Tips for importing and cleaning large contact lists in Sendler for accurate targeting

If you’ve ever tried to wrangle a giant contact list into a tool like Sendler, you know the pain: weird formatting, duplicates, outdated info, and a nagging feeling you’re about to blast the wrong people. This guide is for marketers, admins, or anyone staring down a spreadsheet and wondering, “How do I not screw this up?”

Let’s get your list into shape—without the usual headaches.

1. Get Your Contact List Ready Before Importing

Most import problems start with a messy spreadsheet. Fixing it now saves you hours later.

What matters:

  • Consistent formatting. Emails in one column, names in another, phone numbers standardized. Don’t mix things up.
  • CSV is king. Sendler loves CSV files. Excel and Google Sheets can export to CSV in seconds.
  • Limit columns to what you’ll actually use. If you’re not segmenting by “Favorite Color,” don’t include it.

Pro tip: Open your file in a plain text editor before importing. Weird characters, tabs, or broken lines are easier to spot here than in Excel.

2. Clean Up the Obvious Junk

Don’t trust your list to be perfect, especially if it came from multiple sources or an old CRM export.

What to watch for:

  • Duplicate contacts. Different spelling, same person? Merge or delete.
  • Invalid emails. Obvious typos (gnail.com, missing @, etc.)—fix or remove.
  • Empty fields. Blank emails are useless; filter these out.
  • Role-based emails. Addresses like info@ or sales@ usually aren’t worth importing. They rarely engage and hurt deliverability.
  • Old data. If you haven’t emailed someone in two years, consider if they belong on this list.

How to do it:

  • Deduplication: Excel’s “Remove Duplicates” or Google Sheets’ unique filter do the job for basic lists. For more, use a tool like OpenRefine or Dedupely.
  • Bulk email validation: Tools like NeverBounce or ZeroBounce catch invalid addresses fast. Don’t pay for dead weight.

3. Standardize and Normalize Your Data

Consistency avoids headaches later, especially with segmentation or personalization.

  • Names: Capitalize first letters, remove accidental spaces. “john smith” → “John Smith”.
  • Phone numbers: Pick one format (like +1 555-555-5555) and stick to it.
  • Custom fields: If you’re using tags or custom properties, make sure there’s one column per field and the values are predictable (e.g., “Yes/No” not “Y/N/yes/NO”).

Ignore: Hyper-specific data you’ll never use. You’re not running a census.

4. Prep Your CSV for Sendler

Now that your data’s tidy, make sure Sendler won’t choke on it.

  • Header row: The first row should be your column names: “Email”, “First Name”, etc.
  • No formulas. Sendler needs raw values, not =CONCATENATE(A1,B1). Copy and “Paste as Values” in Excel/Sheets.
  • UTF-8 encoding: Most CSVs are fine, but if you see weird characters (like é instead of é), re-save as UTF-8.

Pro tip: Keep your file under Sendler’s size limit (usually 10–20MB per upload). If you’re pushing those limits, split the list into chunks.

5. Importing to Sendler: Step-by-Step

Here’s how to get your cleaned list into Sendler without any drama:

  1. Log in to Sendler.
  2. Go to the “Contacts” or “Audience” section.
  3. Look for “Import” or “Upload Contacts.”
  4. Choose your CSV file.
  5. Map fields. Double-check that “Email” matches “Email,” “First Name” matches “First Name,” etc. Sendler will try to guess, but don’t trust it blindly.
  6. Set import options (like “Update existing contacts”).
  7. Start the import and watch for errors.

Watch out: If Sendler flags errors, download the error report. It’ll tell you which rows failed and why—fix those, then re-import just the failed ones.

6. Segment As You Import (If You Can)

If you want to target by region, status, or some other property, now’s the time.

  • Tag contacts. If your file has a “Tag” or “Group” column, Sendler can usually import these as segments or tags.
  • Don’t overthink it. Start with broad buckets (“Customers”, “Leads”, “Partners”). You can refine later.

Mistake to avoid: Trying to build perfect segments before you even hit “Import.” You’ll learn what matters after you send your first few campaigns.

7. After Import: Sanity Check and Quick Clean-Up

Even after all that prep, stuff slips through.

  • Spot check: Filter by “Date Added” to see your new contacts. Scan for weird names, missing emails, or obvious junk.
  • Test segment: Create a segment for your new contacts and send a small, internal test email. Make sure it looks right—no “Dear {{First Name}},” disasters.
  • Review bounces and complaints. After your first send, see who bounced or marked you as spam. Remove them right away.

8. What to Ignore (Most of the Time)

  • Overly granular data. You don’t need 50 custom fields unless you’re actually using them.
  • Fancy import plugins. Sendler’s built-in importer is usually enough. Third-party tools often add more confusion than value.
  • Chasing 100% perfection. Some errors just aren’t worth fixing, especially if it’s a handful of incomplete records. Focus on the 95% that matter.

9. Common Pitfalls and How to Dodge Them

  • Importing un-permissioned contacts. If you don’t have consent, don’t import them. You’ll nuke your deliverability and maybe get banned.
  • Ignoring list hygiene. Cleaning is not a one-time thing. Set a reminder to review your list every few months.
  • Not testing. Always test with a small batch before hitting your full list.
  • Believing the hype. No tool or AI will magically clean your data. It still takes a human eye and a bit of common sense.

Wrapping Up

Don’t let a messy contact list tank your email campaigns—or your sanity. Clean, import, test, and don’t stress about being perfect. The best results come from keeping things simple, starting small, and improving as you go. If your first import isn’t flawless, just iterate. The people who win at targeting aren’t perfect—they’re persistent.