The Scenario
The growth team finished a LinkedIn prospecting campaign three weeks ago. A thousand profile URLs ended up in the 'LinkedIn Prospects' tab of the shared sheet — scraped from Sales Navigator searches across five industries. Nobody got around to enriching them because the person who ran the campaign is on leave and the handoff doc said "just run it through Dropcontact when you get a chance." Now it's your problem, and the sales team is asking when the contact data will be ready.
The bad version:
- Chunk the 1,000 URLs into batches manually — Dropcontact's API has limits per request — and submit each batch through the dashboard, keeping track of which request ID maps to which batch of rows.
- Wait for each async job to complete, download each result file separately, and stitch the outputs back together into the original sheet, matching enriched data back to the correct LinkedIn URL row.
- Catch the rows where Dropcontact returned a partial match — email found but name wasn't, or vice versa — and decide what to do with them before the list goes to the sales team.
A thousand rows across four manually managed batches is a full afternoon of work, and that's if nothing goes wrong. If one batch silently fails, you might not catch it until the sales team notices gaps.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads your LinkedIn URL column, handles the batching logic automatically, polls all async Dropcontact jobs in parallel, and writes verified email addresses and contact fields back into the correct rows — without you managing a single request ID.
Read all rows in the 'LinkedIn Prospects' sheet (column A = LinkedIn URL), send them in batches of 250 to Dropcontact, poll each request_id until done, and write verified email and name into columns B, C, D.
What You Get
- Column B: verified professional email address for each LinkedIn URL Dropcontact successfully matched.
- Column C: first name returned from Dropcontact enrichment.
- Column D: last name.
- Rows where Dropcontact returned no match or flagged confidence as low get a note in column E — visible for review, not silently blank.
What If the Data Is Not Quite Ready
Some LinkedIn URLs are malformed or point to company pages instead of personal profiles
Dropcontact enrichment requires personal profile URLs, not company page URLs. Mixing them in the same batch will produce errors for the company pages.
Before submitting to Dropcontact, filter the 'LinkedIn Prospects' sheet: rows where column A matches the pattern 'linkedin.com/in/' are personal profiles — flag these as 'Profile' in column B. Rows matching 'linkedin.com/company/' are company pages — flag as 'Company Page' in column B. Submit only the 'Profile' rows to Dropcontact in batches of 250 and write enriched email and name into columns C, D, E.
The list was built across multiple campaigns and has significant URL duplicates
A thousand scraped URLs often contains 15-20% duplicates when you combine multiple Sales Navigator searches.
Before submitting to Dropcontact, check the 'LinkedIn Prospects' sheet for duplicate values in column A. Keep the first occurrence of each URL, mark duplicates in column B as 'Duplicate — skipped'. Submit the unique rows to Dropcontact in batches of 250, poll for results, and write verified email and name into columns C, D, E for all unique rows.
You need the batching split across multiple tabs because the result set is too large to view in one place
Split the 'LinkedIn Prospects' sheet by campaign source using the 'Source' column (column B). For each distinct source value, create a separate output tab named after that source. Submit all rows to Dropcontact in batches of 250, poll for completion, and write enriched email, first name, and last name into the appropriate output tab based on which source group each row belongs to.
Enrich the full list, score by match quality, and surface the best leads in one operation
In the 'LinkedIn Prospects' sheet: deduplicate by column A, filter to personal profile URLs only, submit all valid rows to Dropcontact in batches of 250, poll until all jobs complete, write verified email to column B, first name to column C, last name to column D. Then score each enriched row: rows with a verified email get 'High' in column E, rows with email but low confidence get 'Medium', rows with no email match get 'Low'. Sort the sheet by column E descending.
When you combine the batch management, the enrichment, and the lead scoring into a single prompt, you hand off a ranked, enriched sheet — not a raw list that still needs prioritization.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with a column of LinkedIn profile URLs, then ask SheetXAI to batch-enrich them via Dropcontact and write the verified email addresses and contact fields back. Link to sibling articles: Bulk-enrich prospects with verified emails · Enrich emails with firmographic data · Dropcontact overview