How to Connect IP2Location.io to Google Sheets (4 Methods Compared)

The Problem With Getting Sheet Data In and Out of IP2Location.io

You have a Google Sheet full of IP addresses — sign-up IPs, transaction IPs, access-log entries, raw server exports — and you need geographic context: country, city, ISP, whether each one is behind a proxy. IP2Location.io returns all of that in a single API call. But getting a column of IPs into that API and the results back into your sheet is a chain of steps that doesn't happen on its own.

The default flow is: export the IPs, write a script or hit the API manually, parse the JSON, paste the results back, and repeat every time the dataset refreshes.

Below are the four approaches people use. Only one of them keeps up.

Method 1: Manual Copy-Paste

You grab the IPs from your sheet, drop them into the IP2Location.io dashboard one at a time, read off the country and city, and type the values into a new column. For a handful of IPs this is merely tedious.

Once you're doing it for 200 sign-up IPs after every marketing campaign, you start to notice something: the work isn't hard, it's just relentless. Every lookup is the same motion. Same tab switch, same paste, same read, same type. By the fiftieth row your eyes are skimming and your error rate is climbing.

IP geolocation is machine work. Doing it by hand is a specific kind of drain that compounds every time the data refreshes.

Method 2: Zapier or Make

Both platforms have IP2Location.io connector options. You can set up a trigger on new rows in your sheet, call the IP2Location.io API with the IP from that row, and write the geolocation result back.

Before you read further — do you know what a webhook trigger is? A data transform step? An API authentication flow? If those phrases feel vague, this method is not the right path for you. Skip to Method 3 or 4.

If you're still here: the automation works. The issue is what it costs to get there. You pick a trigger — new row in the sheet, a schedule, a form submission — then map the IP field to the API call, configure the output field mapping, authenticate, test with a sample row, and debug whatever the response format doesn't match.

Once it's running, there's a structural ceiling you'll hit fast.

A trigger-per-row automation is not the same as a bulk enrichment.

Running 500 IPs through Zapier means 500 separate API calls, 500 task credits consumed, and a run history that becomes impossible to audit when row 312 silently fails because the IP field was blank.

You probably just need the geolocation data. You probably have no idea how to wire up a multi-step Zap with conditional error handling — and that's completely reasonable. So you push this to whoever on your team builds automations, and now you're waiting on Slack for something that should have taken ten minutes.

Once you need to filter by country, aggregate by ISP, or join against a second tab of known proxies, you've left Zapier's native scope entirely.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best repeatable option was a category of add-ons that let you configure a column mapping, save a template, and run it on demand. You picked the IP column, you tagged the output columns, you saved the config, you ran it.

That was a genuine improvement over copy-paste. The output was consistent, the config was reusable, and you didn't have to redo the field layout every time.

But you were still responsible for every piece of the template: which columns to write to, how to handle blank IPs, what to do when the API returned an unexpected field name. The add-on moved the data — the thinking was still entirely on you. And the moment your sheet structure changed, the config broke and stayed broken until someone manually updated it.

This is the previous generation. It worked, within limits.

The Easy Way: Using SheetXAI in Google Sheets

There is a different way entirely. SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet, understands the columns, and through its built-in IP2Location.io integration it can send your IPs to the API and write the results back — across every row, in one shot. No config template, no automation builder, no hand-mapping.

Example 1: Bulk-enrich a column of sign-up IPs with geolocation data

For each IP address in column A, use IP2Location.io to fetch the country, region, city, ISP, and whether it is a proxy or VPN, then write results to columns B through F.

SheetXAI sends the IPs in batches, parses the response, and writes country, region, city, ISP, and the proxy flag into the corresponding columns — one row per IP, no skipped rows, no manual field matching.

Example 2: Build a country breakdown pivot after enrichment

Create a pivot summary on a new sheet called 'Country Breakdown' counting how many IPs per country sorted from most to least, and flag any country with more than 20 IPs in column C.

The pattern: instead of enriching first and analyzing separately, you ask for both in one prompt. SheetXAI handles the aggregation and the conditional flag inline.

Try It

Get the 7-day free trial of SheetXAI and open any Google Sheet with a column of IP addresses, then ask it to enrich them with IP2Location.io geolocation data. The IP2Location.io integration is included in every SheetXAI plan.