How to Connect IPinfo to Google Sheets (4 Methods Compared)

The Problem With Getting Sheet Data In and Out of IPinfo

You have a Google Sheet full of raw IP addresses — server access logs, sign-up records, visitor exports, device inventories. You need each one enriched with geolocation, organization, or privacy data before you can do anything useful with it. And the IPinfo API can give you all of that in bulk.

IPinfo is good at turning a plain IP address into actionable context: country, city, ASN, carrier, company name, abuse contacts, timezone. But the gap between "I have a column of IPs" and "I have all that context next to each IP" is where the friction lives. The default path is to write a script, call the API manually, wrangle the JSON, and paste the results back — or hand the task to someone who can.

Below are the four common ways teams handle this. Only the last one gets you there without building something first.

Method 1: Manual Copy-Paste

The most common starting point. You export a set of IPs from your access logs, your analytics platform, or your CRM. You paste them into IPinfo's web lookup tool one at a time. You copy each result back into your sheet by hand — country here, ASN there, city in another column.

For a handful of IPs this is survivable. For fifty it's tedious. For five hundred it's an afternoon you won't get back. And because IPinfo's web UI returns one result at a time, every single row is a separate round-trip: open tab, paste IP, read result, switch back, paste the field, repeat. By the hundredth row your eyes are glazing over and you're making transcription errors you won't catch until someone runs a query on bad data weeks later.

Method 2: Zapier or Make

Both platforms have IPinfo connector options. You can set up a trigger — a new row in a sheet, a schedule, a webhook — and wire it to an IPinfo lookup, then write the enriched fields back to the sheet.

Before you go further: do you know what a webhook trigger is? A REST connector? Field mapping? Rate-limit handling? If any of those are unfamiliar, this path is going to cost you more setup time than the enrichment saves you. You're better off skipping to Method 4.

If you're still here, the automation itself is achievable. You pick the trigger, map the IP field to the IPinfo connector input, map each output field — country, city, ASN, org — back to specific columns, and run it.

But a trigger-per-row automation is not the same as a batch lookup.

Sending 800 IPs through a Zap means 800 separate API calls, 800 trigger fires, and a task history that becomes impossible to audit when row 412 returns a timeout and the rest skip silently.

You probably just need the enrichment data for your security review or your traffic analysis. You probably have no idea how to wire up rate-limit retries inside Make — and you shouldn't have to. So you push this to whoever on your team builds automations, and now you're waiting on a Slack reply while your report sits half-finished.

Once you add filtering, conditional flags, or a summary table to the automation, you've left Zapier and Make's native capabilities behind entirely.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable spreadsheet-to-API enrichment was a category of add-ons that let you configure column mappings and run them on demand. You pointed the add-on at your IP column, tagged the output fields, saved the config, and clicked run.

That was a real improvement over copy-paste. Output was consistent, the config was reusable, and you didn't have to redo the field mapping every time.

But you were still responsible for every design decision: which columns receive which fields, which rows to include, what to do when the API returns null, whether to add a summary table or a flag column. The tool moved the data through, but all the thinking was still yours to do. And when your sheet structure changed — a column rename, a new tab, a filter you added — the config broke and someone had to go back in.

This is the previous generation. It worked. It just asked a lot of the person running it.

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 what you are looking at, and through its built-in IPinfo integration it can call the API, enrich your IPs, and write the results back — including flags, summary tables, and conditional logic — all from a single prompt.

Example 1: Batch geolocation across 800 rows

Look up all IP addresses in column A using IPinfo batch lookup and write country, region, city, and ASN to columns B through E. Flag any row where the country is outside the US, UK, or Canada as "Review" in column F.

SheetXAI calls the IPinfo batch endpoint in chunks, writes the four enrichment fields to their columns, and adds the conditional flag in one pass — no API key wiring, no JSON parsing, no formula work.

Example 2: Geographic summary table from a traffic export

Geocode all IPs in column A with IPinfo, group by country, and write the top 20 countries sorted by IP count descending to a new tab called "Traffic Summary."

The pattern: instead of enriching the data first and then building the summary separately, you ask for both in one prompt. SheetXAI handles the aggregation 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 IPinfo geolocation, carrier data, or privacy flags. The IPinfo integration is included in every SheetXAI plan.