Using Generative AI to Create Marketing Segments of One

AI - Personalization

Generative AI can predict customer needs and drive ultra-personalized marketing and communication.

Nearly 90% of customers say the experience a company provides is as important as its products or services, according to data from Salesforce. 85% of customers expect consistent interactions across company departments, and 56% expect offers to always be personalized.

That means brands can’t design the customer experience; they have to design each customer’s experience.

There’s plenty of incentive for brands to deliver. Shoppers who click on personalized recommendations have 26% higher order values, on average, compared with those who don’t, according to Bain. And businesses that focus on being loyalty leaders (instead of on short-term gains) grow revenue nearly 2.5 times faster than their industry peers.

Customers and companies want the same thing. Yet personalization has remained a missed opportunity for most brands. Until now.

Generative AI closes the capability gap

With advances in generative artificial intelligence (AI), it just got easier to create ultra-personal experiences. Generative AI tools like ChatGPT, Dall·E, and Codex use sophisticated machine learning to produce original content, almost instantly.

In a recent NPSx webinar, Bain Partners Jeff Katzin and Rob Levy offered four ways to use generative AI to create more-personalized CX.

  1. Customer activation. Generative AI can blend structured and unstructured data and use it to recommend products in a natural way. Demographic information like age, income level, and customer value can be combined with transaction data or social media behavior. The result is a truly personalized recommendation or offer. Customers aren’t presented with products they already own, have already rejected, or don’t qualify for.

  2. Closed loop communication. When a customer interacts with a contact center, generative AI can transcribe the conversation, distill it into a short recap, and generate an email or script. Relevant imagery, links, and ad copy can be inserted into customer messages to tailor the communication even further. Brands can deliver personal follow up messages, without spending hours to prepare them. That means every customer can receive a prompt, personalized response to their question or issue.

  3. Advisor copilots. In the B2B space, companies can use generative AI tools to amplify their CRMs and sales capabilities. OpenAI tools accommodate multiple modalities. So, in one platform, an advisor could have links to recent articles about the customer, meeting transcripts saved as natural text, AI tools to summarize meetings and action items, and an API that’s linked to the company’s email tool. Advisors also get coaching from AI. It can spot recurring questions or suggest offers that have been successful.

  4. Advanced chat bots. Right now, most chat bots are programmed based on decisioning trees. Customers in “Segment A” or with “Issue B” are served up a standard response—which is often a link to webpage or their account login. They’re punted to another channel or self-service instead of reaching a resolution. But now, decisioning can be layered on top of chat bot capabilities. If a customer reaches out because of a bill, AI can dynamically incorporate account information and explain, in natural language, why a bill was higher than normal. And based on the tenure or value of the customer, it can offer a tailored resolution. With generative AI, CX can be delivered at the individual level, instead of the segment level.

AI will not replace every person-to-person interaction. And it won’t dilute the personality of your brand. Humans are still in charge of training AI and set the guardrails around voice, syntax, and tone. You can train AI to deliver personalized CX faster, more efficiently, and more consistently than you’re doing right now. And that’s what everyone wants: customers, companies, and shareholders.

 

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About the Author

Evan Brennan-Johnson

Communications Manager, NPSx