Prospect research with Clay + Apollo

Build a targeted prospect list in Apollo, enrich and research it in Clay with waterfall enrichment and AI research agents, write a personalized first line per lead, and send it back for outreach.

Generic outbound gets ignored. What works is a tight list of the right companies, reached at the right moment, with a first line that proves you did your homework. Doing that by hand takes 10–15 minutes per lead. This playbook combines Apollo (contact database and sequencing) with Clay (multi-provider enrichment plus AI research) to do it for hundreds of leads in an afternoon.

Step 1: Write your ideal customer profile

Be specific. A weak profile is “SaaS companies.” A strong one:

• Company: B2B SaaS, 20–200 employees, US/Canada, has a public pricing page.
• Trigger: hiring for customer support roles (signals support volume growing).
• Persona: Head of Support, VP Customer Success, or COO at smaller companies.
• Pain you solve: support ticket backlog; proof: one customer result you can cite.

Triggers matter most. A company that’s hiring, just raised, launched a product or changed tools is far more likely to reply.

Step 2: Build the list in Apollo

In Apollo’s People search, apply your filters: job titles (include variations like “Head of Support”, “Director, Customer Support”), seniority, company headcount, location and industry keywords. Apollo also offers company-level filters, including signals such as job postings on some plans; use what your plan includes.

Review the first 50 results manually. If more than a few are wrong-fit, tighten the filters before exporting. Save the search, then export people (name, title, company, domain, LinkedIn URL) as CSV, or save them to a list. Exports and email reveals consume Apollo credits, so export only what you’ll work.

Step 3: Import into a Clay table

In Clay, create a new workbook/table and import your CSV. Each row is a person; each column is a field. From here, every enrichment is a new column that runs per row. Before running anything at scale, filter the table to 10–20 rows to test. Clay bills enrichment and AI steps in credits, so testing small protects your budget.

Step 4: Enrich with waterfall providers

Add enrichment columns for what Apollo didn’t give you or what you want to verify:

• Work email (waterfall): Clay queries multiple providers in sequence until one finds a result, which typically raises coverage over any single source. Add an email-verification step after it.
• Company data: headcount, funding, tech stack, location, from the company domain.
• Job postings or news: to confirm your trigger.

Look at the test rows. Are emails found for most? Are company facts right? Adjust providers before scaling.

Step 5: Research each account with an AI column

This is the step that replaces manual research. Add a Claygent (Clay’s AI research agent) or AI column with a narrow, checkable prompt, for example:

Visit {{company domain}}. In one sentence, describe what the company sells and to whom. Then state whether they currently list open customer support roles on their careers page (Yes/No) and give the URL. If you cannot find it, answer “Unknown”. Do not guess.

Narrow prompts with “Unknown” as an allowed answer reduce invented facts. Spot-check 10 rows by clicking the URLs. For deeper account research on a short list, a manual pass with Perplexity is still useful.

Step 6: Score and filter

Add a formula or AI column that scores fit, e.g. +2 if hiring support, +1 if 50–200 employees, +1 if they use a tool you integrate with, −3 if they’re a competitor or existing customer. Filter to the top tier. It’s better to send 80 great emails than 400 mediocre ones; it also protects your sending domain’s reputation.

Step 7: Write a personalized first line

Add an AI column (using an OpenAI or Anthropic model through Clay) that writes only the first line, grounded in the research columns:

Using only the facts provided, write one natural sentence (max 25 words) to open a cold email to {{first name}}, {{title}} at {{company}}. Reference: {{research summary}} and {{support hiring}}. No flattery, no exclamation marks, don’t mention AI or research. If facts are “Unknown”, return an empty string.

Keep the rest of the email human-written and consistent: problem, proof, one low-friction ask. Read 20 generated lines; reject the pattern if any feel creepy or wrong.

Step 8: Push to your sequence and CRM

Export the final rows (with the first-line column) to CSV and import into an Apollo sequence, mapping the first line to a custom field used in your email template, or use Clay’s own integrations to send rows to your outreach tool or CRM such as HubSpot. Log every contacted person in your CRM so you don’t email them twice from different tools.

Start with a small batch, watch bounce and reply rates for a few days, then scale.

Pitfalls

• Running enrichment on the whole table first. Test on 10–20 rows; credits go fast.
• Unverified emails. High bounce rates damage your domain. Verify before sending.
• AI-invented facts. Always allow “Unknown” and spot-check.
• Creepy personalization. Reference business facts, not personal social posts.
• Compliance. Follow CAN-SPAM in the US (honest headers, physical address, opt-out), and check GDPR, CASL and others for non-US contacts. Not legal advice.
• Sending from your main domain at volume. Many teams use a separate, warmed-up sending domain.

Alternatives

Want an always-on agent that does research and follow-ups for you? Look at Lindy. For more tools by sales stage, see Best AI tools for sales.

A complete example email

Putting it together for one row (fictional company):

Subject: Support hiring at Northwind

Hi Priya, saw Northwind is hiring three support specialists while rolling out the new self-serve plan.

Teams at that stage usually find ticket volume grows faster than headcount. We help B2B SaaS support teams deflect repetitive tickets; one customer cut first-response time by about half in a quarter.

Worth a 15-minute look at how that would work with your current helpdesk?

Alex YourCo · 123 Main St, Anytown, USA · Reply “no thanks” and I won’t follow up

The first line came from Clay; everything else is a template. The proof point must be true and verifiable for your own business. Never let AI invent customer results.

Weekly operating rhythm

• Monday: refresh the Apollo search for new matches; import only new rows into Clay.
• Tuesday: run enrichment and research on the new rows; spot-check 10.
• Wednesday–Thursday: send in small daily batches.
• Friday: review replies, bounces and unsubscribes; tweak the profile and first-line prompt.

Track reply rate by segment, not overall. If one title or industry consistently replies more, narrow the list toward it.

FAQ

Why use both Clay and Apollo?

Apollo combines a large B2B contact database with sequencing, which makes it a fast place to build the initial list. Clay is a data-orchestration spreadsheet that combines many data providers and AI research steps, which improves coverage and personalization.

What is waterfall enrichment?

Querying several data providers in sequence for the same field, such as a work email, and stopping when one returns a result. Clay markets this as combining multiple providers for better coverage.

What is Claygent?

Clay's AI research agent. You give it a prompt per row, such as finding a company's pricing model or recent announcements, and it searches and returns an answer with its reasoning.

How much does this cost per lead?

It depends on how many enrichment and AI columns you run. Test on 10 to 20 rows, read the credit usage, and only then run the full table.

Is cold email legal?

Rules differ by country. In the US, CAN-SPAM requires accurate headers, a physical address and an opt-out. GDPR and other regimes can be stricter. This is not legal advice; check the rules for each region you email.

Last checked against official docs: October 2026 (Apollo and Clay product pages and help centers). Prices and UI labels change; confirm on each vendor's site.