If you’re running B2B campaigns, you already know: blasting the same message to everyone is a losing game. Segmentation is where the magic happens. The problem? Most tools make it harder than it should be. This guide is for marketers, SDRs, and founders who want to cut through the noise and actually use their data—without needing a data scientist or three hours of YouTube tutorials.
Here’s how to get real, usable segments out of Databar so you can target the right leads, skip the fluff, and finally see better results.
Step 1: Get Your Lead Data into Databar
Let’s start at the obvious place: your leads have to be in Databar before you can do anything with them.
What you need: - A CSV file (or spreadsheet) with your lead data. Think: company name, contact info, industry, size, etc. - Access to Databar (with permissions to import data).
How to do it: 1. Log in to Databar. 2. Find the “Import” or “Upload Data” option. This is usually on the dashboard or under a “Leads” section. 3. Upload your CSV or connect your CRM directly if Databar supports it. 4. Make sure your columns map to Databar’s fields correctly. 5. Hit “Import” and let it process.
Pro tip: Don’t overthink the data you upload. Start with what you have—it's easier to add more later than to get stuck waiting for “perfect” data.
What to ignore:
Don’t get bogged down cleaning every field perfectly before uploading. Dirty data is a problem, but you can fix most of it inside Databar.
Step 2: Define Segmentation Criteria That Actually Matter
Before you start slicing and dicing, get clear on what you care about. Not every field is worth segmenting on.
Questions to ask: - Who are your best customers? (Look for patterns in industry, size, location, tech stack, etc.) - Who do you not want to target? (Freelancers? Companies too small? Wrong region?) - What signals a high-intent lead for you? (Job title, recent funding, tech used, etc.)
What works:
Simple segments. Don’t get fancy out of the gate. Example segments:
- Industry (e.g., SaaS, manufacturing, professional services)
- Company size (e.g., 1-10, 11-50, 51-200 employees)
- Geography (e.g., North America, EU, APAC)
- Technology used (if Databar can enrich this for you)
What doesn’t:
Ultra-niche segments before you have enough leads. Splitting a list of 100 into 10 micro-segments is a fast way to get… nowhere.
Step 3: Use Databar’s Filters and Enrichment Features
Here’s where Databar earns its keep.
How to segment: 1. Open your lead list in Databar. 2. Use the filtering tools to select leads by: - Industry - Company size - Location - Funding stage - Installed technologies (if available) - Any custom fields you imported
Enrichment:
If you’ve got partial data, Databar can often enrich it—adding missing details like company size, LinkedIn URLs, or tech stack. Do this after uploading, not before.
Pro tip:
Try building a few “saved segments” you can reuse—like “US SaaS companies with >50 employees.” Don’t make more than 3-5 at first.
What to ignore:
Don’t get sucked into every data field. If the info doesn’t shape your messaging or targeting, leave it out for now.
Step 4: Export or Sync Your Segments for Marketing
Once you’ve got your groups, it’s time to actually use them.
Options: - Export CSVs: Most email tools let you upload a list, so export your segment and bring it into your email or ad platform. - Direct integrations: If Databar connects to your CRM or email tool, set up a sync so segments update automatically.
Tips for action: - Double-check your exported data for weird formatting or missing emails. - Name your segments clearly (“US SaaS 50+” beats “Segment 1”). - If using automated syncs, set alerts for sync failures—nothing’s worse than marketing to the wrong list because of a silent error.
Step 5: Personalize Your Outreach (But Don’t Go Overboard)
Now that you have actual segments, tailor your messaging to what matters to each group.
How to personalize: - Reference industry pain points in your copy. - Mention relevant technologies or recent company news (if you have it). - Adjust offers based on company size or role.
What works:
Simple, direct personalization. “We help SaaS companies like yours…” is enough. You don’t need to scrape their CEO’s dog’s name from Instagram.
What doesn’t:
Overautomation. If your emails sound like a robot wrote them, nobody will care. Use merge tags, but keep it human.
Honest Pros and Cons of Databar for B2B Segmentation
What Databar does well: - Quick filtering and sorting—beats Excel any day. - Enrichment can save a ton of manual research. - Easy to export or sync segments.
What to watch out for: - Data enrichment isn’t perfect. You’ll get the occasional outdated or incorrect info, especially on smaller companies. - Integrations aren’t magic. Expect to troubleshoot at least once. - You still need to know what to segment on—Databar helps organize, but won’t tell you your ideal customer profile.
Common Pitfalls (and How to Dodge Them)
- Trying to segment too soon: Get a decent-sized lead list first, then break it down.
- Analysis paralysis: Don’t waste hours making the “perfect” segment. Good enough is good enough.
- Ignoring data hygiene: Fix obvious issues (duplicates, missing emails) but don’t obsess over a few typos.
- Letting the tool dictate strategy: Databar is a means, not an end. Know your goals before jumping into segmentation.
Keep It Simple, Iterate, and Don’t Overthink It
Segmentation is supposed to make your marketing easier, not turn into another project you never finish. Start with a couple of practical segments, see how they perform, and adjust as you go. Databar’s tools can save time and give you a leg up—but only if you keep the process grounded in what actually moves the needle for your business.
Bottom line: Get your data in, make a few smart segments, and start targeting. Tweak as you learn. That’s how you actually get results—and stay sane while doing it.