According to the latest Gartner Technology Marketing Survey, 14 percent of martech leaders are already deploying generative AI (GenAI), and 63 percent plan to within the next two years. Those who have deployed GenAI have reported increases in productivity across several proven use cases, including content creation and next-best action optimization. GenAI, says Gartner, will evolve rapidly in both capability and commercialization, enabling brands to effectively reach prospects and customers as an “essential part of the fabric of marketing.”

What does this mean for the use of GenAI specifically in the context of a customer data platform (CDP) for the purposes of simplifying a marketer’s job or to improve upon core functionality of collecting and storing data, performing data cleansing, enrichment and identity resolution, building a Golden Record, segmentation and activation?

If the overall purpose of a CDP is to develop a better understanding of a customer to enable a more personalized customer experience (CX), GenAI helps accomplish that goal in several ways. First, GenAI can be a valuable tool in helping to build, enhance and maintain a Golden Record, working with machine learning models to understand the context and relationships between data points, analyzing customer data details, and leveraging a deep understanding to improve match and merge accuracy.

Simplified Segmentation with GenAI

Second, GenAI augments the democratization of customer data available and accessible across the organization. It does this by significantly reducing both the amount of time and number of iterations for building audience segments. Even without GenAI, a robust, enterprise-grade CDP should already provide marketers with a no-code environment with which to build and refine dynamic segments – minimizing the dependency on data scientists and IT teams. With GenAI, the process is simplified even more through a natural language interface and the use of large language models (LLMs) to allow marketers to ask questions about their customer data.

A marketer might use a conversational interface to generate an audience, for instance, by saying “Build me a segment of Midwesterners who expressed an interest in an outdoor gas firepit over the last six months.” The marketer might also ask probing follow-up questions. Which of these customers also expressed an interest in patio furniture? Which have an average annual spend of over $1,000? How many have a natural gas line into the house? Perhaps the marketer, failing to see anything unusual or interesting in the dataset, asks the model to probe further, “tell me something about this audience that will maximize value in an email campaign that offers a free set of decorative lava stones for a purchase of a firepit over $500.” Using GenAI simplifies the identification of patterns, trends and correlations that a marketer might otherwise miss, and it does so in a fraction of the time it would take versus either having to write code, or even use a standard drag-and-drop UI. Generating segments and producing better segment insights is a prime GenAI use case for a CDP, which falls into what Gartner deems high-value, high-feasibility in its GenAI use case prism for marketing in the category of content co-pilot.

An Activation Assist Using GenAI

Third, when it comes to data activation, GenAI can be indispensable in helping to generate personalized content for different segments and ensuring that the chosen messaging resonates. Familiar content assets include email content, social media posts and website personalization, and a marketer might ask a GenAI framework to “create five email subject lines for our fire pit campaign that fit our brand voice and would appeal to Gen X buyers.” Similarly, GenAI can be a valuable tool in predicting the right channel and the right time to engage with a customer, and in generating real-time recommendations such as product recommendations and upsell or cross-sell opportunities.

On the activation front, GenAI can accomplish these tasks in an automated way, or through natural language conversations with a marketer using GenAI to help refine chosen content, analyze response data, or create follow-up messages.

The throughline with using GenAI to augment core CD functionality is that better data yields better results. Whether it’s building a more trustworthy Golden Record, generating dynamic segments or activating data to different end channels, GenAI ensures that marketers are working with cleansed, accurate and fit-for-purpose data as well as a deeper understanding of the customer.

To learn about how the Redpoint CDP leverages GenAI to generate a deeper customer understanding and to help marketers more easily perform their day-to-day tasks, click here.