How to Connect FullEnrich to Excel (4 Methods Compared)

The Problem With Getting Sheet Data In and Out of FullEnrich

You have an Excel workbook full of prospect data — names and company domains pulled from LinkedIn, inbound form submissions, a stale CRM export — and none of it has contact information yet. FullEnrich can find the emails and phone numbers, but the default workflow is to export your list, upload it to the platform, run the enrichment, wait, download the results, and paste them back into the original workbook. If your data lives in Excel, that round-trip runs against every instinct you have about where work is supposed to happen.

FullEnrich is good at aggregating contact data across 15+ vendors in a single waterfall lookup. But the connective tissue between it and your workbook is entirely manual. Every enrichment run means a CSV export, a file upload, and a reimport — with all the column-alignment pain that brings.

Below are the four common ways teams handle this. Only the last one scales.

Method 1: Manual Copy-Paste

The default flow for Excel users typically starts with a CSV export: you save the worksheet as a CSV, upload it into FullEnrich's bulk enrichment tool, match your columns to the expected input fields, kick off the job, download the result file, and then open it alongside your original workbook to paste the new columns in — confirming row order, fixing the header row, and tracking down the five rows that shifted because the CSV export added a blank line somewhere.

Once is just a data task.

The second time you're doing this for the same campaign — different segment, same workbook, same column-matching ceremony — you realize you've built yourself a recurring data chore that the work itself doesn't actually require.

Method 2: Power Automate

Power Automate has connectors you can use to call external APIs on a schedule or when a row changes. You could build a flow that reads from your Excel worksheet, sends each contact to FullEnrich, and writes the enrichment result back.

Before going further — are you comfortable with Power Automate's expression language? Do you know how to parse a JSON response and map specific fields back into table columns? Have you worked with API authentication inside an HTTP connector? If any of those feel unfamiliar, this isn't your path. Jump to Method 3 or 4.

For builders who are still here: the flow can work. But setup means configuring the right trigger, handling authentication, writing the HTTP request body to match FullEnrich's input schema, parsing the response, and testing it on a safe subset before running it on your full list.

One row per trigger invocation is the structural limit.

If you need to enrich 400 contacts before the campaign goes out Thursday, that's 400 trigger fires — each one making an API call, waiting for a response, and attempting a writeback. When row 217 returns a null result and the flow silently marks it as complete, you find out at the end when the column is empty.

You probably just need the verified emails and phone numbers from this list before Monday's send. You probably have no idea how to handle partial enrichment failures inside a Power Automate flow — and you shouldn't have to. So you push this to whoever manages your automation flows, and now you're waiting to hear if they can fit it in before the weekend.

Cost and complexity grow as soon as you start adding conditional steps for row-skipping, error handling, or batch scheduling.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable workbook ↔ enrichment workflows was a category of add-ons that let you configure column mappings and save them as reusable templates. You picked your input range, tagged your fields, saved the config, and ran it on demand.

That was a real step forward from manual CSV exports. Configs were reusable. Results landed in the same columns every time. The team didn't have to redo the field mapping on each run.

But you were still responsible for every piece of the template — which fields to pass, which columns to write, whether to skip already-enriched rows, how to handle null results. The tool moved the data; the thinking was still entirely on you. And when the workbook structure changed or FullEnrich updated a field name in its response, the config broke until someone went back and fixed it.

This is the previous generation. It worked, but it asked a lot of the operator.

The Easy Way: Using SheetXAI in Excel

There is a different way entirely. SheetXAI is an AI agent that lives inside your Excel workbook. It reads the workbook, understands what you're looking at, and through its built-in FullEnrich integration it can run bulk enrichments, reverse-email lookups, and people searches for you — writing results back into the columns you name. No CSV export, no file upload, no template to maintain. You just ask.

Example 1: Bulk-enrich 500 prospects with verified email and phone

Enrich all rows in the Prospects worksheet using the First Name, Last Name, and Domain columns — run a FullEnrich waterfall lookup and write the verified work email and direct-dial phone number into columns E and F

SheetXAI runs the enrichment across every row in one pass, writes email into column E and phone into column F, and flags rows where FullEnrich returned no result so you know exactly what's missing before the campaign goes out.

Example 2: Reverse-enrich inbound leads from email addresses alone

For every email in column A of this workbook, run a FullEnrich reverse email lookup and write the returned first name, last name, company name, and job title back into columns B through E — skip any row that already has a value in column C

The pattern: instead of cleaning the data first and then moving it, you ask for both in one prompt. SheetXAI handles the skip-logic inline.

Try It

Get the 7-day free trial of SheetXAI and open any Excel workbook with prospect data, then ask it to run a FullEnrich enrichment on the rows. The FullEnrich integration is included in every SheetXAI plan.