If you’ve ever tried to move contact data from one tool to another, you know how quickly things can get ugly: columns everywhere, missing names, emails that never existed, and duplicates galore. This guide is for anyone who wants to get high-quality contact data out of Harmonic and into their CRM—without spending the rest of the week cleaning up exported spreadsheets.
Whether you’re in sales, recruiting, or just tired of bad data, I’ll walk you through what actually works, what to skip, and how to end up with a contact list you won’t be embarrassed to import.
Step 1: Get Clear on What Data You Actually Need
Before you even open Harmonic, decide what “high quality” means for you. The default export from any tool—including Harmonic—almost always gives you more than you need and less of what you want.
Ask yourself:
- Which contact fields do I actually use in my CRM? (Name, title, company, email, LinkedIn, phone…)
- Are there any fields that just create clutter or confusion for my team?
- Is this export for a one-time import, or will I need to repeat it regularly?
Pro tip: Make a quick list of your CRM’s required fields and nice-to-haves. Check if your CRM has a data import template or required structure. You’ll thank yourself later.
Step 2: Set Up and Filter Your Search in Harmonic
Harmonic is great at surfacing people and companies, but the quality of your export depends entirely on how well you filter up front.
Here’s what tends to work best:
- Use advanced filters—don’t just export a big list and hope for the best.
- Filter by:
- Industry, location, seniority, or whatever’s relevant for your workflow.
- Exclude obvious junk: companies with no funding, people with missing emails, etc.
- Preview results. Harmonic usually lets you see sample rows—scan for weird data or missing info.
What doesn’t work:
Exporting giant, unfiltered datasets and hoping to “clean it up later.” You’ll spend hours sifting through garbage. Start with quality inputs.
Step 3: Select the Right Fields (Columns) for Export
When you’re ready to export, Harmonic will ask which fields you want. Resist the urge to select everything.
Focus on:
- Unique identifiers (email, LinkedIn URL, company domain)
- Core contact info (first/last name, title, company)
- Any custom fields you rely on (e.g., funding rounds, tags, notes)
Skip or deprioritize:
- “About” blurbs or long bios—they’re rarely useful in a CRM
- Social links you’ll never use
- Fields with lots of blanks
Why be picky?
More columns = more room for mismatches and import errors in your CRM. Less is better here.
Step 4: Export Your Data from Harmonic
Now, actually export the data. Harmonic usually offers CSV or Excel formats. Choose CSV unless your CRM specifically wants XLSX—CSV is less likely to break.
Quick sanity checks:
- Open the file before you do anything else. Make sure data isn’t shifted, weirdly formatted, or full of blanks.
- Look for duplicate rows or contacts with missing critical info (like email).
- If you see a bunch of “N/A” or blank rows, go back to your search and tighten your filters.
Pro tip:
If you’re dealing with more than a few hundred rows, consider splitting the export into batches (by company size, region, etc.). Large files are more likely to trip up your CRM’s importer.
Step 5: Clean Up Your Export (Don’t Skip This)
No matter how slick Harmonic is, you’ll almost always need to clean up your data. Here’s how to avoid the most common headaches:
- Deduplicate:
- Use Excel’s “Remove Duplicates” or Google Sheets’ “Unique” tool by email or LinkedIn URL.
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Watch for people who changed jobs—they might show up twice.
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Standardize Fields:
- Make sure “First Name” and “Last Name” aren’t merged into a single cell.
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Check for consistent formatting (no random caps, weird symbols, etc.).
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Fill in the Gaps:
- If you’re missing critical fields (like company domain), see if you can fill them in programmatically or manually for key contacts.
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If more than 20% of your rows are missing required info, consider re-exporting with better filters.
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Match CRM Import Requirements:
- Rename columns to match your CRM’s expected headers (e.g., “Work Email” vs. “Email”).
- Save as CSV UTF-8 to avoid character encoding weirdness.
What to ignore:
Don’t obsess over every missing LinkedIn or phone number—if it wasn’t in Harmonic, you’re unlikely to find it quickly elsewhere.
Step 6: Import the Data into Your CRM
Every CRM is a little different, but the basics are the same:
- Use your CRM’s import tool (look for “Import,” “Bulk Upload,” or similar).
- Map columns from your CSV to the correct CRM fields. Double-check mappings—this is where things usually go sideways.
- Import a small test batch first (10–20 rows). Check how it looks. Are fields in the right place? Any weird errors?
- If all looks good, import the rest.
If you hit errors:
- Check for invalid emails, missing required fields, or duplicate detection rules.
- Read the error messages—CRMs are rarely helpful, but sometimes they give you a clue (e.g., “Unrecognized column: ‘role_title’”).
Pro tip:
Keep your original CSV. If something goes wrong, you’ll want to revert or try again, not start over from scratch.
Step 7: Spot-Check and Validate Post-Import
Don’t just assume everything worked.
- Randomly check 10–20 imported contacts. Is all the info in the right place? Any weird characters or encoding issues?
- Look for duplicates or contacts with missing info that slipped through.
- If something’s off, fix it now—problems get exponentially harder to fix once people start relying on the data.
What Actually Matters (And What Doesn’t)
What Works
- Spending the extra 10 minutes up front to filter and select only what you need.
- Doing a small test import before pushing everything.
- Keeping a backup of your original export.
What Doesn’t
- Exporting everything “just in case”—it’s a pain to clean later.
- Ignoring field mapping warnings from your CRM.
- Hoping missing data will magically appear—use what you’ve got.
Wrapping Up: Keep It Simple, Iterate as You Go
Exporting high quality contact data from Harmonic to your CRM isn’t rocket science, but it’s easy to screw up if you rush or try to skip cleanup. Focus on only the data you need, do a quick manual check at each step, and don’t be afraid to redo the export if the first try isn’t clean.
Most importantly: don’t overthink it. Get your process dialed in, document what works, and update your approach as your needs change. The cleaner your data, the fewer headaches down the line.