From street to suite: A complete guide to address parsing

Data is arguably the most critical asset for any business. When you’re playing with the big bucks and a single decision can easily make you win or waste thousands of dollars, you can’t afford to rely on gut feelings. What you need is clear, accurate information that will help you know your market and customers better.

Problems begin when the data you store is incomplete, unstructured, or incorrect. According to a Bain&Company survey, 56% of companies don’t have the right systems to capture the data they need or aren’t collecting useful data. Of course, not all incomplete or inaccurate customer data spells disaster. But incorrect key details like home addresses can have serious repercussions, from failed deliveries to compliance issues and even lost revenue.

By breaking down and standardizing address data, address parsing makes customer information more consistent and usable, reducing errors and supporting smarter business decisions.

What is address parsing?

Address parsing is a method of breaking down a postal address into individual components so that each can be analyzed, standardized, and validated. Typically, businesses use an address parsing API (Application Programming Interface) to connect to automated tools that do all the heavy-lifting.

These tools typically leverage technologies such as Natural Language Processing (NLP), Machine Learning (ML), and AI, combined with predefined rules and datasets, to improve parsing speed and accuracy.

Each standard address typically includes a:

● Recipient name

● Apartment number

● Floor number

● Apartment name

● Street number

● Street name

● Postcode or ZIP code

● Sub-location or county (for larger cities)

● City

● Country

Who needs address parsing? Key use cases and benefits

Parsing is the first step to standardizing addresses and keeping them accurate. Without it, key details like a floor number, street suffix, or part of a postcode can be missed. These may seem minor, but a single incorrect or missing character can send a parcel to the wrong location or register a customer in the wrong state, which can distort customer records and marketing insights (among other serious repercussions).

While most businesses store customer addresses, for some industries, it’s absolutely critical to have accurate data. These include:

1. Postal and courier services

What's a postal service with incorrect postal addresses? Mail sorting, carrier routing, and international shipping depend on address information that is structured, standardized, and machine-readable. After addresses are parsed and standardized, automated sorting machines used by organisations like Royal Mail, USPS, and international couriers can scan and process millions of items at speed. Without parsing at the start, machines could misinterpret messy data, which would require staff to solve issues manually.

2. Banking and financial services

If one industry needs to “know its customer,” it’s financial services. Address accuracy is critical to prevent fraud like money laundering, identity theft, and tax evasion. Beyond moral and ethical reasons, financial institutions in the US are legally required to collect and verify customer address information under federal regulations such as the USA PATRIOT Act and FinCEN’s Customer Identification Program (CIP) rules, as well as comply with standards like ISO 20022.

On the operational side, address parsing can streamline onboarding, speed up customer verification, and create a smoother experience overall. Plus, banks can assess risk more effectively, calculate creditworthiness with greater precision, and deliver essential communications to the right destination.

3. E-commerce and retail

For retail companies, a customer’s address can be as valuable as the product they sell. That may sound like an exaggeration, but consider the impact of a lost parcel. You’d not only lose your item (and its retail value), but may also have to refund the customer, cover the cost of a replacement, and waste operational resources.

The financial setback is only part of the problem. A failed delivery often damages customer loyalty; once trust is lost, it will be challenging to win it back. Retail businesses rely on repeat purchases and word-of-mouth recommendations, so clean, accurate address data is critical to protecting long-term growth.

4. Utilities and telecoms

Utility companies for electricity, gas, and water, as well as telecom providers for internet and phone, rely on addresses to get services to the correct locations. A wrong apartment number can delay installations, and mistakes in address data can cause billing or compliance problems.

Parsing helps providers match customer accounts to the correct geographic service zones, so deliveries, repairs, and maintenance can be delivered smoothly. Regarding emergency responses like gas leaks or power outages, incorrect address data isn’t just costly; it can put lives at risk.

5. Many others

Various other industries and use cases also require address parsing, such as public services (like voter registration, tax collection, government benefits, and census records), property, healthcare and insurance, and logistics and transportation.

How to parse an address: Step-by-step guide

1. The parsing process

Automated tools use built-in engines that apply rules and patterns to split an address string into components. Take this fictional address, for example: 500 Main Street, Floor 3, New York, NY 10001 USA. This is how a tool would parse it:

 

● Street number: 500

● Street name: Main Street

● Floor number: 3

● City: New York

● State: NY

● Zip code: 10001

● Country: USA

Some tools combine various technologies and capabilities to improve their parsing accuracy. For example, Loqate’s AI-based parser is powered by Machine Learing algorithms trained on vast datasets. It also leverages lexicons, context tables, and pattern recognition to tackle various scenarios. These enhancements allow it to process diverse address formats and adapt to unusual or inconsistent entries.

2. Address standardization

Parsing is a means to an end, and the ultimate goal is to have readable, recognizable, and accurate address data. Once the data is parsed, the next step is to standardize it and convert it to a consistent format. This step includes spelling out abbreviations, separating components, or correcting spelling errors.

3. Data validation

Now that your data is standardized and readable, automated tools will match it with official address data to ensure it is in a recognizable, workable format. There is no official dataset to follow, but the USPS dataset is the most commonly used dataset in the US.

Of course, if you operate across borders and store international addresses, you’ll need other records. That’s why you should choose a provider that covers all the countries you operate in.

For instance, Loqate covers more than 250 countries and territories worldwide, pulling from hundreds of local postal authorities, geospatial data providers, and proprietary datasets. This breadth of coverage gives businesses confidence that their addresses can be validated no matter where their customers are.

Why do you need address parsing?

As we have seen, address parsing is just the first step in transforming raw, potentially incomplete, or incorrect data into deliverable formats. But what if we skip the first step and move straight to matching raw data against trusted records?

There are critical risks with this. Without parsing and standardization, even minor differences like abbreviations, typos, or missing fields can prevent a system from recognizing that two records refer to the same address. For example, “221B Baker St” in your records and “221B Baker Street” in USPS records represent the same location, but without parsing to break down and standardize the components, the system may treat them as different. That means validation fails, and you’re back to square one.

>Address parsing: limitations to watch out for

Address parsing sounds simple, and it is. The challenges only begin when there are millions of customer address records to parse.

Large multinational banks, major telecom providers, and global retail chains (among others) each have at least tens of millions of customers, each with one or more associated addresses. Suddenly, what seemed like a simple process becomes a mammoth job.

It’s clear that you need an automated tool to parse your addresses. But which one should you choose? An address parser is only as good as the rules it follows, so it’s essential to understand how your provider creates these rules, whether they cover international postcodes accurately, and how well they are maintained and updated.

They should also rely on reliable and comprehensive databases that are continuously updated. Every country has its own formatting rules, abbreviations, and conventions, so if your provider’s databases are narrow or poorly maintained, you may risk having invalid addresses or false negatives slipping through.

What sets Loqate’s address parsing solution apart

Loqate’s AI Parser (part of its Address Verify solution) combines advanced technologies like ML and pattern recognition with deep local knowledge of address structures worldwide. It overcomes the limits of traditional rule-based systems by training on extensive global datasets, lexicons, and contextual tables.

It also leverages Loqate’s Global Reference Data, a proprietary master database that contains data for over 250 countries and territories, and handles local variations, transliterations, and aliases. This repository is continuously updated to reflect administrative changes or new streets.

Thanks to these capabilities, Loqate’s AI parser boosts address match and validation success by an average of 7.25% across countries and territories. In developing markets, improvements can reach up to 19%. Discover why leading global companies trust us to parse their address data. Request a demo or free trial here.