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

The Problem With Getting Sheet Data In and Out of Radar

You have a Google Sheet full of data — addresses, GPS coordinates, store locations, delivery stops. You need to push it into Radar for geocoding, geofencing, or routing, or pull the results back out so you can do something useful with them.

Radar is good at turning location data into structured, actionable output. But the gap between your sheet and Radar's API is where most of the time actually goes. The default flow is: export the sheet to CSV, write or find a script that calls the Radar API row by row, parse the JSON responses, paste the results back into new columns, and then reconcile any rows that came back empty or errored.

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

Method 1: Manual Copy-Paste

The default. You copy addresses or coordinates from the sheet, paste them one at a time into Radar's dashboard search or geocoder, read the result, and type the output back into the sheet by hand.

For a handful of addresses this is annoying but survivable. For 50 rows it starts to feel like the kind of work that makes you question your career. For 300 it simply doesn't happen — you either find another method or you ship an incomplete dataset and hope no one notices the gaps.

Method 2: Zapier or Make

Both platforms have Radar connector options. You can set up a trigger on a new row in the sheet, call the Radar API with the cell values, and write the response back into a new column.

Before you go down this path — quick check: do you know what a webhook trigger is? What field mapping looks like when the API returns a nested JSON object? How to handle null values so your automation doesn't silently drop rows? If those concepts feel unfamiliar, you're better off skipping to Method 3 or 4. This path has a learning curve that doesn't show up in the marketing.

If you're still here, the setup is real: pick the right trigger, authenticate to Radar's API, map every response field back to the right column, test with a sample row, debug the cases where the geocoder returns multiple candidates and you have to pick one. The flow works. The problem is maintenance.

A row-by-row automation is not the same as a bulk operation.

Sending 500 addresses through a Zap means 500 separate API calls. If address 312 returns a 422, the rest of the run keeps going and you now have a gap at row 312 that you may not notice until someone looks at the map.

You probably just need lat/lng for every row and have no idea where to start with a Make module. So you hand it to whoever on your team knows automations, and now you're waiting on a Slack thread while the deadline for that route optimization run gets closer.

And when your sheet schema changes — a column rename, a new tab — the automation breaks until someone goes back in and fixes the field mapping.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable sheet-to-Radar workflows was a category of add-ons that let you configure column mappings to call location APIs. You picked your address column, you tagged the output columns, you saved the config, you ran it.

That was a real step up from one-at-a-time lookups. Configs were reusable, output was consistent, you could hand it to a teammate.

But you were still responsible for the template: which column was the address, which columns got the lat and lng, what to write when the geocoder returned no result. The tool handled the API call, but the schema was still entirely on you. And if the address format in column A changed from city-state to full street addresses, your template broke until someone updated it.

This is the previous generation. Useful, but it put the operator in the driver's seat for every decision the tool couldn't make itself.

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 Radar integration it can geocode, reverse-geocode, build route matrices, search for nearby places, manage geofences, and pull location events — all from a single prompt. No template configuration, no Zap wiring, no parsing JSON by hand. You just ask.

Example 1: Geocode a column of delivery addresses

For each address in column A, call Radar's forward geocode API and write the returned latitude, longitude, and formatted address into columns B, C, and D — mark any rows with no result as Failed in column E

Radar processes every address, the coordinates land in the columns you named, and any rows that didn't resolve get flagged so you know exactly what needs a second look.

Example 2: Build a 5x20 driving-time matrix for dispatch planning

Using the 5 technician coordinates in Sheet2 as origins and the 20 customer coordinates in Sheet3 as destinations, call Radar's route matrix API and write the driving duration in minutes for each pair into Sheet1 as a 5x20 grid

The pattern: instead of scripting two nested loops and parsing a matrix response, you describe the outcome and SheetXAI handles the conditional thinking inline.

Try It

Get the 7-day free trial of SheetXAI and open any Google Sheet with addresses or coordinates, then ask it to geocode, route, or geofence using Radar. The Radar integration is included in every SheetXAI plan.