AI Lead Enrichment: How to Use GPT-4 and Gemini for Sales Data

What Is AI Lead Enrichment?

AI lead enrichment uses large language models (LLMs) like OpenAI's GPT-4 and Google's Gemini to research, analyze, and generate data about leads and companies. Unlike traditional enrichment that looks up records in static databases, AI enrichment can reason about available information and generate novel insights.

Traditional enrichment says: "This company has 500 employees." AI enrichment says: "This company has 500 employees, recently raised a Series B, uses Salesforce and HubSpot, and their VP of Sales likely cares about pipeline efficiency based on their job postings."

AI enrichment is transforming B2B sales data because it can extract insights that no database contains. By combining web-scraped company data with LLM reasoning, teams get intelligence that previously required hours of manual research per prospect.

How AI Enrichment Works in Enrichabl

Enrichabl lets you create custom AI columns that process each lead through an LLM. You write a natural language prompt that describes what data you want, and the AI generates that data for every lead in your list.

The workflow is: (1) Import your lead list. (2) Create an AI column with a prompt. (3) Select which LLM to use (GPT-4 or Gemini). (4) Run the enrichment. The AI processes each lead individually, using available data (name, company, domain, scraped website content) to generate the requested output.

You bring your own API keys (BYOK) for OpenAI and Google, so you pay the LLM providers directly at their rates. There's no markup from Enrichabl - just the flat $30/month platform fee.

Best Prompts for AI Enrichment

Personalized first lines: "Based on the company name and domain, write a one-sentence personalized email opener that references something specific about the company. Be casual and conversational, not salesy."

Company analysis: "Based on the company name and any available website content, provide: 1) A one-sentence company description. 2) Estimated company size (small/medium/large). 3) Primary industry. 4) One likely business challenge they face."

ICP scoring: "Based on the following criteria, score this lead 1-10 on fit for a B2B lead enrichment tool: company size 10-500 employees, B2B business model, uses CRM, has sales team. Provide the score and a one-sentence justification."

Technology identification: "Based on the company domain and any available website data, identify the likely sales and marketing tools this company uses. List tools you are confident about."

Combining Web Scraping with AI

AI enrichment is most powerful when combined with web scraping. Enrichabl integrates with Firecrawl to scrape company websites, then feeds that content to the AI for analysis.

Without web scraping, AI enrichment relies on the LLM's training data - which may be outdated. With web scraping, the AI analyzes current, real-time website content. This is the difference between "GPT-4 thinks this company does X" and "According to their current website, this company does X."

Common web scraping + AI workflows: scrape company About page and generate a summary, scrape product pages to identify technology stack, scrape team pages to identify decision-makers, scrape blog/news for recent company developments.

AI Enrichment Best Practices

Be specific in your prompts. Vague prompts produce vague outputs. Instead of "tell me about this company," ask for specific data points: "What is this company's primary product, target market, and estimated employee count?"

Test prompts on a small batch (10-20 leads) before running them on your full list. Review outputs for accuracy, relevance, and formatting. Iterate on your prompt until the results meet your standards.

Use different LLMs for different tasks. GPT-4 excels at creative writing (personalized first lines, email copy). Gemini can be more cost-effective for structured data extraction. Experiment to find the best model for each use case.

Cost of AI Enrichment

AI enrichment costs depend on the LLM provider rates. With GPT-4, processing 1,000 leads with a typical enrichment prompt costs approximately $2-10 depending on prompt length and output size. Gemini can be 50-80% cheaper for comparable tasks.

Combined with Enrichabl's $30/month platform fee, AI enrichment is extremely cost-effective. Processing 5,000 leads with AI personalization might cost $10-50 in API fees - compare that to the $500-1,000+ you'd spend on Clay credits for similar workflows.

The BYOK model gives you full cost visibility. You see exactly how much each API call costs on your provider's dashboard, with no hidden markups from Enrichabl.

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