The Scenario
A field service planner sent you a spreadsheet: five technician home addresses in one tab, twenty customer job sites in another. The quarterly scheduling review is tomorrow morning, and the operations lead wants to know which technician is closest to each site — not as the crow flies, but in actual driving time.
The bad version:
- Open Google Maps, enter technician 1's address, add job site 1 as destination, read the driving time, type it into a matrix cell. That's 100 combinations (5 × 20).
- After the first fifteen lookups you start clicking faster and entering the wrong destination. Cell (3, 12) now has the driving time from technician 2 to site 7 because you lost track.
- The matrix takes four hours to fill. By the time it's done, three of the technician addresses have been updated because the planner sent a corrected file.
You're supposed to be analyzing the schedule, not operating Google Maps as a data entry interface.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet. It reads both tabs, builds the API call to Radar's route matrix endpoint, and writes the full 5x20 grid of driving times into the sheet. You go from two tabs of coordinates to a finished matrix in one prompt.
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
What You Get
- Sheet1 populated with a 5x20 grid of driving durations in minutes
- Row headers corresponding to the five technician identifiers from Sheet2
- Column headers corresponding to the twenty job site identifiers from Sheet3
- The minimum value in each column tells you immediately which technician has the shortest drive to that site
What If the Data Is Not Quite Ready
The coordinates are in separate lat and lng columns rather than combined
Sheet2 has technician lat in column A and lng in column B, rows 2-6. Sheet3 has job site lat in column A and lng in column B, rows 2-21. Build the Radar route matrix and write driving time in minutes into Sheet1 as a 5x20 grid starting at B2, with technician IDs from Sheet2 column C as row labels and site names from Sheet3 column C as column labels
Some sites are flagged as low priority and can be excluded from the matrix
Filter Sheet3 to only include rows where column D is "High" or "Medium" priority, then build the Radar driving-time matrix against the 5 technician origins in Sheet2 and write the result into Sheet1
The matrix needs to show both time and distance
Using origins in Sheet2 (lat A, lng B, rows 2-6) and destinations in Sheet3 (lat A, lng B, rows 2-21), call Radar's route matrix API and write two grids side by side in Sheet1: driving time in minutes starting at B2 and driving distance in kilometers starting at B10
Build the matrix, flag nearest technician per site, and summarize assignments in one pass
Build the Radar driving-time matrix using Sheet2 technicians (lat A, lng B, rows 2-6) and Sheet3 sites (lat A, lng B, rows 2-21), write the grid into Sheet1, then add a column to Sheet3 showing the name of the nearest technician and their driving time for each site
The last prompt takes you from raw coordinates to a draft assignment schedule without a separate analysis step.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with origin and destination coordinates — ask it to build a Radar driving-time matrix and write the results as a grid. For a related task, see bulk driving distance calculations, or return to the Radar integration overview.