If you’re wrangling Salesforce data and using Tractioncomplete, you already know that field mapping isn’t just a checkbox on an import wizard—it’s the difference between clean, usable records and a total mess. This guide is for admins, ops folks, and anyone who’s ever muttered “why did that end up there?” after an import. We’ll walk through how to customize field mapping in Tractioncomplete to make sure your data lands where it should. No fluff, no hand-waving—just practical steps and honest advice.
Why Field Mapping Matters (and Where It Goes Wrong)
Let’s get real: Salesforce is picky about where data lives. If you import a CSV and the “Company Name” column ends up mapped to the billing address, you’ll spend more time cleaning than importing. Tractioncomplete tries to help by auto-matching fields, but it’s not psychic. Custom fields, odd naming, and mismatched formats throw a wrench in things.
Here’s what field mapping actually does: - Matches columns from your import file to Salesforce fields. - Lets you control what gets overwritten, merged, or ignored. - Handles custom fields, picklists, and weird data types (mostly).
If you skip customizing your field mapping, you’re rolling the dice. Best case, you have to fix a few records. Worst case, you scramble your CRM and everyone’s mad at you.
Step 1: Prep Your Data Before Import
Don’t start in Tractioncomplete yet. Save yourself a headache by making sure your data is ready: - Clean up column headers. Use field names that actually make sense (or, better, match your Salesforce fields). - Remove junk columns. If you don’t need it in Salesforce, cut it now. - Check data formats. Dates, picklists, and numbers should be consistent—no “Jan 1” and “01/01/2023” in the same column. - Watch out for duplicates. Decide if you want to merge, update, or skip duplicates later.
Pro Tip: Download a sample export from Salesforce with the fields you care about. Use those as your template for naming columns.
Step 2: Start a Data Import in Tractioncomplete
Let’s get into Tractioncomplete. Not every org has the same setup, but the basics are: 1. Log in. Open Tractioncomplete from your Salesforce instance or via its standalone interface. 2. Choose your import type. Usually, you’re importing Accounts, Contacts, Leads, or custom objects. 3. Upload your file. Drag-and-drop your CSV or pick it from your computer.
You’ll hit the field mapping screen next. This is where you can fix what the auto-matcher gets wrong.
Step 3: Review Tractioncomplete’s Auto-Mapped Fields
Tractioncomplete will try to “guess” which columns go where. Sometimes it nails it; sometimes it’s way off. Here’s what you should do: - Scan for mismatches. Did “First Name” get mapped to “Primary Contact”? That’s a red flag. - Look for unmapped fields. Anything in your CSV that isn’t mapped will not import. - Check custom fields. These almost always need manual mapping.
Don’t trust the auto-mapping blindly. It’s a starting point, not the finish line.
Step 4: Customize Your Field Mapping
This is where you actually take control: 1. Manual mapping. For each column, use the dropdown to pick the right Salesforce field. If you don’t see your field, double-check your object and field-level security settings. 2. Handle custom fields. Custom fields sometimes have cryptic API names. Hover over the field name to see the full label if you’re unsure. 3. Ignore unnecessary columns. If there’s a column you don’t want to import, set it to “Do Not Map” or leave it unmapped. 4. Map picklists carefully. If your import file uses different values than your Salesforce picklist, you’ll need to normalize those (either now or in your CSV).
What doesn’t work well:
- Auto-matching with inconsistent naming. If your columns are called “Cust_Name” and your Salesforce field is “Customer Full Name,” Tractioncomplete won’t connect the dots.
- Mapping to formula fields. You can’t import data into formula fields. Ignore them.
- Importing into lookup fields. This can work, but only if you have the right IDs or unique values. Otherwise, you’ll get errors or blank lookups.
Step 5: Save Your Mapping for Next Time (If You Can)
If you do this import regularly, look for a “Save mapping” or “Mapping template” option. Tractioncomplete supports this in some versions. This saves you from repeating all this work: - Give your mapping a clear name (“Q2 Account Import – Custom Fields”). - Review it every few months—field names and requirements change.
If there’s no save feature in your version, keep a cheat sheet or screenshot handy.
Step 6: Run a Test Import (with a Small Sample)
Don’t import your whole file yet. Use a sample of 10-20 rows to check: - Fields land in the right place. - Picklists and lookups behave as expected. - No weird errors or skipped rows.
If something looks off, go back and tweak your mapping. Don’t be afraid to run a few tests—fixing 20 records is easy; fixing 20,000 is a nightmare.
Pro Tip: Always double-check record ownership and required fields. Missing these can cause silent failures or orphaned records.
Step 7: Import the Full Data Set
Once your test looks good: 1. Import the full file. 2. Watch for errors—Tractioncomplete will usually flag rows that fail. 3. Download error logs and review them. Don’t just ignore them; they tell you what needs fixing.
If you see a pattern in the errors (like missing required fields or data type mismatches), adjust your CSV and re-import those rows.
Step 8: Review and Clean Up in Salesforce
After the import’s done: - Spot-check a few records in Salesforce. Are the fields populated like you expected? - Use Salesforce reports or list views to validate the new data. - Update any user training or documentation if field names or data processes changed.
If you find issues, fix them before anyone else starts using the data. The longer you wait, the harder it gets.
What to Ignore (and What Not to Sweat)
- Don’t map fields you don’t use. More isn’t better. Focus on what’s actually important.
- Ignore fields with formulas or calculated values. These update automatically in Salesforce.
- Don’t overthink mapping one-off imports. If it’s a rare job, brute-force it and move on.
But don’t ignore: - Mapping required fields—Salesforce will block the import if these are missing. - Data consistency—garbage in, garbage out.
Troubleshooting Common Field Mapping Headaches
1. Custom Field Not Showing Up?
Check your Salesforce permissions. Sometimes fields are hidden based on profile or field-level security.
2. Lookup Fields Throwing Errors?
Make sure your import file has the correct Salesforce IDs or unique values (like email). Names alone might not work.
3. Picklist Values Not Accepted?
The import will fail if your CSV has picklist values not allowed in Salesforce. Standardize your values ahead of time.
4. “Unknown Error” or Rows Skipped Without Explanation?
Download the error log. Sometimes the messages are cryptic, but they’ll usually point you in the right direction.
Keep It Simple, Iterate Often
Customizing field mapping in Tractioncomplete isn’t rocket science, but it does take a few extra minutes to get right. Take the time to prep your data, double-check your mapping, and always run a test import. Don’t try to map every possible field—start with what matters, and improve as you go. The less you try to do in one go, the fewer late-night cleanup sessions you’ll have down the road.