If you’re in sales, marketing, or growth, you know the drill: you get a giant list of companies, but only a handful are worth your time. The real work is figuring out which accounts to go after, and which to ignore. This guide is for folks who want practical steps to cut through the noise and use advanced filters in Pandamatch to actually find and prioritize target accounts—without getting buried in features or hype.
Why Bother With Advanced Filters?
Let’s be honest: most company databases are noisy. You can waste hours clicking around, or you can get systematic. Pandamatch’s advanced filters are your best shot at slicing through mediocre leads and surfacing the accounts that actually fit your strategy.
But filters only help if you know what you’re looking for. You need a plan, not just a pile of data. Here’s how to get started, step by step.
Step 1: Get Clear on What “Good” Looks Like
Before you touch a filter, nail down your Ideal Customer Profile (ICP). If you don’t know what you want, no tool will magically fix that.
Ask yourself: - What size company do you actually want? (Revenue? Headcount? Both?) - What industries or niches do you do best with? - Where are your customers located? - Are there red flags or instant dealbreakers? - What tech stack or signals would make an account a slam dunk?
Pro tip:
If you have existing customers, start by looking for patterns among your best ones. Don’t overthink it—just jot down what they have in common.
What to Ignore
- Don’t get sucked into “maybe” accounts just to build a bigger list.
- Ignore vanity criteria (“cool brands” or “big logos”) unless they tie directly to your goals.
Step 2: Start With the Basics—Don’t Overcomplicate
Log in to Pandamatch, head to the company search or “Find Accounts” view, and open the advanced filters panel. You’ll see things like:
- Industry (sometimes called vertical or segment)
- Company size (by employees or revenue)
- Geography/location
- Funding stage
- Technologies used
Start simple: - Pick 2–3 must-have filters based on your ICP. - Avoid the temptation to layer on ten criteria right away. You’ll just end up with zero results or junk.
Example:
If you sell HR software for mid-sized tech companies in North America, try:
- Industry: Software/Technology
- Company size: 100–500 employees
- Location: United States, Canada
Step 3: Layer in “Dealbreaker” Filters
Now add filters that rule out bad fits. This is where you save hours later.
Common dealbreakers: - Already using a direct competitor (if Pandamatch shows tech installs) - Too small/big to matter - Wrong geography - In a regulated industry you can’t serve
How to do it in Pandamatch: - Use “Exclude” filters if available (e.g., exclude companies using X competitor). - If you’re not sure what a filter does, test it with a small list and see what actually changes.
Don’t:
Apply so many exclusions that you end up with a list of five impossible unicorns.
Step 4: Use Advanced Filters for Fine-Tuning
Here’s where Pandamatch’s advanced filters pay off. Depending on your account, you might see options like:
- Tech stack (what software they use): Great for SaaS sales.
- Hiring signals: Are they growing or shrinking?
- Recent funding: Signals budget or growth mode.
- Job posting keywords: Shows strategic priorities.
- Custom tags or firmographic data: Like certifications, compliance needs, or ownership type.
What’s actually useful? - Tech stack matters if switching costs or integrations are a big deal. - Hiring trends tell you who’s investing in your area. - Funding is helpful—but don’t obsess over it. Not all funded companies are ready to buy.
What’s mostly noise? - Social media buzz or “sentiment” scores. Fun for PR, usually useless for B2B sales. - Vague “intent” signals that aren’t connected to real buying behavior.
Pro tip:
Test your filters on a small sample first. Look at the actual companies it surfaces. If you’re getting weird results, tweak one thing at a time.
Step 5: Sort and Prioritize—Don’t Just Build a Massive List
Once you’ve filtered down to a manageable set, it’s time to prioritize. This is where most teams blow it—don’t just dump everything into your CRM.
How to prioritize in Pandamatch: - Use sorting features: By company size, funding date, or whatever matters most. - Tag or “star” your A-list accounts. - Export only your top tier for outreach. Ignore the rest for now.
Scoring approaches that actually work: - Assign a simple points system (e.g., 1 point for each must-have, -1 for each risk). - If you have historical win/loss data, look for patterns and apply those as bonus filters or columns.
What to avoid: - Overcomplicated scoring models—if it takes longer to set up than to just look at the list, skip it. - Chasing “hot leads” just because they’re new. Focus on fit, not just activity.
Step 6: Build and Save Segments for Ongoing Use
Pandamatch lets you save filter sets or “segments.” Use this—don’t reinvent the wheel every week.
Best practices: - Name segments by ICP (e.g., “Mid-market SaaS, US, 100–500 employees”). - Create a few key segments for different campaign types or reps. - Review and update saved filters every quarter or when your ICP changes.
Don’t bother with: - Micro-segments that are too narrow to be useful. - Saving every random filter combo “just in case.”
Step 7: Rinse, Review, and Iterate
Segmentation isn’t one-and-done. Markets shift, your product evolves, and what worked last quarter might flop today.
What to do: - Schedule time every month or quarter to review your segments. - Ask your team: Are we seeing good accounts? Are we wasting time on duds? - Adjust filters based on real-world feedback, not wishful thinking.
Warning:
If your team isn’t actually using the segments, something’s broken. Either the filters are off, or you’re overcomplicating things.
Quick Tips and Honest Takes
- Don’t be afraid to start simple. You can always add filters, but undoing a tangled mess is a pain.
- Ignore features you don’t need. Not every shiny filter adds value.
- Talk to sales and marketing. The best filters are built from real feedback, not guesses.
- Exporting junk is still junk. A focused list of 50 real targets beats 1,000 random companies every time.
Keep It Simple, Keep It Moving
Segmenting and prioritizing accounts isn’t magic—it’s just discipline. Tools like Pandamatch are only as good as the thinking behind your filters. Start with what matters, check your work, and don’t get lost in the weeds. Iterate as you learn, and you’ll spend less time chasing bad leads—and more time closing real deals.