Learn and master Clay with Clay university

We talked about the philosophy behind Create, how AI helps distill large amounts of data into high-quality, focused content. Now it's time to put that into practice.

In this lesson, we'll show you how to create personalized content at scale using modular AI Snippets in Clay.

🌐 Applications of Create Across Your GTM Motion

We can create personalized content across your entire GTM motion:

• Ad copy for account-based marketing campaigns
• Direct messages on LinkedIn or Twitter
• Content for blog posts, landing pages, or LinkedIn posts
• And of course, highly tailored sales emails

The most common use case is outbound messaging. And with Clay, you can take a deep personalization table and create dynamic snippets tailored not just to the person, but to the hypothesis you're running.

📈 The Evolution of Personalization

In the past, personalization meant using simple variables like:

"I see you're working at {{company}}"

Now, the personalization is richer, more dynamic — and powered by AI:

• {{subj line}}: "Congrats on the new GTM hire"
• {{body}}: "Saw you closed out Q1 with a 2x jump in pipeline. Curious how the team's prioritizing RevOps this quarter?"

You're still using a template. You'll have sections like intro, body, close, ask… but now each variable can contain an entire AI-generated sentence or phrase.

You can even change tone and voice using dynamic prompting. This means adjusting copy depending on whether you're writing to a VP or an individual contributor.

💪 Benefits of AI-Powered Snippets

This approach helps you:

• Enhance email deliverability
• Adjust tone and voice per persona
• Increase message quality without writing every word yourself

🧠 Scaling Strategy, Not Just Messages

The real power of AI Snippets is how they reflect your hypotheses, not just your data. For example:

• If you think a company values innovation, you can generate a subject line that highlights that
• If you're targeting accounts with closed/won pipeline growth, your intro can reference their velocity
• If someone's on the ASU board and you're a fellow alum, your CTA can reflect shared context

Each variable becomes a reflection of why this person was selected in the first place.

🔬 Example: Personalized Email Intros at Scale

Let's say you're reaching out to 100 marketing leaders at recently funded SaaS startups. You've pulled in:

• Company descriptions
• Job changes
• Funding round details
• Personal bios

Using AI Snippets, you can generate:

• A subject line based on their funding news
• A personalized intro based on their latest hire
• A CTA that reflects the growth stage of their team

All without writing a single line of copy by hand.

📋 Implementation in Clay

Let's see what this looks like in Clay:

1. Start with a deep personalization table
   • Begin with your list of prospects
   • Enrich with social profiles to get detailed information
   • Use AI formulas to transform the enriched data
   • Apply Claygent to find additional context (thought leadership, blogs, interviews)
2. Create modular AI Snippets
   • Generate subject lines that reference specific insights
   • Craft personalized intros based on research findings
   • Develop custom P.S. lines that connect on a personal level
3. Combine into complete messages
   • Use formula columns to combine snippets into cohesive messages
   • Maintain consistent core messaging where appropriate
   • Preview and refine your results

🚀 The Power of Scaling What Works

With Clay, you're not writing 100 emails. You're writing one great play — and then letting AI turn it into 100 unique, relevant messages.

That's what scaling personalization looks like. You identify what works, and then apply it systematically across your entire prospect list.

🔮 What's Coming Next

In the next lesson we'll show you how to take these snippets and stitch them into complete emails, faster and with better copy, using tools like Twain.

💡 Conclusion

Traditional personalization has always faced a fundamental tradeoff between scale and depth. With AI Snippets, you get both and more:

• Deeper personalization: Each message can reference specific, nuanced details about your prospect
• Greater scale: You can reach more people without sacrificing quality
• Consistent messaging: Your core value proposition remains clear and focused
• Testable hypotheses: You can systematically track which personalization approaches work best

By breaking messages into modular components, you gain both flexibility and control, allowing you to maintain your brand voice while adapting to each prospect's unique context.