In the previous lesson, you learned how to use Claygent for Last-Mile data discovery. Now, let's explore a similar but distinct use case: researching and enriching data that's difficult to structure and doesn't live in standard databases.

This is where Perplexity enrichment comes in. It's specifically designed to help you access information from unstructured data sources across the web.

🔍 When to Use Perplexity Enrichment

Perplexity enrichment is ideal when you need:

• Information from unstructured data sources
• Fast, high-level summaries
• To provide your sources alongside your data

🗂️ Real-World Example: Liquor License Requirements

Let's walk through a practical example to illustrate how Perplexity works.

The Challenge

Imagine you target new prospective bar or restaurant owners, and you want to find and enrich your outreach with information about the requirements to get a liquor license in various cities across the U.S.

This is challenging because:

• There's no single place to find all this information
• Each state and city has different requirements
• You also typically need to check:
  • Your state's alcohol control website
  • Additional requirements from your city government
  • For states with complicated rules (like those with license quotas), you may also need to consult with a liquor license broker or lawyer

Step-by-Step Process with Clay and Perplexity

Here's how to tackle this with Clay's Perplexity enrichment:

1. Prepare Your Data Table – Start with a list of cities for research.
   • Create a new table or use an existing one with city names.
   • Make sure city names are clean and properly formatted.
2. Add the Perplexity Enrichment – Set up your research query:
   • Navigate to the enrichment panel.
   • Select Perplexity AI as your enrichment source.
   • Create a simple prompt, e.g. "What are the requirements to get a liquor license in [city]?"
3. Run the Enrichment – Process your data:
   • Start with a few rows to test your prompt.
   • Review the results to ensure they contain the information you need.
   • Run the enrichment on all rows once satisfied.
4. Organize Your Results – Structure the returned data:
   • Separate the information into different columns.
   • Create one column for the main response.
   • Create another column for Perplexity's sources.

Refining the Results

Since the raw response might be too detailed for outbound emails, you'll want to refine it:

1. Summarize with AI – Condense the detailed information:
   • Choose the AI option (not Claygent) since you're summarizing existing data.
   • Use the meta prompter to structure your request.
   • Ask AI to condense the response into three key points about liquor license requirements.
2. Process the Summary – Format for practical use:
   • Save and run your AI prompt.
   • Review the summarized content for accuracy and clarity.
   • Split the results into separate columns if needed (e.g., "Point 1," "Point 2," "Point 3").
3. Prepare for Outreach – Integrate with your campaigns:
   • Use these concise points in your outreach templates.
   • Personalize messages based on the specific requirements in each city.
   • Reference the source links for credibility when necessary.

The end result is exactly what you need: three concise points about liquor license requirements for each city, perfect for incorporating into your outreach to potential bar or restaurant owners.

📊 What Are Other Use Cases for the Perplexity Enrichment?

Perplexity is best for enriching from unstructured data sources. Other potential use cases include:

• Industry trends in a specific region (e.g., "restaurant trends in Austin 2024")
• Competitive positioning or market perception (e.g., "How does Gusto compare to Rippling for HR software in 2024?")
• Event intelligence for sales triggers (e.g., "What are the top food & beverage trade shows happening in Chicago in Q2 2024?")

🔮 Conclusion

Perplexity enrichment expands your data capabilities by allowing you to:

• Access information that doesn't exist in structured databases
• Quickly summarize complex information from across the web
• Include source citations for additional credibility
• Transform unstructured data into actionable insights for your outreach

That’s it for the Perplexity enrichment.

In the next lesson, we'll look at enriching from images and screenshots.