If you’re in B2B sales or marketing, you already know: not all leads are created equal. Some are gold, most are just noise. You want to spend your time on the right accounts, not burn hours chasing the wrong ones. This guide is for anyone who wants to use data—specifically, data from Thecompaniesapi—to segment and score B2B prospects in a way that’s actually useful, not just “data for data’s sake.”
Let’s cut through the fluff and get into what works.
Step 1: Figure Out What Actually Matters (Don’t Skip This)
Before you run off to pull every data field under the sun, slow down. Start with your real-world criteria for a good prospect. Ask your team:
- Who actually buys from us?
- What makes a company a great fit (or a terrible one)?
- What are the “dealbreakers”—things that, if present, mean we shouldn’t waste another second?
Jot these down. Usually, you’re looking at things like: - Industry or vertical - Company size (headcount, revenue) - Geography - Tech stack or tools used - Funding rounds or financial health
Pro tip: Don’t overcomplicate this. Two or three variables are plenty to start. You can always get fancier later.
Step 2: Set Up Thecompaniesapi
Now you’re ready to get your data. Thecompaniesapi gives you access to company profiles, firmographics, tech usage, and more. It’s flexible, but don’t fall into the trap of “pull everything and sort it out later.” That’s a recipe for analysis paralysis.
Here’s what works:
- Decide which data points you actually need (from Step 1).
- Review Thecompaniesapi’s docs or UI—make sure these fields are available and well-populated.
- Test a few sample queries. If a field is missing or always blank for your target market, don’t build your system around it.
What to ignore: Vanity fields like “social followers” or “recent news mentions” almost never predict sales success. Focus on what’s actionable.
Step 3: Define Your Segments
Segmentation is just grouping companies in a way that makes sense for you. The classic mistake is slicing things too finely (e.g., “Midwestern SaaS companies with 37-44 employees using Azure and Mailchimp”). That’s fun for a spreadsheet, but useless for planning or outreach.
Start with broad, useful buckets. For example:
- By size: Small (<50), Medium (50-500), Large (>500)
- By industry: SaaS, Manufacturing, Agencies, etc.
- By location: US, Europe, APAC
Use Thecompaniesapi to pull these fields. Here’s a simple approach:
- Query for your target geography and industry.
- Break down the results by employee count or revenue.
- Tag each result with a segment label in your CRM or a spreadsheet.
Pro tip: If you’re not sure which segments matter, pick the top 2-3 customer types from your existing book of business and start there.
Step 4: Build a Scoring Model That’s Simple (and Actually Useful)
Lead scoring sounds fancier than it is. At its core, it’s just: “How much do we care about this company?” Don’t get seduced by machine learning or scoring models with 15 variables—those usually end up being noise. Here’s how to do it in the real world:
A. Pick Your Criteria
From Step 1, choose 2-4 traits that matter most. For example: - Industry match (yes/no) - Company size match (score: 0, 1, or 2) - Tech stack match (yes/no) - Geography (yes/no)
B. Assign Points
Give each criteria a score. Keep it simple: - 1 point if they match a key criteria - 0 points if they don’t
You can get fancier, but honestly, it doesn’t make much difference at this stage.
C. Set a “Good Fit” Threshold
Decide what a “good” score looks like. Maybe it’s 3 out of 4. Anything below that, don’t prioritize.
D. Automate It
Use Thecompaniesapi’s API or export features to pull the data and calculate the score automatically. Many CRMs let you set up custom fields or use a spreadsheet to run the math.
What doesn’t work: Relying on gut feel or browsing LinkedIn one-by-one. Automation isn’t magic, but it beats guesswork.
Step 5: Test and Iterate—Don’t “Set and Forget”
No model is perfect out of the box. Here’s what to do:
- Check the results: Are your “high scoring” companies actually buying? Or is something off?
- Tweak your criteria: If you’re getting too many low-fit companies, tighten your filters. If you’re missing good ones, loosen up.
- Talk to sales: They’ll tell you fast if the scoring is nonsense.
Pro tip: Set a calendar reminder to review your model every month or quarter. It’s easy to forget, and things change.
Step 6: Use Segmentation and Scoring in Real Life
It’s not enough to segment and score—you have to use the data to work smarter.
- Prioritize outreach: Start with high-scoring companies in your best-fit segments.
- Personalize messaging: Use segment info to tailor your emails or calls (“We help SaaS companies in Europe grow faster,” not “Dear Sir or Madam…”).
- Measure results: Track which segments and scores actually lead to closed deals. Adjust your model as you go.
What to ignore: Don’t bother with segmentation or scoring if you’re only handling a handful of leads per week. This is for when you’ve got more prospects than you can handle manually.
Real-World Tips and Pitfalls
- Don’t chase the perfect model. “Good enough” is better than nothing. You’ll refine over time.
- Garbage in, garbage out. If your data from Thecompaniesapi is outdated or incomplete, your scores will be too.
- Resist the urge to automate everything. Sometimes a quick manual check beats a fancy workflow, especially when something looks off.
- Don’t ignore your own instincts. If a company looks like a great fit but scores low, dig deeper—maybe your model needs an update.
Wrapping Up: Keep It Simple, Keep It Honest
Segmenting and scoring with Thecompaniesapi can help you focus on the accounts that matter, but don’t let it become a science project. Start with what you know. Use the data to save time, not create extra work. Test, tweak, and don’t be afraid to ignore stuff that isn’t helping.
You’ll get more out of this if you stay skeptical, keep things simple, and adjust along the way. That’s how you actually win with data.