Your list is your strategy.
That’s one of the first things I tell my clients when I’m coaching them on cold outbound: if you don’t have the right list, you’re toast from the start.
Without the right list, you won’t reach the right people, won’t book meetings, and won’t make sales. But it used to be slow and manual, expensive, and nearly impossible to craft a great list.
I’ve fallen in love with Clay and how it helps build the target account list of your dreams. In this post, I’ll show you three examples of lists I built on Clay for three different companies so you can see how simple and powerful Clay is for list building—and hopefully pick up a few tricks.
Problems with list building the old way
Historically, you had to do a ton of manual work to build lists of the right target companies.
Option A: Hire SDRs to build lists manually
Option A was hiring a gazillion SDRs and paying them tons of money for slow, manual research. It took way too long to book meetings and you were constantly dealing with hiring and firing and churn.
I wrote a whole post about my take on the current state and future of the SDR motion—if you’re interested in that, check out my article on Outbound Sales Automation here.
Option B: Use ZoomInfo, Sales Navigator, or other tools
Option B is to use tools like ZoomInfo or LinkedIn Sales Navigator to pull a list of companies and prospects. Option B is better, but still not great.
These tools are good at sourcing large lists, but because they’re so big, they don’t help you hone in on what you’re looking for in detail. You probably have search criteria that these big out-of-the-box data providers can’t filter by. ZoomInfo’s definition of a SaaS company, for example, might be broader than yours.
To get the perfect list, you might still need to do some web scraping or another step that would require human, manual labor. Otherwise, you’re stuck spraying and praying.
Option C: Use Clay and AI to get hyper-specific targeting
In this post, we’ll show you an Option C—how to use generic list building tools as a basis and then really hone in on your target accounts with Clay’s AI research abilities.
Real-life examples of list building without Clay
I want to pick some real companies, show you who they sell to, and then show you how I would automate their list building with Clay.
Keap is a CRM that sells to small businesses. On their industry page, you can see the different kinds of companies they sell to: accounting, coaches, consultants, financial advisors, etc.
Imagine I was a Keap salesperson and wanted to target my outreach to B2B accounting firms. Using Option B, I would go to a website like Apollo.io and try to find a list of these companies.
In Apollo, I tried a search filtering for accounting firms. This gave me a mix of B2B accounting firms, B2C accounting firms, accounting software companies, and so on.
The first company that came up looked like a B2B accounting service firm. Great. But the next one was Ernst & Young—not exactly a small accounting firm!
If you were pulling this list right off Apollo, you’d have a bunch of bad-fit companies in your account list.
Without the extra layer of refinement—which I’ll show you how to add with Clay—you’d be wasting time and money on outreach to companies which were never a good fit.
How Clay helps you target much more specifically
Example 1: Finding small accounting firms for Keap
I built this Clay table for Keap, pulling in some websites and companies from a raw export in Apollo that contained the company website, name, and the industry.
Then, it was time to actually use sophisticated reasoning with AI to determine if a company is really an accounting service company. For this, I used Claygent, Clay’s powerful AI web scraper that combines Google Search with web scraping and ChatGPT to execute on reasoning tasks.
Here is the prompt I used to more effectively bucket the companies:
“Your job is to determine if a website is an accounting firm that renders accounting services to its clients, or another type of company, like an accounting software company. We want to reach out to accounting service companies. If a company is an accounting services firm (they sell accounting services), respond ‘Accountant.’ Otherwise, do your best to label the company type. Here is the website to check: [company website]”
Claygent gave me all kinds of answers: “cloud-based software company,” “not an accounting firm,” “consulting services,” and, of course, “accountant.” It gave me far more specificity and power to filter for my ICP than Apollo could provide.
You can use Claygent to filter companies in any way you can imagine—including figuring out what kind of go-to-market team a company is (B2B, B2C, or both).
Finally, I used Clay’s Enrich Company from LinkedIn enrichment to pull in live company data like employee headcount. With this data, I could filter for small companies that would be perfect for Keap’s services—in this case, I chose 10-100 employees.
With this account scoring workflow, you can just load in all the companies from your CRM and automatically filter them for your dream target account list.
Example 2: Segmenting lists of vacation properties for Lodgify
Lodgify sells to vacation rental properties, including everything from B&Bs to resorts to camping and glamping spots. I created a Clay table to categorize their leads based on the type of property they are.
After pulling in the company name and website, I used the Enrich Company from LinkedIn enrichment and found the employee headcount again. Then I used Claygent to classify the property type.
After that, I filtered their account lists so Lodgify could target their outreach based on the type of property they’re reaching out to.
Example 3: Building lists of product-led SaaS companies for Amplitude
Amplitude is a great software for product managers—it helps you track how users are engaging with your product and moving through your funnel. In this case, we wanted to sell to product-led SaaS companies with product teams.
The Clay table started the same way: I pulled in a list of software companies and their websites from Apollo, then used the Enrich Company from LinkedIn enrichment and pulled the employee count.
Then I used the “Find Employee Headcount by Job Title” enrichment to find any employees with titles that include the following keywords at the company: product manager, head product, VP product, CPO, or chief product officer. If there were jobs that had these keywords, I used a formula to return the number of roles that fit the criteria.
Then I scraped each company’s website using Claygent to determine if they were a SaaS company using the following prompt:
“Your job is to determine if a company is a SaaS (software as a service) company. Things like ‘demo request’ or ‘free trial’ are often signs they are a software company. ‘Product’ or ‘platform’ in the nav are all good signs. Here is the website: [website]. Respond ‘SaaS’ if it’s a SaaS company. Otherwise, do your best to label the type of company.”
Finally, I wanted to know if a company had a product- or sales-led GTM motion. This took a somewhat longer Claygent prompt:
“Your job is to determine if a SaaS company is product-led or sales-led. Sales-led companies do NOT have a free trial or ‘self serve’ option on the website. These websites only have a ‘contact sales’ or ‘demo request’ or ‘book demo’ button. If the website only has options to submit a contact form for a sales meeting, the company is ‘sales-led.’ If the company has a ‘free trial’ or ‘get started’ or ‘sign up’ or ‘try for free’ button on the website, it’s likely a ‘product-led’ company. Product-led companies allow users to sign up for an account and get started for free. If the company is sales-led, respond ‘Sales-led’. If the company is product-led, respond ‘Product-led’. If both, respond ‘both’. Here is the website: [website]. Only respond product-led if you’re at least 80% sure. Otherwise, it’s probably sales-led.”
As a salesperson for Amplitude, I could use Clay to transform our unsegmented leads into a list of product-led or sales-led SaaS companies with enough product people on staff. I could even sort and score accounts based on how many product people they have or similar criteria.
Hopefully, this gives you a sense of how powerful Clay can be for account scoring and prospecting. I used this strategy at ServiceBell to build super qualified account lists. I was able to go from reaching out to a ton of companies that weren’t a good fit, low conversion rates, low show rates, low qualified rates on sales calls to, in one case, a demo actually paying us on the first discovery call straight from a cold email.
Clay helps you easily build super qualified account lists. Once you have a list of companies, you can find the right people at these companies to sell to, find their emails, and reach out to them, at scale.
Check out other posts and videos on our blog to see how to do this, and let us know what other scraping and account list building functionality you’re curious about on our Slack community. Happy prospecting!
Your list is your strategy.
That’s one of the first things I tell my clients when I’m coaching them on cold outbound: if you don’t have the right list, you’re toast from the start.
Without the right list, you won’t reach the right people, won’t book meetings, and won’t make sales. But it used to be slow and manual, expensive, and nearly impossible to craft a great list.
I’ve fallen in love with Clay and how it helps build the target account list of your dreams. In this post, I’ll show you three examples of lists I built on Clay for three different companies so you can see how simple and powerful Clay is for list building—and hopefully pick up a few tricks.
Problems with list building the old way
Historically, you had to do a ton of manual work to build lists of the right target companies.
Option A: Hire SDRs to build lists manually
Option A was hiring a gazillion SDRs and paying them tons of money for slow, manual research. It took way too long to book meetings and you were constantly dealing with hiring and firing and churn.
I wrote a whole post about my take on the current state and future of the SDR motion—if you’re interested in that, check out my article on Outbound Sales Automation here.
Option B: Use ZoomInfo, Sales Navigator, or other tools
Option B is to use tools like ZoomInfo or LinkedIn Sales Navigator to pull a list of companies and prospects. Option B is better, but still not great.
These tools are good at sourcing large lists, but because they’re so big, they don’t help you hone in on what you’re looking for in detail. You probably have search criteria that these big out-of-the-box data providers can’t filter by. ZoomInfo’s definition of a SaaS company, for example, might be broader than yours.
To get the perfect list, you might still need to do some web scraping or another step that would require human, manual labor. Otherwise, you’re stuck spraying and praying.
Option C: Use Clay and AI to get hyper-specific targeting
In this post, we’ll show you an Option C—how to use generic list building tools as a basis and then really hone in on your target accounts with Clay’s AI research abilities.
Real-life examples of list building without Clay
I want to pick some real companies, show you who they sell to, and then show you how I would automate their list building with Clay.
Keap is a CRM that sells to small businesses. On their industry page, you can see the different kinds of companies they sell to: accounting, coaches, consultants, financial advisors, etc.
Imagine I was a Keap salesperson and wanted to target my outreach to B2B accounting firms. Using Option B, I would go to a website like Apollo.io and try to find a list of these companies.
In Apollo, I tried a search filtering for accounting firms. This gave me a mix of B2B accounting firms, B2C accounting firms, accounting software companies, and so on.
The first company that came up looked like a B2B accounting service firm. Great. But the next one was Ernst & Young—not exactly a small accounting firm!
If you were pulling this list right off Apollo, you’d have a bunch of bad-fit companies in your account list.
Without the extra layer of refinement—which I’ll show you how to add with Clay—you’d be wasting time and money on outreach to companies which were never a good fit.
How Clay helps you target much more specifically
Example 1: Finding small accounting firms for Keap
I built this Clay table for Keap, pulling in some websites and companies from a raw export in Apollo that contained the company website, name, and the industry.
Then, it was time to actually use sophisticated reasoning with AI to determine if a company is really an accounting service company. For this, I used Claygent, Clay’s powerful AI web scraper that combines Google Search with web scraping and ChatGPT to execute on reasoning tasks.
Here is the prompt I used to more effectively bucket the companies:
“Your job is to determine if a website is an accounting firm that renders accounting services to its clients, or another type of company, like an accounting software company. We want to reach out to accounting service companies. If a company is an accounting services firm (they sell accounting services), respond ‘Accountant.’ Otherwise, do your best to label the company type. Here is the website to check: [company website]”
Claygent gave me all kinds of answers: “cloud-based software company,” “not an accounting firm,” “consulting services,” and, of course, “accountant.” It gave me far more specificity and power to filter for my ICP than Apollo could provide.
You can use Claygent to filter companies in any way you can imagine—including figuring out what kind of go-to-market team a company is (B2B, B2C, or both).
Finally, I used Clay’s Enrich Company from LinkedIn enrichment to pull in live company data like employee headcount. With this data, I could filter for small companies that would be perfect for Keap’s services—in this case, I chose 10-100 employees.
With this account scoring workflow, you can just load in all the companies from your CRM and automatically filter them for your dream target account list.
Example 2: Segmenting lists of vacation properties for Lodgify
Lodgify sells to vacation rental properties, including everything from B&Bs to resorts to camping and glamping spots. I created a Clay table to categorize their leads based on the type of property they are.
After pulling in the company name and website, I used the Enrich Company from LinkedIn enrichment and found the employee headcount again. Then I used Claygent to classify the property type.
After that, I filtered their account lists so Lodgify could target their outreach based on the type of property they’re reaching out to.
Example 3: Building lists of product-led SaaS companies for Amplitude
Amplitude is a great software for product managers—it helps you track how users are engaging with your product and moving through your funnel. In this case, we wanted to sell to product-led SaaS companies with product teams.
The Clay table started the same way: I pulled in a list of software companies and their websites from Apollo, then used the Enrich Company from LinkedIn enrichment and pulled the employee count.
Then I used the “Find Employee Headcount by Job Title” enrichment to find any employees with titles that include the following keywords at the company: product manager, head product, VP product, CPO, or chief product officer. If there were jobs that had these keywords, I used a formula to return the number of roles that fit the criteria.
Then I scraped each company’s website using Claygent to determine if they were a SaaS company using the following prompt:
“Your job is to determine if a company is a SaaS (software as a service) company. Things like ‘demo request’ or ‘free trial’ are often signs they are a software company. ‘Product’ or ‘platform’ in the nav are all good signs. Here is the website: [website]. Respond ‘SaaS’ if it’s a SaaS company. Otherwise, do your best to label the type of company.”
Finally, I wanted to know if a company had a product- or sales-led GTM motion. This took a somewhat longer Claygent prompt:
“Your job is to determine if a SaaS company is product-led or sales-led. Sales-led companies do NOT have a free trial or ‘self serve’ option on the website. These websites only have a ‘contact sales’ or ‘demo request’ or ‘book demo’ button. If the website only has options to submit a contact form for a sales meeting, the company is ‘sales-led.’ If the company has a ‘free trial’ or ‘get started’ or ‘sign up’ or ‘try for free’ button on the website, it’s likely a ‘product-led’ company. Product-led companies allow users to sign up for an account and get started for free. If the company is sales-led, respond ‘Sales-led’. If the company is product-led, respond ‘Product-led’. If both, respond ‘both’. Here is the website: [website]. Only respond product-led if you’re at least 80% sure. Otherwise, it’s probably sales-led.”
As a salesperson for Amplitude, I could use Clay to transform our unsegmented leads into a list of product-led or sales-led SaaS companies with enough product people on staff. I could even sort and score accounts based on how many product people they have or similar criteria.
Hopefully, this gives you a sense of how powerful Clay can be for account scoring and prospecting. I used this strategy at ServiceBell to build super qualified account lists. I was able to go from reaching out to a ton of companies that weren’t a good fit, low conversion rates, low show rates, low qualified rates on sales calls to, in one case, a demo actually paying us on the first discovery call straight from a cold email.
Clay helps you easily build super qualified account lists. Once you have a list of companies, you can find the right people at these companies to sell to, find their emails, and reach out to them, at scale.
Check out other posts and videos on our blog to see how to do this, and let us know what other scraping and account list building functionality you’re curious about on our Slack community. Happy prospecting!
