Your list is your strategy.
Get it right, and your outreach flows. Get it wrong, and you waste time chasing unsuitable prospects.
The problem is that traditional list building is slow, manual, and often inaccurate. SDRs spend hours on research while generic data providers give big lists but little precision.
Apollo solves this issue. With over 65 million companies and more than 210 million verified contacts, Apollo uses AI-driven filtering. This makes it possible to create highly targeted account lists that match your ideal customer profile quickly and on a large scale.
In this article, I will show you how to use Apollo io to build the most targeted account lists possible, step by step.
Problems with Old-School List Building
Historically, you had to do a ton of manual work to build lists of the right target companies. Most teams had to choose between two bad options:
Option A: Manual SDR Research
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.
Option B: Generic Data Providers
Tools like ZoomInfo or LinkedIn Sales Navigator gave you massive databases, but not always the right fit. Their definitions of “SaaS company” or “SMB” might not match your ICP. You’d still spend hours cleaning and narrowing the list—or risk blasting the wrong accounts.
The Core Issue
The real problem with old-school list building is lack of precision. You either get too little data (manual SDRs) or too much irrelevant data (generic providers). Either way, your outreach pipeline gets clogged with unqualified leads.
That’s why modern sales teams are moving toward AI-powered list building, where accuracy and scale finally meet.
Option C: Use Apollo and AI to get hyper-specific targeting
In this post, i’ll show you an Option C— How Apollo io takes the headaches out of list building by combining a massive B2B database with AI-powered targeting and enrichment. Instead of juggling multiple tools (a data provider, enrichment service, and outreach platform), Apollo does it all in one place.
How Apollo helps you target much more specifically
Example 1: Finding Small Accounting Firms for Keap
Keap sells CRM software to small businesses, and one of their top customer segments is small B2B accounting firms. The challenge is separating these firms from giant enterprises or software vendors.
I started by pulling a raw list of “accounting” companies from Apollo.io using its industry filter. That gave me a broad dataset with company names, websites, and industry tags.
But here’s the problem: not every company in the “accounting” category is actually an accounting services firm. Some are SaaS vendors. Some are large enterprises. Others aren’t even relevant.
That’s where Apollo.io’s AI enrichment comes in. I set up Apollo to analyze each website and classify whether it was:
✅ An accounting services provider (the ICP),
❌ A software vendor, or
❌ A large consulting firm that didn’t fit.
Here’s a sample AI prompt I used inside Apollo:
“Your job is to determine if a company is an accounting services firm (they sell accounting services) or something else, such as an accounting software company. If it’s a services firm, respond with ‘Accountant.’ Otherwise, label the company type. Website: [company URL].”
Apollo’s AI gave me highly specific answers like “Accountant,” “Cloud-based software company,” or “Not an accounting firm.” This level of filtering gave me far more precision than ZoomInfo or LinkedIn alone.
Finally, I layered on firmographic enrichment inside Apollo to pull live company data, such as employee headcount. From there, I filtered down to companies with 10–100 employees—the exact sweet spot for Keap’s CRM.
👉 The result? Instead of a messy list of “all accounting companies,” I had a clean, hyper-targeted list of small B2B accounting firms that Keap’s sales team could prioritize for outreach.
Example 2: Segmenting Vacation Properties for Lodgify
Lodgify sells website and booking software to vacation rental businesses—everything from small B&Bs to boutique resorts to unique stays like glamping sites. The challenge is that “vacation property” can mean many different things, and each type of property responds better to a different sales message.
I started by exporting a broad list of hospitality companies from Apollo using the hospitality industry filters. This gave me a big dataset with company names, websites, and industry tags.
But here’s the catch: the list was too generic. Apollo was showing me a mix of hotels, real estate management firms, resorts, and even unrelated travel businesses. Lodgify’s sales team needed granularity—to know what kind of property each company actually was.
So I used Apollo io’s AI enrichment to classify the property type. For each website, I prompted Apollo’s AI to determine whether the business was a:
Bed & Breakfast
Resort
Camping/Glamping site
Vacation rental home provider
Or unrelated (real estate, agencies, etc.)
Apollo’s AI quickly categorized each lead with detailed, human-like reasoning. For example, it would return “Boutique” or “Glamping site” instead of just a generic “hotel.”
Next, I pulled in additional enrichment like employee size and location data to help Lodgify prioritize targets. For instance, smaller family-run B&Bs in Europe might require a different sales play than large resorts in the US.
The result? Lodgify could segment its account lists not just by “hospitality company” but by specific property type, making their outreach more relevant and personalized. A message to a B&B about managing bookings on their website looks very different than a pitch to a camping site or a luxury resort.
Wrapping Up -
Hopefully, this gives you a clear picture of just how powerful Apollo can be for account scoring and targeted prospecting. I used this exact strategy at one of the company to build highly qualified account lists.
Before using Apollo, I were reaching out to a wide mix of companies - many of which weren’t a fit. That meant low reply rates, low conversion, and wasted time on calls that went nowhere. Once we refined our targeting with Apollo’s AI-driven filters and enrichment, everything changed.
Apollo makes it simple to:
Build hyper-qualified account lists.
Enrich those companies with the right data.
Find the decision-makers and their verified contact details.
Launch personalized outreach sequences at scale.
The result is more focus, less waste, and a pipeline full of accounts that actually match your ICP.
[If you want me to do the List building for you - DM " List Building]
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