Clay + LeadsFactory.io + LinkedIn Sales Navigator: How to Find Decision Makers Automatically for Sales and Lead Generation

You’ve probably already Googled “how to find decision makers” a dozen times, and every result gives you the same advice: use LinkedIn, try a database, look at the company’s About Us page, maybe attend a conference.

That advice is not really wrong. But the problem nobody talks about is that doing all of that manually, across disconnected tools, for every single target account, is a massive time sink for your sales process. And if you’re running outbound at any kind of scale, it’s borderline impossible.

Your sales reps are spending hours every week bouncing between LinkedIn Sales Navigator, Apollo, company websites, and spreadsheets trying to figure out who to contact at each target company.

They’re copying and pasting names, guessing job titles, verifying emails one at a time, and still ending up with incomplete lists that are outdated by the time the first email goes out.

We know this because we work with sales teams every day at Nebor, and this is one of the most common bottlenecks we see.

The companies that come to us are not lazy or incompetent. They’re just stuck doing everything manually because they never set up a system to handle this work for them.

This post is going to walk you through the traditional methods for finding decision makers (because they do work as individual tactics), and explain why relying on them without a system slows you down.

Then, we'll show you how we build automated workflows that find decision makers for our clients on autopilot using Clay, LeadsFactory.io, LinkedIn Sales Navigator, and a few other tools.

Let’s get started.

The traditional approaches to finding decision makers (and why they fall apart without a system behind them)

Before we get to how we automate things, it’s worth covering the standard methods because they form the building blocks of any good system. The issue is not the tactics themselves.

It’s that most teams use them in isolation, manually, with no connective tissue between them.

Here’s what we mean.

LinkedIn and LinkedIn Sales Navigator are the go-to starting point that eats up your team’s time

LinkedIn Sales Navigator is one of the best tools out there for identifying key decision makers. You can filter by job title, seniority level, department, company size, industry, geography, and more.

You can save leads and accounts. You can build targeted lists of VPs of Sales at SaaS companies with 50 to 200 employees in the DACH region. It’s incredibly powerful. You probably don’t need us to know that.

But here’s where it breaks down in practice.

Your SDR opens Sales Navigator, runs a search, scrolls through profiles, clicks into each one to verify they’re actually still at that company, copies names into a spreadsheet, and then moves to another tool to find their email.

That process takes anywhere from 30 minutes to an hour for a single batch of 20 to 30 leads. Now multiply that across your entire target account list.

If you’re going after 500 companies and need to identify two to three decision makers at each one, your team is spending weeks doing nothing but manual research.

Sales Navigator is excellent for filtering and finding business decision makers and department heads. It's super effective, especially for the latter. But it was designed as a research tool, not a workflow component.

Our point is that it doesn’t automatically feed those contacts into your CRM, enrich them with verified emails and phone numbers, or trigger outreach sequences. It just shows you who exists. Everything else you'll need after that for your sales success is on you.

And there’s another issue: title inconsistency. The person you need to talk to could be called “VP of Growth” at one company, “Head of Revenue” at another, and “Director of Business Development” at a third.

Sales Navigator search filters are literal. If you search for “VP of Sales”, you will miss the “Head of Sales” who has the exact same decision-making authority. That’s a real problem at scale.

Prospecting databases like Apollo, Cognism, and ZoomInfo provide good data, but never the full picture

Tools like Apollo, Cognism, and ZoomInfo give you access to large databases of contacts with direct phone numbers, email addresses, LinkedIn profiles, and firmographic data for relevant decision makers and even general employee data at companies.

If you can sustain the budget, some of them also offer intent data (although, as we’ve talked about in previous posts, the quality of that intent data is just flat out poor).

The appeal is clear: type in a company name, get back a list of employees with their contact details, and start reaching out. For one-off research, this works fine.

But there are a few things you need to know.

No single data provider has complete coverage.

• Apollo could have the CMO’s email at Company A, but not at Company B.

• Cognism might have the phone number for one contact but return nothing for another.

• ZoomInfo might show you someone who left the company six months ago.

This is a well-documented issue in the data enrichment space, and it is why relying on one tool for your contact data will always leave gaps in your pipeline.

The other challenge is that these tools operate as standalone databases. Your reps log in, search, export a CSV, clean it up, upload it to their CRM or outreach tool, and then start a campaign.

That’s a lot of manual steps between “I found a contact” and “I’ve sent them a personalized email”. Every one of those steps introduces delays, errors, and wasted time.

At Nebor, we use multiple data providers layered together in a sales automation waterfall enrichment setup inside Clay. That means if Apollo doesn’t have the email, LeadMagic tries next, then Findymail, then FullEnrich, and so on.

This approach consistently gets us significantly higher enrichment coverage compared to using a single tool. But setting this up manually every time you need to find decision makers is impractical.

Leveraging company resources: The “old school” approach that still has its place

Some guides will tell you to check the company’s About Us page, look for team members on their website, review press releases, or browse conference attendee lists and speaker rosters. And that’s not bad advice.

It can uncover key contacts that don’t show up in databases, especially at smaller companies or in industries where people are less active on LinkedIn.

The problem is that this is the most manual and least scalable approach of all. You are literally visiting websites one by one, reading team pages, cross-referencing names with LinkedIn profiles, ensuring you haven't added any same company twice, and hoping the information is current.

This may work if you’re targeting 10 accounts. It does not work if you’re targeting 500. Imagine having to go through the company structure of 500 companies on their websites.

Conference attendee lists can be gold for identifying decision makers, but they come and go, and they’re often gated behind event registrations.

Press releases and news mentions can help you identify newly appointed executives (which is actually a great buying signal), but manually scanning news feeds for every company on your list is not a sustainable prospecting strategy.

The point here is that these are useful data points. They just need to be captured and processed as part of a broader system, not as standalone research tasks for your sales reps.

“Reverse” searching decision makers with AI tools like Clay (it’s powerful, but not meant to be a manual task)

This is where things start getting interesting. Clay, specifically, lets you input a domain name or company name and then automatically find relevant contacts using its 100+ integrated data providers.

You can set up a Clay table, feed it a list of companies, and use enrichment steps to pull back the names, job titles, LinkedIn URLs, and email addresses of the people you want to talk to.

Clay can even use AI to interpret job titles and determine whether someone is a decision maker based on your criteria beyond the exact title match.

That means if you’re looking for “the person who makes purchasing decisions for sales tools”, Clay’s AI can assess whether “Head of Revenue Operations” fits that description. This is a massive step up from the rigid title-matching logic in Sales Navigator or Apollo.

But here’s where a lot of teams get stuck: they treat Clay as a research tool their reps jump into whenever they need to look someone up. And that creates two problems.

First, it’s inefficient. You don’t want five SDRs all logging into Clay, building their own ad hoc tables, running enrichments, and exporting contacts. That duplicates effort, wastes credits, and creates inconsistency in your data.

Second, if your reps are manually kicking off Clay searches every time they need to identify a decision maker at a target account, you’re still stuck in a reactive, one-at-a-time workflow. You’ve just replaced the manual Google search with a manual Clay search.

Clay is at its most powerful when it sits at the center of an automated B2B lead generation workflow that finds decision makers without anyone needing to do anything. And that’s what we’re going to talk about next.

How Nebor helps you find decision makers through workflow automation (so your team can focus on selling)

Everything we’ve covered above represents the ingredients. LinkedIn Sales Navigator gives you the filters. Data providers give you the contact details. AI gives you the intelligence to match the right people. Company resources give you additional context.

What most teams are missing is the recipe. A system that chains all of these ingredients together into an automated workflow that runs continuously, finds the right decision makers at the right companies, enriches them with accurate contact data, and pushes them into your outreach pipeline without your reps lifting a finger.

That’s exactly what we build at Nebor. Here’s how we approach it.

Start by defining your ICP and buyer persona so you know exactly who you want to reach

We start every engagement with this step, and it’s the one most teams rush past.

If you don’t have a clear and precise Ideal Customer Profile (ICP) and buyer persona, everything downstream breaks.

Your filters will be too broad, your enrichment will return irrelevant contacts, and your outreach will land in front of people who have zero authority (or zero interest) in buying what you sell.

When we say ICP, we mean the company-level criteria: industry, company size (employee count and revenue), geography, tech stack, growth stage, and any other firmographic or technographic attributes that define your best-fit accounts.

When we say buyer persona, we mean the individual-level criteria: job title patterns, seniority level, department, and decision-making authority.

For example, one of our clients sells event management software. Their ICP is (let’s say) mid-market companies in Europe that organize at least 5 events per year.

Their buyer persona is the person responsible for event operations or marketing events. That could be titled “Head of Events”, “Event Marketing Manager”, “Director of Field Marketing”, or even “VP of Marketing” at a smaller company. If we just searched for one of those titles, we’d miss a huge chunk of their addressable market.

Getting this right up front is critical because it determines everything: which tools to use for sourcing, what filters to set, how to configure your persona waterfall, and what signals indicate someone is actually worth reaching out to.

At Nebor, we’ve learned from working with a lot of B2B companies that most businesses struggle to define their ICP with the precision needed for effective outbound campaigns, which is why many turn to specialist Clay agencies or in-house experts to close that gap.

So we help refine it as part of the process. We look at your existing customer data, identify patterns among your best-fit clients, and use that to sharpen targeting before we build a single workflow.

Standardize your strategy for finding decision makers based on your ICP and the tools that work best

Not every ICP requires the same toolset or the same approach to finding decision makers. The tools that work best for identifying CTOs at Series A startups are different from the tools that work best for finding procurement managers at enterprise manufacturers.

Here’s how we think about tool selection at Nebor:

If your ICP is well-represented on LinkedIn (which is the case for most B2B SaaS, tech, consulting, and professional services companies), then LinkedIn Sales Navigator combined with LeadsFactory.io is your best bet for identifying and matching decision makers.

LeadsFactory.io is especially interesting here because it scrapes Sales Navigator in real time without requiring your LinkedIn credentials, and it uses smart persona waterfall logic.

You upload your company list, define your personas in priority order (for example, 1. CMO, 2. VP of Marketing, 3. Head of Growth), and LeadsFactory.io searches Sales Navigator to find the closest match at each company.

If the CMO doesn’t exist at a particular company, it automatically falls back to the VP of Marketing, and so on. This solves the title inconsistency problem we talked about earlier.

And because it integrates with Clay, the data can flow directly into your enrichment and outreach workflows.

If your ICP includes industries where LinkedIn coverage is weaker (like manufacturing, logistics, or traditional retail), you’ll want to lean more heavily on data providers like ZoomInfo, Cognism, or Apollo that have deeper offline databases.

You might also need to layer in tools that pull from non-LinkedIn sources like company websites, press releases, or industry directories.

If your outreach strategy is heavily email-based, you need to prioritize tools with the strongest email verification. That usually means combining multiple email finders (LeadMagic, Findymail, FullEnrich) in a waterfall enrichment inside Clay to maximize coverage and accuracy.

The key point here is that there’s no universal formula. The right approach depends on who you’re trying to reach, where those people are most visible, and what data sources give you the most reliable contact information for that specific audience.

This is something we evaluate and customize for every client as part of building a sales tech stack that runs on autopilot with Clay and n8n.

Finding decision makers as part of an automated outbound sales and lead generation workflow

This is where everything comes together. Instead of having your reps manually research decision makers for each target account, you build an automated workflow that does it for them, continuously.

Here’s how a typical Clay-based lead generation system and decision-maker workflow looks when we build it for our clients at Nebor:

Step 1: Source your target companies.

This can come from multiple sources. You can scrape a specific list using LinkedIn Sales Navigator filters (exported via PhantomBuster or a similar tool).

You can pull companies from your CRM that match certain firmographic criteria. You can use Clay’s built-in company search to build a list based on industry, size, funding stage, or tech stack.

Or you can use a signal-based trigger (more on that shortly). The company list lands in a Clay table as the starting point.

Step 2: Find the decision makers at each company using LeadsFactory.io.

This is where LeadsFactory.io plugs into the workflow. You configure your persona waterfall (the job titles you want, in priority order), and LeadsFactory.io automatically searches Sales Navigator for each company in your Clay table to find and match the right contacts.

Because it uses closest-match logic instead of exact title matching, it handles the messy reality of B2B org charts where the same role has 15 different titles across 15 different companies.

The matched contacts are pushed back into your Clay table, enriched with their LinkedIn profiles and basic information.

Step 3: Enrich contacts with verified emails, phone numbers, and additional data.

Once you have the decision-maker names and LinkedIn profiles from LeadsFactory.io, Clay takes over to enrich them further.

We run a waterfall enrichment to find verified work emails (using a combination of tools like LeadMagic, Findymail, and FullEnrich), direct phone numbers, company firmographics, technographic data, and any other data points needed for personalization.

If one provider doesn’t return an email, the next one tries. This multi-source approach consistently delivers better coverage than relying on any single tool.

Step 4: Qualify and score each lead.

Not every decision maker is worth contacting right now. Using Clay’s AI and custom scoring logic, we can qualify leads based on criteria you define: company size, tech stack, recent funding, hiring signals, or engagement history.

Leads that meet your threshold move forward. Leads that don’t get parked for later or excluded entirely. This makes sure your reps only see the best-fit prospects.

Step 5: Generate personalized outreach and push to your outreach platform.

Using Clay’s native AI integrations (ChatGPT or Claude), we generate personalized message drafts based on the enriched data we’ve collected.

This isn’t the typical Hi {FirstName}, I noticed your company does X stuff. It’s contextual messaging based on real data points: their role, their company’s recent activity, their tech stack, their industry challenges.

The finalized contacts and messages are then pushed to your outreach tool (like Instantly for email, Lemlist for multi-channel, or directly into your CRM) to kick off campaigns automatically.

The beauty of this setup is that once it’s built, it runs on its own. New companies get added to the Clay table (manually, via webhook, or through a trigger), and the entire workflow unfolds automatically: find the decision maker, enrich, qualify, personalize, and send.

Your sales reps get notified when there’s a warm lead to follow up on. That’s it.

A Manual Input Workflow that finds decision makers directly inside your CRM

Not every team needs a fully automated outbound engine from day one. Some teams just need a faster way to identify decision makers for accounts that are already in their CRM.

So, here’s a simpler workflow we often set up for clients in this situation:

Your sales rep identifies a target company in your CRM (HubSpot, Salesforce, Pipedrive, whatever you use).

They flag the account, or it gets flagged automatically based on a trigger (like being added to a specific pipeline stage). That trigger sends the company data to a Clay table via webhook or n8n automation.

Clay then activates LeadsFactory.io to find the right decision makers based on your persona waterfall, enriches the contacts with verified emails and additional data, and pushes the finalized contacts back into your CRM, attached to the correct account.

From the rep’s perspective, they flagged a company and a few minutes later, the right contacts appeared in their CRM with everything they need to start outreach. No logging into Sales Navigator. No opening Clay. No manual research at all.

This is a great starting point for teams that want to reduce the time their reps spend on research without overhauling their entire outbound process while exploring specialized sales automation companies and tools to scale further.

It also keeps your CRM as the single source of truth, which matters a lot for teams that need clean data, automated CRM hygiene and enrichment, and accurate reporting.

How to find decision makers among people already visiting your website (through visitor identification)

This is one that most teams overlook completely, but it’s incredibly valuable.

Think about it: there are people visiting your website right now who work at companies that fit your ICP. They could be browsing your pricing page, reading your blog posts, or checking out your case studies.

Or even better, maybe you run marketing and ads campaigns that bring in an insane amount of prospects on your website. But you have no way of knowing who they are or whether they were ever even there in the first place.

These are warm prospects showing real interest, but if you don’t know who they are, they leave your site and you never hear from them.

Website visitor identification tools like RB2B (which works for US-based visitors) and Leadinfo (best for Europe), or Snitcher can identify the individuals behind anonymous website visits, enrich them with contact details and profile data, and push that information into Clay or your CRM.

Here’s how we set this up as a workflow at Nebor:

A visitor lands on your website and meets certain engagement criteria (for example, they visited the pricing page twice or spent more than 20 minutes on a specific product page).

The visitor identification tool (we choose this based on your business and location) captures their information and pushes it into a Clay table.

From there, the same decision-maker workflow we described above kicks in: Clay checks whether the visitor matches your ICP, identifies if they hold a decision-making role (or finds the right decision maker at their company if the visitor themselves is not one).

Next, it enriches the contact with verified email and phone data through the workflow we described earlier, and either triggers an automated outreach sequence or alerts your sales team with a full dossier on the prospect.

The value here is timing. You’re reaching out to someone whose company just showed real intent by visiting your website. That’s a fundamentally different conversation than cold outreach to a random lead from a purchased list.

And because the entire process is automated, your team doesn’t need to manually check analytics dashboards or cross-reference IP data. The system identifies the opportunity and acts on it.

We extend this same logic beyond website visits. Social media engagement, content downloads, webinar registrations, and other digital interactions can all feed into the same workflow, which is exactly the kind of modern motion top outbound experts now recommend.

The idea is that any meaningful engagement signal becomes a trigger that automatically identifies the decision maker, enriches the lead, and sets up the outreach. Your reps just focus on the conversation.

Hire Nebor to build Clay workflows that find decision makers automatically (so your sales reps can sell)

If you’ve read this far, you probably have a clear picture of what a modern, automated system for finding decision makers looks like. You understand the tools, the logic, the workflow structure, and why doing this manually doesn’t scale.

But here’s the reality: building this yourself takes time, expertise, and a lot of trial and error. You need to know how to structure Clay tables, configure waterfall enrichments, connect tools via APIs and webhooks, set up n8n automations, handle data hygiene, and tune every step so the output is clean, accurate, and ready for outreach.

And that’s just the technical side. You also need the sales strategy to ensure you’re targeting the right people with the right message at the right time.

That’s exactly what we do at Nebor. We’re not just Clay experts or random workflow builders. We’re sales and lead generation specialists who happen to use Clay as the engine behind the systems we build.

Every workflow we design is built with one goal: get your sales reps out of the research and prospecting grind so they can focus on what actually generates revenue, which is having qualified conversations and closing deals—exactly what the best Clay sales automation agencies optimize for.

And because we build systems, not campaigns, everything we create is yours. You own the infrastructure. You own the workflows. You own the data.

If you’re tired of your sales reps spending more time researching than selling, book a 15-minute call with us and we’ll show you exactly how we’d build this for your business—or help you evaluate top Clay experts for outbound sales automation if you’re comparing partners.