Supercharge your Personalization Game with Gen AI

Personalization at scale has always been a challenge for marketers managing large customer data sets. Significant resources are being allocated to it, and this trend is only accelerating. CMOs—both in enterprise and mid-market organizations—have faced challenges in enabling personalization across diverse customer segments effectively.

With Generative AI (Gen AI), marketing teams can now create sufficiently personalized content with impressive granularity. Over the past three months, I’ve had the chance to explore this technology with brands that have customer bases of around 250K. We used a model like LLAMA to generate segment-level personalization, and the results are promising. For most marketers, this level of segmentation is more than enough unless you’re equipped to go ultra-granular at an enterprise level.

In this piece, I’ll share how CMOs can leverage Gen AI to streamline their personalization strategies, regardless of their existing tech stack. We’re assuming that you at least have a basic Customer Data Platform (CDP) in place and are using it to drive campaigns.

Why is Gen AI a Game Changer?

Let’s be clear - Gen AI is a game changer. Personalization has historically required significant manual effort, restricting marketing teams to broad segments rather than more granular personas. As audience expectations grow, the ability to deliver increasingly personalized experiences becomes critical.

If your team has sizable customer data, Gen AI transforms the playing field. By leveraging AI models, teams can generate content that speaks directly to specific audiences based on their preferences, past behaviors, and predicted needs—at scale. That’s the revolutionary part.

But how can you implement it? You don’t need to overhaul your existing stack. Here’s a step-by-step guide to creating a scalable, Gen AI-powered content generation process. Let’s dive in. everage Gen AI to streamline their personalization strategies, regardless of their existing tech stack. We’re assuming that you at least have a basic Customer Data Platform (CDP) in place and are using it to drive campaigns.

1. Centralize and Analyze Your Customer Data

Before AI can generate personalized content, it needs to understand your audience. Start by centralizing your customer data. Whether through your CDP or another data repository, gather key insights such as:

- Purchase history

- Browsing behavior

- Demographics

- Engagement metrics (e.g., email clicks, social media interactions)

Centralizing this data allows AI models to personalize content at a micro-segment or individual level.

2. Segment and Summarize Customer Data

Once your customer data is centralized, define your customer segments. These segments could be based on factors like customer lifetime value (CLV), product preferences, or discount sensitivity. For example, you could create a segment for high-value customers who frequently buy outdoor gear.

Summarizing key attributes of each segment, such as a preference for ski-related products, will guide the AI in crafting content tailored to those interests.

3. Design Your AI Prompts

This is where the Gen AI magic happens. Crafting the right prompts for your AI model is crucial. Smart prompting ensures that the AI generates content that fits your audience’s needs.

Key considerations for designing effective AI prompts:

• Define the role of the AI (e.g., “You are a knowledgeable sales associate describing this product”).

• Provide clear guidance on how to integrate customer data (e.g., “Use customer preferences for outdoor gear when writing product descriptions”).

• Include corrective measures to prevent inaccuracies (e.g., “Write for the entire segment, not a single individual”).

Here’s an example of a well-constructed prompt open:

"Imagine you are a customer service representative at a retail store. Your task is to use details from the {segment_profile} to adapt the standard product description to match the interests of this segment. Incorporate relevant information like product preferences, pricing sensitivities, and regional trends to make the description more appealing. Craft the content in an engaging, approachable manner that resonates with this group. Since this content is meant for a broad customer segment, avoid references to individuals. Ensure the final copy is clear, persuasive, and encourages action."

Many vendors offer Prompt Playgrounds—use these to refine your prompts until they consistently deliver the results you want. Here is one from Databricks for their customers.

4. Generate and Test Your Content

With your AI model and prompts in place, you can start generating personalized content for each customer segment. Whether it’s product descriptions, email subject lines, or ad copy, AI can automate content creation at a scale that manual processes simply can’t achieve.

However, be sure to test the output. AI-generated content often benefits from a human touch to ensure accuracy, tone, and alignment with brand voice. A human-in-the-loop review process is key to ensuring high-quality results before rolling it out across channels.

5. Automate and Scale the Process

Once you’re confident in the quality of your AI-generated content, it’s time to automate. Many marketing platforms integrate with AI solutions, allowing you to automate content generation across email marketing, website personalization, and more.

The power of Generative AI lies in its scalability. As you refine your AI models and gather more data, the system continuously improves, allowing your marketing team to deliver even more personalized and accurate content over time.

6. Measure, Refine, and Optimize

Like any marketing initiative, AI-driven personalization should be continuously measured and optimized. Track metrics such as engagement rates, conversion rates, and customer feedback. These insights will help you refine your AI models and improve future content output.

AI’s ability to learn from data makes it incredibly powerful. The more data you feed into the system, the more nuanced and effective your content becomes.

Finally. CMOs, Take Note:

Generative AI is a transformative tool that allows you to deliver highly personalized content at scale. By combining AI with rich customer data, marketing teams can generate content that resonates with individuals, driving engagement, conversions, and customer loyalty.

Whether you have enterprise-level tools or not, the steps outlined here will help you create a Gen AI workflow that fits your needs. You don’t need to invest heavily upfront—start experimenting with what you have. Get our hands dirty. Believe me, you and your audiences will start smiling soon enough! I guarantee it.