How Dropcontact uses column headers to recognize data in my file?

When you upload a file to Dropcontact for enrichment, the tool automatically detects the data it needs, as long as your column headers clearly describe the type of information they contain.

Here’s how it works 👇

💡 Why are column headers important?

Dropcontact identifies and enriches your data based on the column names in your file.
Well-named columns allow Dropcontact to automatically recognize what each column contains - such as first name, company, or LinkedIn profile - and match it with the right enrichment fields.

If your headers are correctly labeled, you won’t need to manually map anything. 

Here are some examples of headers Dropcontact understands 👇

💡 Tip: Dropcontact recognizes many header variations — as long as they describe the data clearly, you don’t need to rename them exactly.

🧹 Should I remove unnecessary columns?

Not at all.
You don’t need to delete columns that aren’t useful for enrichment (for example, a Contact ID or Created Date).

Dropcontact will:

• Automatically select only the columns it needs for enrichment,
• Ignore the rest, but
• Keep all your original data in the output file.

✅ No loss of information: All your original columns are preserved in the enriched file.

If your file comes from a LinkedIn scraping tool, Dropcontact is already familiar with this kind of format and will automatically detect all the right columns: no need to rename anything.

🔗 What if Dropcontact doesn’t recognize my headers?

If Dropcontact doesn’t seem to recognize your column headers correctly, start by checking that they clearly describe the data; for example, Full Name, Company, or LinkedIn URL.

Renaming them with clearer titles often fixes the issue right away.

If the problem persists, or if you’d like Dropcontact to automatically recognize a specific recurring file format, feel free to reach out to our team at support@dropcontact.com 💌