How To Find Company Key Decision Makers for Cold Emails Using Clay.com
Trying to figure out the right person to send your emails to? Using Clay, you can find key decision makers at prospective companies and personalize the emails to boost your response rates!

Jonathan Garces
Updated March 20, 2024

a man sitting at his desk at work, but everything is made of mushy clay like claymation, digital art
Reading Time: 8 minutes
March 20 2024: Screenshots on this article are being updated. Please check back soon!
As a salesperson, you might be given a prospect list, but it may be limited in information. In this article we’re going over how to go from only having a list of companies to a list of decision makers to even personalizing the email for each decision maker with data that will grab their attention. Clay is an incredible lead enrichment tool that lets us do this, so we'll make use of their tool for this tutorial 🙂
Let's dive in!
Finding Decision Makers With Only Company Name
If your list looks like the image below, we’ll go ahead and import this into Clay. You’re going to download your sheet as a CSV and save it somewhere. In Clay, you’re going to click “New Table”, then “Import CSV”.
Once you’ve imported your CSV successfully into Clay, this is what you should see.
Now, the next step is to find their decision makers. We need to find their company LinkedIn page first. And remember, the whole point of this is to find this data without doing it manually.
In Clay, we’re going to add an “enrichment” column. To do this, you’re going to add a column and click “Enrich Data”.
You’re going to search for the “Search Google” enrichment which looks like this.
In the text box, we’re going to specially ask google for the company’s LinkedIn page using only the “Company Name” which is the only data we have available. If you already have the company’s LinkedIn page, you can skip this step.
In the Google Search Query box, you’re going to type the following:
“site:linkedin.com/company” “{insert company name}”.
In the part where you see {insert company name} you’re going to do a “/” and that should pull up the list of columns to reference. You’re going to reference the column where you have the list of company names. This is what it should look like.
You’re then going to click “Save and Run First 10 Rows”.
If done correctly, you should see a list of LinkedIn company URLs.
If you see the list, great! But wait…we’re not done. Because we did a Google Search Query request, it means there’s multiple links or results per row. Because we did an exact search query, searching specifically for the company name, it’s most likely going to be the first result.
So we need to map the first google search result to its own column. Below is a gif showing how to map the first search result to a new column.
If done correctly, you should now have a new column with the company’s official LinkedIn page.
Now, we're ready to find our decision makers at these companies.
Create a new column, new enrichment and you’re going to search for a “Find People” enrichment.
For the “Company Identifier” you’re going to type “/” and select the new column you created that contains the company LinkedIn Page.
Next, you’re going to click “Job Title Keywords”.
Here is where you enter the list of job titles you want to find. Let’s assume the following titles:
- Chief Human Resources Officer
- Human Resources Director
- Talent Acquisition Director
- Human Resources Manager
- Talent Acquisition Manager
- HR Business Partner
- Head of Recruitment
- VP of Human Resources
- Procurement Manager
- Chief Operating Officer
Now let’s put these into the “Job Title Keywords” box.
This is what it should look like.
Here’s a useful tip - you could paste that list into ChatGPT and ask it the following: “Separate this list by commas: Chief Human Resources Officer Human Resources Director Talent Acquisition Director Human Resources Manager Talent Acquisition Manager HR Business Partner Head of Recruitment VP of Human Resources Procurement Manager Chief Operating Officer”.
Now you can directly paste it into the box without having to manually separate it with a comma.
Once you have the job titles in, go ahead and click ‘Continue to add fields”. You should now see a few different pieces of data.
What you’re seeing is data from each prospect or contact that we can map into a new column.
For this exercise, we’re only going to use “Name”, “Title” and “Company”. Once you have those toggled, you’ll click “Save and Run First 10 rows”.
If done correctly, your table will look like the image below.
Looks like we found decision makers! Now, depending on the size of the companies we’re enriching, you’re going to have a number of employees with those job titles. Some rows have “10 Profiles”, “2 Profiles”, etc. We obviously want all of the contacts because they’re all considered decision makers.
So now we have to “write these contacts” to another table. Stick with me here, we’re almost done.
What this means is that we have to get each individual contact into their own rows.
Let’s create a new table, just like how we did in the beginning.
When you create a new table, name it something you will recognize like “Decision Makers”. By default, you will have 3 columns: Name, Email, and LinkedIn Profile.
Remember how we toggled only “Name”, “Title” and “Company” from the contacts? Well those are the columns we’re going to use. Go ahead and delete those default columns, and create new ones.
Your new workspace should look like this.
Now we’re ready to pass data to this new workspace from the original workspace.
Click the expand arrow, as seen in the screenshot below.
Then you’re going to hover over the “People” box and then you should see “Take action on List”
Once you click on “Take Action on List” you should see a dropdown list pop up. Click on “Write each item to new row in other table”.
You should see the options box come up. For the table, you’re going to select the new table which should be called “Decision Makers”.
For the box titled “What are you writing to another table” make sure you have “a list of objects” selected.
Once selected, you’re going to write it exactly as I do in the image below. Same text and same settings.
Once done, click “Save and Run First 10 Rows”. Your new workspace “Decision Makers” should look like this.
Each contact/profile we pulled from our original workspace is now separated into their own row with this new table.
And there you go. We now have decision makers from our list of dream companies!
Grabbing a Decision Maker’s attention
Now that we have a list of decision makers we now have to think of a way to grab their attention. These people are busy, getting bombarded with cold emails and calls every single day so it’s an absolute must to stand out.
A great way to stand out is by showing the prospect you did research on them or the company. In this scenario we’re going to stand out by showing we did “research” on the company, but actually we’re going to be using Cla.y. We’ll display data programmatically to make it look as if we did that research to each contact!
Let’s go back to the original table.
Go ahead and create a new column. You’re going to search for the “Get Headcount Growth at Company” and select that enrichment.
For the company identifier box, you’re going to reference the “Company LinkedIn URL”.
You should now see a few different data points to toggle. You’re going to toggle on the “Percent Employee Growth Over The Last 3 Months” and “Employee Count 3 Months Ago”.
This is what you should see in your workspace.
Now obviously the goal is to use this data inside of an email and to make it sound as human as possible.
Let’s convert the percent column into an actual percentage. For this, we’ll use the AI Formula generator.
Go ahead and create a new column. Once you do, click the header, then select “Settings”. You can also rename the column to “Percentage”.
Once in the settings, click “Use AI” and write “Turn this into a percentage /percentage over last 3 months”. Remember to actually reference the column you want to turn into a percentage.
This is what you should now see.
If you’d like, we can round this to the nearest whole number because remember the whole goal of this is to make the data sound conversational.
You can create a new column and again you’re going to use the AI formula generator.
In the new column, you’re going to round to the nearest whole number and the column you’re going to reference is “Percent Employee Growth..”.
Then once you have rounded up, you’re going to create a new column and turn that new column into a percentage. This is what your table should look like.
Now we have variables available to be used in our emails that can grab the attention of your decision makers!
Happy Hunting! Let us know if you have any questions or suggestions in the comments below!
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