If you’re dealing with cold outreach, you know the drill: messy prospect lists, bounced emails, and that nagging feeling your list is working against you. This guide is for anyone who’s tired of wasting time with bad data—and wants to use Scrubby to actually make their outreach better, not just “more automated.”
Here’s how to import, clean, and prep your prospect data in Scrubby, step-by-step, with real talk about what matters and what’s just fluff.
1. Get Your Data Together (and Actually Look at It)
Before you even touch Scrubby, make sure you know what’s in your file. Most people slap together a CSV, cross their fingers, and hope Scrubby (or any tool) will magically fix their mess. Don’t be that person.
What you need: - A CSV, XLSX, or Google Sheet with your prospects. - At minimum: first name, last name, and email. Company and role help, but don’t invent data just to fill columns.
Quick self-check: - Are all emails in one column? - Are there weird symbols or blank rows? - Duplicates? (You’d be surprised.)
Pro tip: Open your file in Excel/Google Sheets and do a quick scan. If you see “info@company.com” or “test@test.com” more than once, you’ve got cleanup to do before you even start.
2. Import Your File Into Scrubby
Once your file isn’t a total disaster, log in to Scrubby and go to the “Import” section. Here’s what actually happens:
- Choose your source: Upload a local file or connect Google Sheets. If your sheet has multiple tabs, make sure you pick the right one.
- Map your columns: Scrubby tries to guess which columns are “Email,” “First Name,” etc. Don’t trust it blindly. Double-check each mapping—bad mappings mean bad data downstream.
- Preview import: Scrubby usually shows you a sample. If it looks weird here, it’ll look weird everywhere. Go back and fix it.
What to ignore: Don’t get caught up in optional fields unless you actually use them in your outreach. “Industry” or “Revenue” sounds nice, but if you never use that info, it’s just clutter.
3. Let Scrubby Do Its Thing (But Don’t Trust It Blindly)
Scrubby will now analyze your list. This usually means:
- Validating emails: Checks for correct format and whether the address can actually receive mail.
- Deduplication: Finds obvious duplicates—though it’s not perfect.
- Flagging risky addresses: Catch-alls, role accounts (like “sales@”), or domains known for bouncing.
Here’s the honest scoop:
- Email validation is useful, but not magic. Scrubby can’t guarantee 100% deliverability—no tool can. You’ll still get some bounces.
- Deduplication is only as good as your data. “Jane Smith” and “jane.smith@company.com” might be flagged as separate if the names are slightly off.
- Risky addresses: It’s up to you to decide if you want to keep or cut these. If you need volume, keep them. If you want quality, ditch them.
Pro tip: Download the “flagged” or “invalid” list and check if any high-value prospects got caught by mistake. Sometimes legit emails get flagged.
4. Clean Up: Fix, Remove, or Tag Bad Data
Here’s where the real work happens. Scrubby’s analysis will show you:
- Invalid emails (remove these)
- Duplicates (merge or remove)
- Role accounts or catch-alls (your call)
Action steps: - Remove all invalid emails. Don’t argue, don’t overthink—just delete them. - Decide on role/catch-all addresses. If you’re sending cold emails, these get lower reply rates and higher bounce rates, but sometimes they’re your only way in. - Tag questionable entries. Use Scrubby’s tagging or notes features to mark anything you want to revisit. But don’t let “maybe later” become “never.”
Don’t bother: Trying to fix every single entry. If you have hundreds of rows, focus on what you can control: valid, real people with real emails.
5. Standardize Fields for Personalization
Most outreach fails because the “personalization” is generic or broken. Scrubby can help, but again, it’s garbage in, garbage out.
What to check: - First names: Are they capitalized? “john” looks lazy. Fix it. - Company names: Consistent formatting (“Acme Inc.” vs “acme”). - Custom fields: If you use “{job_title}” in your emails, make sure that field is actually filled in for most prospects.
Quick fixes: - Use Scrubby’s “standardize” tools to auto-capitalize or format. - Remove rows where key fields are blank. An email that starts “Hi ,” is an instant delete.
Pro tip: Don’t overcomplicate. If you can’t automate it cleanly, leave it out of your messaging.
6. Export or Sync Your Clean List
Once your data looks good:
- Export as CSV or XLSX for use in your outreach tool.
- Or, sync directly if your platform supports it (like importing straight to Outreach, Apollo, or HubSpot).
What matters: Use the cleaned list, not the raw import. And save a backup—you’ll thank yourself later.
Avoid: Pulling new versions from your CRM every time. You’ll just be cleaning the same junk over and over.
7. Keep It Clean—Set a Simple System
The first clean is the hardest. Make it easy for “future you”:
- Save your cleaned files with clear names (“Prospects_June2024_CLEAN.csv”).
- Schedule regular cleanups—every month is plenty for most teams.
- Train anyone touching your prospect lists to do a basic check before importing.
Not worth it: Obsessing over 100% perfection. Good enough is truly good enough here.
What Works, What Doesn’t, and What to Ignore
Works: - Running every list through Scrubby before outreach. - Removing obvious junk (invalids, duplicates, blanks). - Standardizing fields you actually use.
Doesn’t work: - Hoping Scrubby (or any tool) will rescue a trash list. - Personalizing with missing or sloppy data. - Chasing down every “maybe bad” email—set a standard and move on.
Ignore: - Fancy data enrichment unless you’re actually using it. - Exporting new lists every week. Quality beats quantity.
Wrap-Up: Keep It Simple (and Don’t Overthink It)
You don’t need perfect data to get better results—just a process that catches the worst offenders. Scrubby is a solid tool, but it’s not a silver bullet. Import, clean, standardize, and move on. Focus on what matters: reaching real people with real messages. And when in doubt, delete the junk and hit send.