to ensure personalization strategies are ethical and compliant. Transparent data practices build trust and strengthen customer relationships. This increases their willingness to share information.
Analyze organized data to uncover meaningful segments
Once data is unified and accessible, AI-powered tools can be used to analyze large amounts of customer data and identify meaningful patterns. Through behavioral segmentation, you can identify groups of customers with common characteristics, purchasing behaviors, or engagement patterns.
Common analytical approaches include RFM analysis, which assigns a score to each customer on three dimensions: recency, frequency, and monetary value. This provides a powerful demonstration of customer value and loyalty and allows for targeted marketing. for example, laxideThe RFM segments are “Loyal Customers,” “Champions,” “Can’t Lose Them,” “Prospective Customers,” “Hibernating,” “New Customers,” and “Sleeping.”
Cohort analysis, on the other hand, groups customers based on a shared experience, such as month of first purchase or month of sign-up. This helps you understand how retention and lifetime value change over time. Additionally, a behavioral approach segments customers based on how they interact with your brand, including browsing patterns, email engagement, and product preferences.
Develop clear segment profiles and goals
Once your segments are identified, you can translate them into clear marketing strategies. The key segmentation approaches that underpin AI-enabled CRM are:
Demographic segmentation is the first major segmentation approach that underpins AI-enabled CRM. Group customers using attributes such as age, location, income, and gender. This data is basic, but provides important context.
Psychographic segmentation focuses on your customers’ values, interests, and lifestyle. This approach is especially effective for brand storytelling and loyalty messaging. Behavioral segmentation is also based on how customers interact with your brand, making it one of the most effective tools for improving retention. Common behavioral segments include loyal subscribers, repeat customers, high-value customers, and at-risk customers.
Predictive segmentation, which uses historical data to predict future behavior, and preference-based segmentation, which focuses on how customers choose to interact with a brand, are two further approaches.
Segmentation is only valuable if each segment has a defined role and purpose within your CRM strategy. These typically include conversion, retention, loyalty, driving second purchases, and re-engagement.
Incorporate segmentation into your decisions and strategy
Segmentation should shape marketing decisions across your organization, not just your CRM campaigns. The value of segmentation really increases when it is incorporated into broader marketing plans that inform campaign targeting, content development, product recommendations, channel selection, and more. An AI-powered CRM platform can operationalize this by dynamically choosing what content to display, which products to recommend, and which channels to use.
For more and more companies, CRM is of A platform for modern marketing. This enables powerful, automated, and personalized marketing communications at scale. The application of AI will enable CRM to better understand consumers and become even more valuable as a strategic marketing tool. But like any martech, a platform is only as good as the data it provides and how you use the technology to fuel your marketing strategy.
