If you’ve ever wrestled with importing a giant spreadsheet of contacts and ended up with a mess of duplicates, missing info, or weird formatting, you’re in the right place. This guide is for anyone who needs to get a big contact list into Bitscale and actually have it be usable—not just dumped in and forgotten. We’ll cover what works, what doesn’t, and how to avoid the classic headaches that come with handling large lists.
Step 1: Get Your Contact List Ready
Before you even open Bitscale, do yourself a favor and look at your contact file. If you toss garbage in, you’ll get garbage out—no fancy software can magically fix a broken spreadsheet.
What to do:
- Stick to CSV or XLSX: Bitscale handles both, but CSV is less likely to break (no weird formatting, no hidden formulas).
- Check your columns: Make sure you have consistent headers:
First Name,Last Name,Email,Phone, etc. Don’t get cute with column names; Bitscale expects the basics. - No merged cells or multi-row headers: Bitscale won’t know what to do with them. Clean them up first.
- Remove obvious junk: Blank rows, random notes, or “see attached” comments in cells—all of that should go.
Pro tip: If your file has over 10,000 rows, consider splitting it into chunks. Bitscale can handle big files, but you’ll save yourself a headache if something goes wrong.
Step 2: Importing the File into Bitscale
Now, let’s get your file into Bitscale without drama.
- Log in and head to the import tool.
- Usually, it’s under “Contacts” or “Import Contacts.”
- Choose your file.
- Click “Upload,” select your CSV/XLSX, and wait for the preview.
- Map your columns.
- Bitscale will try to guess which columns go where. Double-check this! For example, it might map “Mobile” to “Phone” instead of “Mobile Number.”
- If you see “Unmatched” columns, either map them manually or ignore them if you don’t need them.
- Set deduplication rules (if available).
- Most people skip this. Don’t! At minimum, set it to dedupe by email address—that’s the main unique identifier.
- If your list has no emails (bad sign), pick something else unique, like phone number.
- Start the import.
- For large files, this can take a while. Don’t refresh the page like a maniac; let it finish.
What doesn’t work:
Don’t try to upload a file with a million custom fields or random Unicode symbols. You’ll just end up with a failed import or a mess of unusable data.
Step 3: Cleaning Up After Import
No matter how careful you are, you’ll have some cleanup to do. Bitscale’s import is decent, but it’s not psychic.
Here’s what usually needs fixing:
- Duplicates: Even with deduplication, some will slip through—different emails, or typos in names.
- Weird characters: “Jöhn” instead of “John” or smart quotes from Excel. Do a quick search/replace or export and fix offline if needed.
- Empty fields: Decide if you care. If most contacts are missing a phone number, maybe delete the column.
- Obvious errors: Like emails in the phone field, or “N/A” as a name.
How to fix:
- Use Bitscale’s built-in filter/search to find and edit bad records.
- For massive lists, export the contacts after import, clean in Excel or Google Sheets, then re-import (yes, it’s annoying, but sometimes faster).
- Tag or segment contacts as you go. This is easier now than later.
Pro tip:
Don’t aim for perfection here. Get rid of the worst issues, but don’t let “cleaning” become a month-long project.
Step 4: Handling Special Cases (Duplicates, Invalids, and More)
Large lists always have gremlins—dead emails, repeated entries, or contacts that don’t belong.
Duplicates:
- Use Bitscale’s “Find Duplicates” feature if it has one. Otherwise, export and use Excel’s “Remove Duplicates” on emails or phone numbers.
- Decide which version to keep: usually the most recently updated, or the one with the most complete info.
Invalid Contacts:
- Use Bitscale’s validation tools to flag bad emails or phone numbers.
- Consider using a bulk email validator (third-party) before import for huge lists—Bitscale’s native tools are just okay.
Unwanted Segments:
- If your list combines totally different groups (e.g., customers and vendors), filter and tag them separately now. It’s a pain to untangle later.
What to ignore:
- Don’t obsess over fixing every single missing field. Focus on what you actually need to use.
Step 5: Setting Up for Ongoing Cleanliness
Imported lists decay fast. If you want your data to stay useful, you need a simple process.
Here’s what actually works:
- Regular exports: Every few months, export your list and scan for obvious problems.
- Deduplication on every import: Don’t trust that “just this once” is safe—set up dedupe rules every time.
- Minimal custom fields: The more fields you add, the more ways your data can go sideways.
- Train your team: If others are importing, show them this process. Sloppy imports are a top source of headaches.
Pro tip:
Set a calendar reminder for a quarterly data review. It’s boring, but it saves you from chaos later.
Honest Takes: What Works, What Doesn’t, and What to Ignore
- Bitscale’s import is solid for standard CSV/XLSX files, but not magic. If your source data is bad, expect problems.
- Automated cleaning tools are limited. Don’t expect them to fix typos or inconsistent formats reliably.
- Don’t waste time on over-cleaning. Get your list “good enough” and move on—nobody has time for 100% perfection.
- Ignore fancy AI enrichment promises. Most tools just guess and fill in blanks with junk. If you want reliable info, collect it yourself.
Keep It Simple and Iterate
Getting a giant contact list into Bitscale isn’t rocket science, but it does require some patience and a willingness to deal with messy data. Don’t get paralyzed by perfectionism or tempted by “one-click” cleaning tools—they rarely work as advertised. Focus on getting your list in, fixing the worst problems, and setting up a routine for future imports. Simple, repeatable processes will save you way more time than chasing after the perfect contact list.
Remember: Clean data is a journey, not a destination. Get started, keep it simple, and tweak as you go.