Geocoding 27,854 routes without a paid API

Description and use

Built a route directory without a paid API by leveraging public city coordinates, rigorous name normalization, and a road‑factor distance estimate.

Problem

Building a directory of long‑distance moving routes cost‑effectively at scale.

Outcome

The directory was built without any paid geocoding or routing APIs, avoiding large bills while maintaining data quality through manual review of near matches.

Workflow

• 1. Gather a canonical city list from public datasets (gazetteers, census files).
• 2. Normalize city names: lowercase, strip punctuation, expand abbreviations, and match to canonical list.
• 3. Flag near matches for manual review; exact matches auto‑accept.
• 4. Join city coordinates to form routes; no per‑route lookup needed.
• 5. Calculate straight‑line distance; estimate driving distance by multiplying with a calibrated road factor.
• 6. Publish routes and cost estimates, labeling them as approximations.
• 7. Automate the entire pipeline so updates to source data trigger regeneration.

Evidence

We had tens of thousands of city pairs, and every commercial geocoding API we priced would have charged us per lookup.

Source

City coordinates are public knowledge, and several open datasets publish them: gazetteers, census place files, and open geographic databases.

Source

We built a normalization pass: lowercase everything, strip punctuation, expand common abbreviations, and match against our canonical list with a strict rule.

Source

We estimated driving distance from straight‑line distance using a road factor, calibrated against a sample of known driving routes.

Source

Free data breaks in predictable places. Small towns change names or merge. New developments appear faster than public datasets update.

Source