How to import and clean large contact lists using Crustdata tools

If you’ve ever fought through a massive, messy contact list, you know “just import and clean it” is the understatement of the year. This guide is for the folks who actually have to get it done—sales ops, marketers, admins—anyone facing a 10,000-row spreadsheet and a ticking deadline. We’ll walk through using Crustdata tools to import, clean, and wrangle your data into something usable, without losing your sanity or half your weekend.

There’s no magic button for perfect data, but there are some real tricks and a few potholes to avoid. Let’s get into it.

Step 1: Get Your Contact List Ready (This Matters More Than You Think)

Before you even touch Crustdata, spend a few minutes (or hours, honestly) on your source file. This is the single best investment you can make—garbage in, garbage out is as true as ever.

What works: - CSV is king. Crustdata’s import works best with plain CSVs. Avoid Excel files with multiple sheets, colors, or weird formatting. - One row, one contact. No merged cells. No notes jammed into the name field. - Columns should make sense. At a minimum: First Name, Last Name, Email, Company, Phone. Extra columns (like Title, Address) are fine, but don’t get cute.

What doesn’t: - Copy-pasting from Outlook or Gmail. You’ll get hidden characters and all sorts of junk. - Files with tons of blank rows or columns. - Custom date or phone number formats that only your team understands.

Pro tip:
Open your file in a plain text editor (Notepad, VS Code) to see if there’s invisible weirdness. You’d be surprised what Excel hides.

Step 2: Importing to Crustdata—The Right Way

Now, log in to Crustdata and head to the “Import Contacts” section. Here’s how to avoid rookie mistakes.

2.1. Choose “Upload CSV”

Don’t bother with manual entry or copy-paste options for big lists—they’re slow and error-prone.

2.2. Map Your Fields

Crustdata tries to auto-match your columns to fields in its database. Double-check every mapping. If it guesses wrong, you’ll have a mess.

  • If your column is called E-mail Address but Crustdata wants Email, fix it.
  • Unmapped columns will get ignored, often without warning.

2.3. Set Up De-duplication (Don’t Skip This)

Crustdata lets you pick fields to check for duplicates—usually email is the best bet.

  • Best practice: Always dedupe by email. If you don’t have emails, use phone, but know it’s less reliable.
  • Don’t trust “combine by name.” Names are way too common and inconsistent.

What to ignore:
“Advanced matching” options that promise to magically combine contacts across six fields. These are more trouble than they’re worth unless you’re a data scientist.

2.4. Run a Preview Import

Crustdata shows you a sample of how the import will look. Scan it for obvious problems: names in the wrong columns, garbled characters, “NULL” where you expect data.

  • If anything looks off, cancel and fix your CSV. It’s much easier than cleaning up after a full import.

Step 3: Clean Up Your Data After Import

Even with a perfect CSV, you’ll need to tidy up. Crustdata has some built-in tools, but don’t expect miracles—plan on a little manual work.

3.1. Use Built-in Cleaning Tools

  • Bulk Edit: You can select a batch of contacts and fix fields like company or phone format.
  • Standardize Fields: Crustdata can auto-format phone numbers and capitalize names, but it’s not infallible. Double-check samples before running bulk actions.
  • Remove Duplicates: If you skipped dedupe earlier, now’s your last good chance. Crustdata can scan and merge, but always review what it’s about to combine.

3.2. Filter and Tag Your Contacts

Tags help you segment later. After import, filter by fields like Source, Region, or whatever matters to you, and apply tags in bulk.

What works: - Tag by source (“2024 Event List”, “Old CRM”, etc.) so you can undo mistakes or review later. - Use filters to find contacts missing key data (like no email) and clean or remove them.

3.3. Manual Review: Still Necessary

No software is perfect. Spot-check your biggest segments:

  • Look for “Firstname Lastname” in the email field (it happens).
  • Watch for contacts with the same name but different emails—merge if needed.
  • Check for non-standard characters, especially if you imported international names.

Pro tip:
Sort your contacts by each field and scroll through—patterns and outliers jump out this way.

Step 4: Handle Common Headaches

Let’s get real. No tool solves every problem. Here’s what you’ll run into, and what to do about it.

4.1. Weird Characters and Encoding Issues

If you see gibberish or question marks in names, your CSV probably wasn’t saved as UTF-8 encoding.

Fix:
Resave your file from Excel or Google Sheets as “CSV UTF-8” and re-import. Crustdata plays nice with UTF-8, not so much with older formats.

4.2. Duplicate Contacts With Slight Differences

You’ll always have “Jon Smith” with jon.smith@email.com and “Jonathan Smith” with jon.smith@work.com.

Fix:
Pick a rule and stick to it. Either merge by email only, or keep both and tag them. Don’t let the software guess for you.

4.3. Incomplete or Junk Data

Contacts with no email, phone, or company are usually useless.

Fix:
Filter and delete, unless you have a plan to enrich them. Don’t keep junk “just in case.” It slows everything down later.

4.4. Overly Complex Custom Fields

Crustdata lets you add custom fields, but more isn’t always better.

Honest take:
Unless you have a solid process for keeping custom fields updated, stick with the basics. Extra fields become clutter fast.

Step 5: Export, Sync, or Share (Without Making a New Mess)

Once your list looks good, Crustdata lets you export to CSV, sync with other tools, or share access.

What works: - Export a clean backup before syncing with your main CRM—always have a fallback. - Set up syncs for future imports, but don’t automate everything until you trust your process.

What doesn’t: - Pushing unreviewed data into your live systems. Seriously, don’t. - Sharing edit access with people who aren’t trained—they’ll undo your work in minutes.

Pro tip:
Document your import/cleaning steps. Next time, you’ll spend half the time and avoid repeat mistakes.

Keep It Simple, Iterate Often

Cleaning big contact lists is never glamorous, and there’s no silver bullet. Crustdata speeds up the grunt work, but no tool is smarter than your process. Focus on getting the basics right: clean input, careful mapping, sensible deduplication, and a final manual check. Don’t chase perfection—just aim for “good enough to use,” then improve as you go.

If you keep things simple, document your steps, and don’t trust “magic” features, you’ll build a process that works for any list, no matter the size.