So you want to get smarter about B2B audience segmentation. Maybe you’re tired of lists that go nowhere, or you’ve realized buying generic data is mostly a waste. If you’re working in sales, marketing, or data, and you want to cut through the fluff, this guide is for you. I’ll walk you through how to segment B2B audiences using advanced search in Peopledatalabs, with zero buzzwords and a focus on what actually works.
Why B2B Segmentation Matters (And When It Doesn’t)
Before we get into the weeds, let’s be real: Not every business needs fancy segmentation. If you’re selling SaaS to a handful of Fortune 500s, you probably know your targets by name. But if you need to reach thousands—or want to get granular with verticals, titles, or buying signals—good segmentation is the difference between a useful list and a time sink.
Peopledatalabs (PDL) is a B2B data provider that gives you access to millions of company and professional profiles. Their advanced search can help you build precise audience segments. But—and this is important—PDL is only as good as your inputs and your clarity about what you want.
Let’s get into how to actually use it.
Step 1: Get Clear on Your Ideal Audience
Don’t skip this step. You can’t fix bad targeting with more data.
Ask yourself: - Who are you actually trying to reach? (Job titles, industries, company size, geography) - What signals matter? (Tech stack, funding, recent hires, job changes) - What’s a must-have and what’s just nice to have?
Pro tip: Write down your criteria. If you’re vague (“decision-makers at tech companies”), you’ll get vague results.
What to ignore: Don’t chase every possible filter. More isn’t always better—just more noise.
Step 2: Get Access to Peopledatalabs Advanced Search
PDL offers several ways to search: API, integrations, and a web-based dashboard (if you have it in your plan). For most people, the dashboard’s advanced search is the fastest way to segment without writing code.
- If you have API access only, you’ll need basic programming chops. (There are wrappers for Python, Node, etc.)
- The dashboard gives you point-and-click filtering. If your company doesn’t have dashboard access, talk to your admin or sales rep. Don’t waste time trying to hack around it.
Honest take: The dashboard is easier, but the API is more powerful if you want to automate or pipe results into your own tools.
Step 3: Build Your Search Query
Here’s where most people go wrong: they use generic filters, or they go overboard and get zero results. PDL’s advanced search lets you combine dozens of filters, such as:
- Industry (e.g., “Software,” “Financial Services”)
- Company size (employee count or revenue range)
- Location (country, state, city, or even remote)
- Job title or function (beware: titles vary a lot)
- Seniority (C-level, VP, Director, etc.)
- Technologies used (e.g., “Salesforce,” “AWS”)
- Keywords in bio or company description
- Recent role changes or hiring activity
Example: Segmenting by Industry, Role, and Tech Stack
Say you want U.S.-based marketing directors at SaaS companies using HubSpot.
Your search might look like: - Company Industry: “Software” - Company Tech Stack: “HubSpot” - Job Title: “Marketing Director” (or “Head of Marketing”; use OR logic) - Location: United States
What works: Start broad, then narrow down. If you start with 10 filters, you’ll probably get zero or meaningless results.
What doesn’t: Don’t trust title filters alone. “VP Marketing” and “Head of Marketing” can be the same job at different companies. Use fuzzy matching or multiple variations.
Ignore: Vanity filters like “Fortune 500” unless you really need them. Many great prospects aren’t on those lists.
Step 4: Use AND/OR Logic Thoughtfully
PDL supports Boolean logic in advanced search. This means you can combine filters (AND) or offer alternatives (OR).
- AND means all conditions must be true (e.g., “Marketing Director” AND “California”).
- OR means any condition can be true (e.g., “VP Marketing” OR “Head of Marketing”).
Pro tip: Use parentheses to group logic. Example:
(“VP Marketing” OR “Head of Marketing”) AND (“San Francisco” OR “Los Angeles”)
Don’t get carried away with nested logic unless you really need it. Simpler queries are easier to debug and understand.
Step 5: Review and Refine Your Results
Once you run your search, look at the output. Is it what you expected? Probably not the first time. Here’s what to do:
- Check a sample: Open a few records. Are these the right people at the right companies?
- Look for weird outliers: If you see retail managers in your “SaaS CMO” segment, your filters need work.
- Adjust filters: Too broad? Add another. Too narrow? Remove or relax one.
Honest take: No search tool is perfect. PDL’s data is good, but not magic. Expect to iterate.
What works: Reviewing sample results beats exporting a giant CSV and hoping for the best.
What doesn’t: Don’t fall for “set it and forget it.” Data changes, and so should your filters.
Step 6: Export and Use Your Segmented List
After you’re happy with your segment, export it in the format you need (usually CSV or via API). Most teams will push this data into their CRM, marketing automation, or enrichment workflow.
A few gotchas: - Duplicates: Expect some. Clean your list before blasting emails. - Data freshness: PDL updates often, but people change jobs fast. - Fields: Make sure you’re exporting the fields you actually need (email, phone, company, etc.).
Pro tip: If you’re running outreach, be careful with volume. Burning through a list with bad targeting or messaging is a fast way to get ignored.
Step 7: Keep Improving Your Segmentation
Good segmentation is a process, not a one-off. Check performance:
- Are your reply rates or conversion rates decent?
- Are you getting the right kind of meetings or inbound interest?
- Are your sales or marketing teams saying “these leads are garbage”? (If so, revisit your filters.)
Don’t be afraid to tweak and rerun searches. The best teams treat audience segmentation as an ongoing experiment.
What’s Overhyped (and What to Skip)
A few things people talk about that aren’t worth obsessing over:
- AI-powered segmentation: There’s no substitute for knowing your audience. “AI” can’t read your mind.
- Super-niche filters: If you end up with a list of ten people, you’ve probably gone too far.
- Buying “intent data” add-ons: Sometimes useful, but often noisy and expensive. Try basic segmentation first.
Real-World Tips for Better B2B Segmentation in PDL
- Always check a sample before exporting a big list.
- Titles are messy—use variations and don’t expect perfect matches.
- Company size and industry classifications aren’t always accurate. Cross-check with LinkedIn or your own CRM.
- Combine filters for best results, but don’t overcomplicate it.
- Update your segments regularly—companies and people move fast.
Wrapping Up: Keep It Simple, Iterate Often
Peopledatalabs is a powerful tool if you know what you’re after and don’t overthink it. Start with clear criteria, use a few well-chosen filters, and check your results before you act. Data won’t solve bad targeting, but with good segmentation, you’ll spend less time chasing dead ends.
Keep it simple. Test, tweak, and adjust as you go. That’s how you actually find the audiences that matter—no hype required.