The Scenario
Your latest campaign just wrapped and 500 new sign-up IPs landed in column A of your Excel workbook. The growth team wants to know which countries are driving registrations, whether any clusters look like bot traffic, and which ISPs are showing up most. This isn't the first time you've been handed a raw IP column and asked to turn it into something useful — last month it was 300 IPs from a webinar sign-up form.
The bad version:
- Open the IP2Location.io dashboard, paste each IP one at a time, read the country and city from the result, and manually type it into column B and C
- Repeat 499 more times, watching for the rows where the IP field is blank or malformed so you don't break your column alignment
- Export the results to a separate worksheet, build a COUNTIF pivot by hand, and try to remember whether you're comparing this month's numbers to last month's or the month before
You've got a Monday morning standup where this is coming up. There's no version of doing 500 manual lookups tonight that leaves you with time to actually read the data before presenting it.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads your data, understands the columns, and talks to IP2Location.io on your behalf — no API key wrangling, no script, no template to configure.
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.
What You Get
- Column B: country name (e.g., "United States", "Germany", "Brazil")
- Column C: region or state (e.g., "California", "Bavaria")
- Column D: city (e.g., "San Francisco", "Munich")
- Column E: ISP or organization name
- Column F: proxy/VPN flag — "true" or "false" per row
- Blank IP rows are skipped and noted in the chat so you know exactly what was missed
What If the Data Is Not Quite Ready
Some IPs in column A have trailing spaces or mixed formatting
For each IP address in column A, trim whitespace and normalize any IPv6 addresses to lowercase before sending to IP2Location.io, then write country, region, city, ISP, and proxy flag to columns B through F.
The ISP values need to be grouped — too many unique strings to read at a glance
After enriching column A IPs with IP2Location.io data in columns B through F, add a column G that normalizes ISP names: replace any ISP containing 'Amazon' with 'AWS', 'Google' with 'Google Cloud', 'Microsoft' with 'Azure', and everything else with 'Other'.
The IP list spans two worksheets — 'July Signups' and 'August Signups'
Combine the IP addresses from column A on the 'July Signups' worksheet and column A on the 'August Signups' worksheet, send all unique IPs to IP2Location.io, and write the enriched results to a new worksheet called 'Combined Geo Data' with the source worksheet in column A and IP in column B.
Full enrichment plus fraud flag plus country pivot in one shot
For each IP in column A, use IP2Location.io to get country, city, ISP, and proxy status and write to columns B through E. In column F, write 'REVIEW' if proxy is true or the country is not in the list ['US','CA','GB','AU','DE'], and 'OK' otherwise. Then create a new worksheet called 'Country Summary' with a count of IPs per country sorted descending.
The whole point is that you can ask for the enrichment, the conditional logic, and the summary in one instruction — you don't have to sequence them manually.
Try It
If you have an Excel workbook with sign-up or event IPs waiting in column A, Get the 7-day free trial of SheetXAI and ask it to enrich them with IP2Location.io geolocation data. For a deeper look at classifying IPs by origin type, see the server log classification guide or the full hub overview.