How to Calculate the Distance Between Addresses in Excel

Updated July 7, 2026 · Geloky team

"How far is each customer from our depot?" is a spreadsheet question, and Excel can answer it — partly. Here's what Excel does well (straight-line distance between coordinates), what it can't do alone (addresses, driving distance), and how to fill the gaps.

Step 1 — Addresses must become coordinates first

No distance formula accepts "221B Baker Street". If your columns contain addresses, geocode them first — see converting addresses to lat/long in Excel. After that, each row has lat and lon and the math below applies.

Step 2 — Straight-line ("as the crow flies") distance in one cell

With point 1 in A2:B2 and point 2 in C2:D2 (lat, lon):

=6371*ACOS( COS(RADIANS(A2))*COS(RADIANS(C2))*COS(RADIANS(D2)-RADIANS(B2))
           + SIN(RADIANS(A2))*SIN(RADIANS(C2)) )

• 6371 = Earth's radius in km → result in kilometers. Use 3959 for miles.
• This is the spherical law of cosines — accurate to a fraction of a percent for any distance that matters in logistics. The haversine variant is equivalent in practice.
• It's pure math: instant, free, works for a million rows.

Step 3 — When you need driving distance

Straight-line says the two banks of a river are 300 m apart; the bridge says 4 km. Roads, ferries, one-way systems — only a routing engine knows them. From a spreadsheet you have two options:

• Routing API per row — accurate, but you're writing request loops, handling rate limits, and paying per element.
• Batch upload — the Geloky distance calculator takes a spreadsheet of origin/destination pairs and returns driving distance and travel time for every row (with options like avoiding ferries), or straight-line if that's all you need. Preview is free.

Rule of thumb

• Rough radius filters ("within 50 km?") — the Excel formula is enough, and a ×1.2–1.3 road factor approximates driving distance for planning.
• Cost, ETA, or route decisions — use real driving distance; the road factor breaks down exactly where it's expensive (mountains, rivers, city cores).