When dealing with raw address data from various sources, inconsistencies like missing commas, weird abbreviations, and hidden characters can cause routing and delivery failures. The address normalization process automatically cleans up street names, extracts unit numbers, and formats everything into a standardized structure.

This ensures your addresses are perfectly formatted for geocoding, mapping, and accurate routing.

How Address Normalization Works

The system runs raw address data through a multi-step cleaning engine before updating your records.

flowchart TD
    A["Raw Input Data"] --> B["1. Scrub & Trim"]
    B --> C["2. Extract Units"]
    C --> D["3. Expand Abbreviations"]
    D --> E["4. Smart Title Casing"]
    E --> F["5. Final Assembly"]
    F --> G["Geocoding (Lat/Long)"]
    F --> H["Update System Records"]

1. 1

   Scrub and Trim

   The system removes invisible control characters, zero-width spaces, and extra whitespace. It also detects and ignores placeholder text like "missing sample data" or "n/a".

2. 2

   Extract House Numbers and Units

   Unit information is often tangled with the street name (e.g., 123A Main St or 123 Main St Apt 4). The system intelligently separates the core house number from unit identifiers (like #, UNIT, APT, STE, SUITE, LOT).

3. 3

   Expand Abbreviations

   Common street suffixes are expanded into their full words to ensure consistency across your database. For example, BLVD becomes Boulevard, LNDG becomes Landing, and PKWY becomes Parkway.

4. 4

   Apply Smart Title Casing

   Addresses are converted to Title Case, but with smart exceptions. Directionals and state codes (NW, NC, USA) remain capitalized. Names starting with "Mc" are handled correctly (e.g., McDermott), and hyphenated or apostrophized words retain their proper casing.

5. 5

   Assemble and Geocode

   The cleaned components are reassembled into distinct, standardized fields. The system then pings the Google Maps API to fetch the exact Latitude and Longitude for accurate routing.

Key Normalization Rules

The "St" vs "Street" Rule

The abbreviation "ST" is notoriously tricky because it can mean "Saint" or "Street" depending on where it appears. The normalization engine uses contextual rules to get this right every time:

• If "ST" is at the end of the address: It is expanded to Street.

• If "ST" is earlier in the address: It is formatted as St (e.g., St Marys).

• If "Saint" is explicitly written: It is shortened to St for consistency.

Aggressive Unit Cleaning

Unit numbers are extracted and standardized into a clean Unit X format.

If a user enters messy unit data like Apt-B, Suite #100, or just -, the system strips out the punctuation and redundant words, outputting a clean Unit B or Unit 100. Known "empty" values like none, null, or no data are completely removed so they don't clutter the final address.

Expected Output Fields

Once an address passes through the normalization engine, it is broken down into several distinct fields. These fields are then automatically synced to your database (such as Monday.com) alongside the fetched geographic coordinates.