Claygent guide: Automating prospect research and personalization with Clay's AI agent

Claygent automates the manual prospect research that consumes the bulk of an SDR's day: scraping websites, qualifying leads, and writing personalized icebreakers one at a time. For B2B SaaS teams running coordinated outbound campaigns, it replaces hours of tab-switching with structured, repeatable AI research that feeds directly into your enrichment and outreach workflows.

This guide covers how Claygent works, the most effective use cases for B2B SaaS teams, and the implementation best practices that separate successful deployments from wasted credits.

What Claygent is and how it works

Claygent is Clay's AI-powered research agent. It performs human-like web research to extract custom data points unavailable from traditional enrichment providers. Where standard data enrichment tools pull from static databases, Claygent visits websites, navigates pages, fills forms, and extracts unstructured information in real time.

It solves what Clay calls the "last mile data problem": collecting niche, high-value data points that traditional enrichment databases simply don't carry.

How it differs from Clay's standard "Use AI" feature

Standard AI integrations work with data already in your tables, writing personalized messages, categorizing leads, or analyzing existing information. Claygent goes further by combining generative AI with intelligent agent models that perform live web scraping and navigation.

The technical architecture

Claygent uses multiple AI models depending on your task. Proprietary Claygent Neon is optimized for answer formatting and data extraction. GPT-4 handles general-purpose reasoning tasks. Claude handles enhanced reasoning and longer context windows.

You control Claygent through custom prompts that define what to research, where to look, and how to format outputs. The Claygent Builder provides version control for prompt iterations, A/B testing of different prompt approaches, and risk-free prompt development without consuming credits during testing.

Core capabilities for SaaS prospect research

Claygent excels at extracting both company-level and people-level data that static databases miss.

Company-level data points reveal organizational context: mission statements, value propositions, ICP identification, B2B vs. B2C classification, pricing inference, free trial availability, and goals or priorities from job listings.

People-level data points enable personalized outreach: role focus and job responsibilities, LinkedIn activity summaries, thought leadership topics, and speaking engagements.

The differentiator is dynamic signals. Claygent can extract recent funding announcements, job listing intent signals, competitive positioning from website content, and technology stack indicators, all in real time rather than from a stale database snapshot.

Five high-impact use cases for B2B SaaS teams

These verified workflows deliver the most value for SaaS growth teams. Each connects enrichment, research, and outreach into a unified execution sequence.

1. Dynamic prospect qualification

Import scraped leads, add Clearbit enrichment for missing company data, then use Claygent to scrape company websites for mission, problems they solve, and tech stack. Feed this into GPT-4o to determine ICP fit automatically. This automated qualification pipeline eliminates manual handoffs between enrichment and sales enablement.

Prompts that consistently deliver accurate qualification data include "Is this company B2B or B2C?" and "What problems is this company trying to solve based on their job listings?"

2. Intent signal detection from job listings

Company hiring patterns reveal buying intent. Use Claygent to scrape careers pages and analyze listings with two sequential prompts: first, "What problems is this company trying to solve based on job listings?" and second, "List job titles that would benefit most from their products." This automation routes high-intent prospects to sales teams based on hiring alignment with your solution.

3. Competitive intelligence and positioning

Claygent synthesizes competitive positioning by scraping multiple pages per company: pricing models, trial offerings, integrations, and customer testimonials. Teams compare findings across competitors and generate personalized outreach addressing specific competitive gaps.

Tested prompts for competitive research include "Infer pricing strategy from the pricing page," "What is the mission of the company?" and "Summarize the latest news about this company."

4. Account-based marketing account mapping

For ABM campaigns, Claygent supports detailed account profile creation through three phases:

• Phase 1, data enrichment: scrape company missions, recent funding news, and organizational structure.
• Phase 2, ICP scoring: weight factors including company size, growth signals, and tech stack alignment.
• Phase 3, personalization: generate account-specific insights for email content referencing specific company initiatives.

This end-to-end ABM workflow unifies account intelligence, scoring, and personalized outreach within a single system.

5. CRM data hygiene automation

Export CRM records missing key fields, run them through Clay's enrichment waterfall (standard providers first, Claygent as fallback), then push updated records back to your CRM automatically. At Understory, we use this approach to maintain accurate, up-to-date contact and company records across client CRMs as part of our outbound engineering service.

Automating personalization at scale

The highest-value Claygent application for most SaaS teams is coordinated personalization. The workflow follows five phases: target list creation, waterfall data enrichment, Claygent AI research, AI-powered message generation, and data sync to email platforms.

Multi-layer personalization strategy

Layer 1, company context: "Based on this company's LinkedIn description and recent news, write a one-sentence context statement that shows I've done research."

Layer 2, role-specific pain point: "This prospect is a [job_title] at a [company_size] company in [industry]. What is their number one pain point related to [your solution category]?"

Layer 3, personalized CTA: suggest a concrete next step referencing their actual situation. Instead of "quick call," reference a specific business outcome. Example: "Would it make sense to show you how we helped [similar company] reduce [metric] during their expansion phase?"

This layered approach integrates company research, role insights, and contextual CTAs into outreach that feels handwritten at scale.

Output format specifications

Specify output formats explicitly: plain text for icebreakers, JSON for structured data extraction, boolean for qualification questions, and URL lists for case study discovery. Claygent performs significantly better when the expected output shape is defined upfront.

Known limitations

Claygent cannot access paywalled content requiring paid subscriptions, access password-protected sites or member-only areas, guarantee consistent output quality without prompt optimization, or overcome anti-scraping measures on protected websites.

Plan your workflows around these constraints to avoid wasted credits and failed enrichment attempts.

Scale your Claygent implementation with expert allbound execution

Claygent handles research and enrichment effectively on its own, but the teams that get the most from it connect those outputs into coordinated paid media and outbound workflows. That coordination, building enriched prospect lists, syncing them into personalized email sequences via Instantly, feeding engagement signals into LinkedIn retargeting audiences through Fibbler, and maintaining CRM hygiene across every touchpoint, is where most teams stall.

At Understory, we build and manage these Clay-powered outbound systems end to end as part of our go-to-market engineering service. We've built outbound engines for clients who replaced their entire SDR team with our coordinated approach.

Book a demo with Understory to see how coordinated Clay-powered outbound and paid media turns prospect research into a qualified pipeline.