How I Learned Clay

ENTRY #003

12 months ago, I didn’t know what Clay was.

Today, it's my most-used sales tech tool and the #1 essential platform in any sales tech stack.

But it wasn’t always like this.

The first time I opened Clay, I closed the tab after 15 minutes.
It felt overwhelming. Too many buttons. Too many options. No clear direction.

The second time, something was different.
I had a problem I was trying to solve, and I knew Clay could help.

Since then, I’ve built 50+ clay tables, automated hours of work, and booked meetings with it.

That problem gave me clarity. And clarity is all you need to build with Clay.

My Framework for Clay Workflows

Every time I build something in Clay, I break it down using 4 stages.

Think of it like this:

Find the Data
Fill the Gaps
Fix the Format
Forward the Output

Let’s walk through one of the first Clay tables I built

The goal was to target Sales (Manager and up seniority), CEO and COO of Sales Tech SaaS companies that are:

Hiring for a sales, customer success or GTM Engineer role
With 11-200 employees
Located in the US

Step 1: Finding Data (The Foundation)

I ask myself:

“Where is this data coming from?”

In this case:

Use find people inside Clay to filter for SaaS Companies
Filter by industry, company size, description keywords (optional), and location
Optional: Import a CSV or use Webhooks if you have data outside Clay. For example, if you are building the list in Apollo or Sales Navigator

Now I have a foundation: people of SaaS companies that fit the right company size, and location.

Step 2: Enriching the Data (The Missing Pieces)

Now I fill in the blanks:

Use Clay’s enrichment option to pull in:

Qualify that they are a Sales Tech Company
Find people that work in these companies (for the companies that are Sales Tech SaaS Companies)
Find and verify their work email address
Find open jobs relating to sales or marketing

Using options like:

Use AI to visit the website and categorise
Use the Find People at These Companies enrichment to find people after qualifying them
LeadMagic/Prospeo/Findymail/Wiza/Hunter in an email waterfall to find and verify emails
Use the find open jobs waterfall with sources from LinkedIn, Google, and Predict Leads to find any open jobs

Watch the breakdown here

At this point, I have a rich dataset of Sales Tech SaaS companies with strong outbound potential.

Step 3: Reform the Data (Format It Clean)

This is where most people stop, but formatting is key.

Here I:

Apply formulas to the columns with multiple open roles to reflect the most recent one
Use AI inside Clay to normalise the job titles of the open roles for reference in the email

Watch the breakdown here

AI Prompt used for Normalising the Job Title:

#CONTEXT#

You are tasked with standardizing job titles for use in cold email outreach. The goal is to make the job title as clear, concise, and professional as possible, removing any unnecessary or extraneous information.

#OBJECTIVE#

Normalize the value in the {job title} columns to output the most standard, widely recognized version of the job title for reference in a cold email.

#INSTRUCTIONS#

1. Review the job title in {job title} column

2. Remove any unnecessary qualifiers, extra descriptors, or company-specific jargon (e.g., “at Company”, “(Remote)”, “(Contract)”, “Team Lead of”, “Global”, “Sr.”, “Jr.”, etc.) unless they are essential to the core job title.

3. Output the most common, professional, and easily understood version of the job title (e.g., “Senior Software Engineer” instead of “Sr. Software Engineer, Backend (Remote) at Acme Inc.”).

4. Ensure the result is suitable for use in a cold email and is as generic and recognizable as possible.

5. If the column is empty, return output empty.

#EXAMPLES#

Input: "Sr. Software Engineer, Backend (Remote) at Acme Inc."

Output: "Senior Software Engineer"

Input: "Global Head of Customer Success (Contract)"

Output: "Head of Customer Success"

Input: "Marketing Manager at Beta Corp"

Output: "Marketing Manager"

Input: ""

Output: "No job title available"

Now, the data looks clean and can be easily used in my campaigns.

Step 4: Export or Distribute (Push It Out)

Once the table is qualified, I decide where it’s going:

If I’m launching a campaign: push to Instantly, Smartlead, or HeyReach
If I’m adding to CRM: push to HubSpot or GoHighLevel
If I need to review it first, send it to Airtable or Google Sheets
Or I export it as CSV for manual use

Pro Tip: Start with the problem, not the tool.

Every time I use Clay, I make sure I’m solving a real problem and know exactly what data points matter.

If you ever feel lost inside Clay, ask:

❓ “What do I need to know to move this lead forward?”
❓ “What data do I already have, and what do I still need?”

So whenever you’re building a table in Clay, don’t just dive in.

Map out the workflow first

Then break each step down into this simple framework.
This helps you stay focused, save time, and ensure you build an efficient table

Until the next entry, stay curious and keep building.
Natasha | GTME in the wild

Diaries of a GTME