If you’ve ever pulled a CRM report and immediately doubted every number you saw, you’re not alone. Garbage data leads to garbage insights, and nothing kills trust in your CRM faster. This guide’s for folks who want to import their data into Copy (the CRM tool, not the verb) and actually trust what comes out. Whether you’re moving from a clunky old system or wrangling spreadsheets, you’ll get a no-nonsense walkthrough—what to do, what to skip, and how to avoid the pitfalls that turn CRM projects into a slog.
Step 1: Get Your Data Together (and Know Where It’s Coming From)
Before you even open Copy, figure out what you’re dealing with. Here’s what usually happens: people grab every export they can find, dump them together, and hope for the best. That’s how you end up with duplicates, weird formatting, and contacts named “Test123.”
Do this instead:
- List your sources. Old CRM, spreadsheets, email lists, marketing tools—write them down.
- Export cleanly. Always export in CSV or XLSX. Avoid PDFs or anything that needs manual copy-pasting.
- Note field names. Different tools call things different names (“First Name” vs. “Given Name”). You’ll need to match these up later.
Pro tip: If your data’s a mess, don’t try to fix everything up front. Just get it all into one place so you can see the problems clearly.
Step 2: Review and Prep Your Files
Now, open your files. This is the boring part, but it’s where most problems start if you rush.
- Open in Excel or Google Sheets. If you see merged cells, colors, or notes, flatten those out.
- Delete junk columns. If you see columns like “Last Login,” “Profile Pic URL,” or “Notes from 2017,” ask yourself if you need them.
- Standardize headers. Make sure “Email,” “First Name,” and “Last Name” are the same in every file.
What matters: You want each column to be one type of data, and each row to be one person, company, or record.
What doesn’t: Fancy formatting, hidden columns, or color coding. Copy doesn’t care, and it’ll just slow you down.
Step 3: Clean Up Obvious Errors
You don’t need to fix every typo right now, but you do want to avoid importing junk that’ll haunt you later.
- Remove duplicate rows. Excel and Google Sheets both have a “Remove duplicates” feature. Use it.
- Fix broken emails. Sort your “Email” column. Blank or obviously fake emails (“asdf@asdf.com”) should go.
- Check for missing required fields. If you need “First Name” and “Email” for every record, filter out rows where they’re missing.
Honest take: There’s always a tradeoff. If you spend days cleaning every record, you’ll never finish. Set a timer—an hour or two is plenty for most jobs.
Step 4: Import to Copy
Now you’re ready to bring your data into Copy. Here’s how to do it without tripping over the most common issues.
- Log in to Copy.
- Go to the Import section. Usually, you’ll find this under “Settings” or “Data Management.”
- Upload your file. Pick the CSV or XLSX you just cleaned.
- Map your fields. This is where you tell Copy that your “First Name” column matches its “First Name” field, and so on.
- Automatic mapping: Copy will try to match fields for you. Double-check—automation is great, but it’s not psychic.
- Manual tweaks: If something doesn’t match, fix it here. Don’t just hit “next.”
- Preview your import. Most systems show you a sample. If you see weirdness (missing names, shifted columns), stop and fix it.
- Run the import. Cross your fingers—but not really, because if you prepped well, this should just work.
Pro tip: Import just a small sample (10–20 rows) first. If it looks good, do the rest. Saves you from cleaning up a big mess later.
Step 5: Post-Import Checks (Don’t Skip This)
The “import complete” message is not your finish line. Now’s the time to check what landed in Copy.
- Spot-check records. Search for a few people or companies by name. Is their info correct?
- Look for obvious duplicates. If you see “John Smith” twice, something’s off with your deduplication.
- Test key fields. If you use tags, stages, or deal values, make sure they came over right.
What to ignore: Don’t worry about every tiny formatting issue right now. You’re checking for big-picture problems.
Step 6: Use Copy’s Built-in Cleansing Tools
Most CRMs, including Copy, have features to help you clean up after the fact. (Let’s be honest—no import is perfect.)
- Deduplication: Use Copy’s duplicate finder to merge or delete duplicates. Do this regularly.
- Bulk updates: If you need to fix a field for lots of records, use bulk edit instead of manual fixes.
- Validation rules: Set up rules in Copy to prevent junk from getting in next time (e.g., require valid emails).
Reality check: No tool will catch every issue. Automated cleansing is helpful, but manual review still matters—especially for small teams.
Step 7: Keep Your Data Clean Going Forward
If you stop at the first import, your data will rot again. Set up a simple routine.
- Schedule regular reviews. Once a month, check for duplicates or weird records.
- Train your team. Make sure everyone knows what should (and shouldn’t) go in Copy.
- Automate what you can. If you get data from web forms or other tools, use integrations to keep things consistent.
What to ignore: Don’t waste time on over-complicated data governance policies unless you’re a massive enterprise. For most teams, simple habits beat fancy systems.
Pro Tips and Things to Watch Out For
- Don’t trust old data blindly. If you’re importing from an ancient CRM, expect a lot of outdated info. Consider starting fresh or archiving inactive contacts.
- Custom fields can be a trap. Only create custom fields you’ll actually use. Too many fields = confusion.
- Beware of character encoding issues. If you see weird symbols (like �), check your file’s encoding (UTF-8 is safest).
- Back up before big changes. Always export your data from Copy before mass updates or imports—just in case.
Wrapping Up: Keep It Simple (and Don’t Chase Perfection)
Don’t fall for the myth that your CRM data has to be perfect before you do anything. Good enough is usually, well, good enough—especially if you’ve got a way to clean things up as you go. Focus on the basics: clear fields, no duplicates, and records you actually care about. The rest? Fix it over time. Iterate, review, and keep your process simple.
You’ll spend less time cleaning up after yourself—and more time actually using those CRM insights for something useful.