When was the last time you found all addresses in your list followed the same format and were error-free? Never, right? Despite all the steps your company may take to minimize data errors, address data quality issues – such as misspellings, missing fields, or leading spaces – due to manual data entry – are inevitable.
Spreadsheet data errors especially of small datasets can range between 18% and 40%. Â
To combat this problem, address standardization can be a great solution. It’s worth first exploring some of the definitions regarding addresses, though:
- Address Autocompletion: Address autocompletion is a user interface feature that helps users enter addresses more quickly and accurately by suggesting possible matches as they type. This can reduce the likelihood of errors and ensure that the entered address data is accurate and complete.
- Address Cleansing: Address cleansing is the process of correcting, updating, and removing errors in address data. This may include fixing typos, removing duplicate entries, filling in missing information, and updating outdated addresses. The goal is to ensure that addresses are accurate and up-to-date for purposes such as mailing, geocoding, and customer data management.
- Address Deduplication: Deduplication refers to the process of identifying and removing duplicate records in a dataset, which can include duplicate addresses. This helps to maintain data quality and reduce inconsistencies. It requires that the data is normalized or standardized in order to improve deduplication rates.
- Address Matching: Address matching is the process of comparing and identifying equivalent addresses across different datasets or systems. This can be useful for tasks like deduplication, data integration, and data validation. It requires that each source is normalized or standardized in order to have higher match rates.
- Address Normalization: Address normalization refers to the process of transforming addresses into a consistent format. This might involve converting abbreviations to their full forms, changing casing to a standard style, and reordering address components according to a specified format. Normalization helps to ensure that addresses are represented consistently across different systems and datasets.
- Address Parsing: Address parsing is the process of breaking down an address into its individual components, such as street number, street name, city, state, and postal code. Parsing can be an essential step in cleansing, normalization, standardization, and verification processes.
- Address Standardization: Address standardization is the process of conforming addresses to a set of established rules or a specific addressing system, such as the United States Postal Service (USPS) guidelines. This can involve modifying address components to meet the standards, adding missing data, or correcting invalid information. Standardized addresses are easier to compare, sort, and analyze.
- Address Verification: Address verification is the process of confirming that an address is valid and deliverable. This often involves checking the address against an authoritative source, such as a postal service database. Verification can help to reduce the likelihood of undeliverable mail or packages, improve geocoding accuracy, and maintain the quality of customer data.
This post highlights how companies can benefit from standardizing data, and what methods and tips they should consider to bring about intended results.
The History of Postal (Zip) Codes
Postal codes were first introduced in the Ukrainian Soviet Socialist Republic in December 1932, but abandoned in 1939. The next country to introduce postal codes was Germany in 1941, followed by Singapore in 1950, Argentina in 1958, the United States in 1963, and Switzerland in 1964.
Before the 1960s, mail was delivered based on the city and state it was addressed to, plus a two-digit postal code that indicated a broad region. In 1962, the United States Postal Service expanded this system to what we know as modern zip codes to assist in mail sorting and make it easier and faster to get an ever-increasing amount of mail to where it needed to go. In fact, Zoning Improvement Plan (ZIP) was chosen specifically to indicate that letters and packages arrive faster––zippier, if you will––when zip codes are used.
Zip codes do more than just divide the mail. These five digits at the end of an address are the most informative part of the location data. These numbers indicate the national region, sub-region, post office, and delivery station tied to each address.
Because they have become accepted as a standard, zip codes can be used to quickly identify other useful data. Census records and demographic maps are tied to zip codes. It’s easy to see how all of this data can be used to find patterns in consumer behavior and help businesses make better decisions.
Of course, the US has grown a lot since 1962, and eventually, even the five-digit zip code was not efficient enough to keep up with the demand. What is known as the plus-four code was added in 1983. The last four numbers add more precision to the address, often identifying a location down to within a few blocks. This code is not something that the average consumer adds when they are addressing a piece of mail or inputting their home address on a collection form, which is unfortunate, because plus-four codes provide additional information and help to standardize the data.
There are more than 40,000 zip codes in the United States (not counting the plus-four number), so the possibilities for research and interpretation are almost endless. However, the chances that data will be mixed up or corrupted in some way are also high, since a single digit completely changes what the numbers mean. That is why it is vital for businesses to validate their zip code data and ensure that the information they spend so much effort to collect is actually helping in the ways they think it is.
The United States Postal Service provides a free address validation system, but, as with most free things, it is not without limitations. The system has very limited customer support, isn’t always working correctly, and can only process a single address at a time. Luckily, there are many third-party software solutions that provide helpful alternatives to the USPS verification system. When you are basing the future of your business on the address data you have, it is worth investing resources to ensure that the data is clean and reliable.
What is Address Standardization?
Address standardization is the process of identifying and normalizing the format of address records in line with recognized postal service standards as laid out in an authoritative database such as that of the United States Postal Service (USPS).
Most addresses do not follow the USPS standard, which defines a standardized address as, one that is fully spelled out, abbreviated using the Postal Service standard abbreviations, or as shown in the current Postal Service ZIP+4 file.
Standardizing addresses becomes a pressing need for companies that have address entries with inconsistent or varying formats due to missing address details (e.g., ZIP+4 and ZIP+6 codes) or punctuation, casing, spacing, and spelling errors. An example of this is given below:
As seen from the table, all address details have one or multiple errors and none meet the required USPS guidelines.
Address standardization should not be confused with address matching and address validation. While there are similar, address validation is about verifying if an address record conforms to an existing address record in the USPS database. Address matching, on other hand, is about matching two similar address data to ascertain if it refers to the same entity or not.
What Is A USPS Standardized Address?
The standard United States address format, as recommended by the USPS, typically includes the following components:
- Recipient Line:
- This line contains the recipient’s name or the name of a business/organization. It is essential to ensure proper delivery.
- Delivery Address Line:
- Street Number: The numerical identifier assigned to a building or property along a street.
- Predirectional (optional): A directional abbreviation that comes before the street name (e.g., N, S, E, W, NE, NW, SE, SW).
- Street Name: The name of the street or road.
- Street Suffix: The type of street or road (e.g., St, Ave, Rd, Blvd).
- Postdirectional (optional): A directional abbreviation that comes after the street name (e.g., N, S, E, W, NE, NW, SE, SW).
- Secondary Address Unit (optional): Additional information to specify a location within a larger building or complex (e.g., Apt, Unit, Ste, Fl).
- Secondary Unit Number (optional): The number or identifier associated with the secondary address unit.
- City, State, and ZIP Code Line:
- City: The name of the city or town.
- State: The two-letter abbreviation for the state or territory.
- ZIP Code: The 5-digit ZIP (Zone Improvement Plan) code, which may be followed by a hyphen and the 4-digit extension, known as the ZIP+4 code.
When formatting a standard U.S. address, it is important to follow USPS guidelines for abbreviations, capitalization, and punctuation. Here’s an example of a properly formatted address:
John Doe
1234 N Main St Apt 56
Springfield, IL 62704
Keep in mind that the format may vary slightly depending on the specific address, but the general structure and components will remain consistent.
Benefits of Standardizing Addresses
Apart from the obvious reasons for cleansing data anomalies, standardizing addresses can provide an array of benefits for companies. These include:
- Save time verifying addresses: without standardizing addresses, there is no way to suspect if the address list used for the direct mail campaign is accurate or not unless the mails are returned or have got no responses. By normalizing varying addresses, substantial man-hours can be saved by staff sifting through hundreds of mailing addresses for accuracy.
- Reduce mailing costs: Direct mail campaigns can lead to wrong or incorrect addresses that can create billing and shipping issues in direct mail campaigns. Standardizing addresses to improve data consistency can reduce returned or undelivered mails, resulting in higher direct mail response rates.
- Eliminate duplicate addresses: varying formats and addresses with errors can result in sending twice as many emails to contacts that can lower customer satisfaction and brand image. Cleaning your address lists can help your firm save wasted delivery costs.
How to Standardize Addresses?
Any address normalization activity should meet USPS guidelines for it to be worthwhile. Using the data highlighted in Table 1, here is how address data will appear upon normalization.

Standardizing addresses involves a 4-step process. This includes:
- Import addresses: gather all addresses from multiple data sources – such as Excel spreadsheets, SQL databases, etc. – into one sheet.
- Profile data to inspect errors: carry out data profiling using to understand the scope and type of errors present in your address list. Doing this can give you a rough idea of the potential problem areas that require fixing before carrying out any kind of standardization. Â
- Clean errors to meet USPS guidelines: Once all errors are detected, you can then cleanse the addresses and standardize it in accordance with USPS guidelines.
- Identify and remove duplicate addresses: to identify any duplicate addresses, you can search for double counts in your spreadsheet or database or use exact or fuzzy matching to dedupe entries.
Methods of Standardizing Addresses
There are two distinct approaches to normalizing addresses in your list. These include:
Manual Scripts and Tools
Users can manually find run scripts and add-ins to normalize addresses from libraries via various
- Programming languages: Python, JavaScript, or R can enable you to run fuzzy address matching to identify inexact address matches and apply custom standardization rules to suit your own address data.
- Coding repositories: GitHub provides code templates and USPS API integration that you can use to verify and normalize addresses. Â
- Application Programming Interfaces: Third-party services that can be integrated via API to parse, standardize, and validate mailing addresses.
- Excel-based tools: add-ins and solutions such as YAddress, AddressDoctor Excel Plugin, or excel VBA Master can help you parse and standardize your addresses within your datasets.
A few benefits of going down this route are that it is inexpensive and can be quick to normalize data for small datasets. However, using such scripts can fall apart beyond a few thousand records and thus are not suited for very large datasets or those spread across disparate sources.
Address Verification Software
An off-the-shelf address verification and normalization software can also be used to normalize data. Usually, such tools come with specific address validation components – such as an integrated USPS database – and have out-of-the-box data profiling and cleansing components along with fuzzy matching algorithms to standardize addresses at scale.
It is also important that the software has CASS certification from USPS and meets the required accuracy threshold in terms of:
- 5-digit coding – applying the missing or incorrect 5-digit ZIP code.
- ZIP+4 coding – applying the missing or incorrect 4-digit code.
- Residential Delivery Indicator (RDI) – determining whether or not an address is residential or commercial.
- Delivery Point Validation (DPV) – determining whether or not an address is deliverable down to the suite or apartment number.
- Enhanced Line of Travel (eLOT) – a sequence number that indicates the first occurrence of delivery made to the add-on range within the carrier route, and the ascending/descending code indicates the approximate delivery order within the sequence number.Â
- Locatable Address Conversion System Link (LACSLink) – an automated method of obtaining new addresses for local municipalities that have implemented a 911 emergency system.
- SuiteLink® enables customers to provide improved business addressing information by adding known secondary (suite) information to business addresses, which will allow USPS delivery sequencing where it would not otherwise be possible.
- And more…
The main advantages are the ease at which it can verify and standardize address data stored in disparate systems including CRMs, RDBMs and Hadoop-based repositories and geocode data to yield longitude and latitude values.
As for limitations, such tools can cost far more than manual address normalization methods.
Which Method Is Better?
Choosing the right method for enhancing your address lists depends entirely on the volume of your address records, technology stack, and project timeline.
If your address list is less than say five thousand records, standardizing it through Python or JavaScript can be a better option. However, if achieving a single source of truth for addresses using data spread in multiple sources within a timely manner is a pressing need then a CASS-certified address standardization software can be a better option.
Address Standardization Services
There are several address standardization platforms available online, which can help you clean, normalize, standardize, and verify addresses according to specific rules and standards, such as those set by the USPS or other postal authorities. Some of these platforms include:
- Smarty – Offers address validation, standardization, geocoding, and autocomplete services for the United States and international addresses.
- Melissa – Provides a variety of data quality tools, including address verification, standardization, and geocoding services for global addresses.
- Loqate – Offers address verification, geocoding, and address autocompletion services for addresses worldwide.
- EasyPost – Provides address verification and standardization services, primarily focused on shipping and logistics for U.S. and international addresses.
- Experian Data Quality – Offers address validation, standardization, and enrichment services for global addresses, as part of a broader suite of data quality tools.
- Informatica – Offers address validation, standardization, and geocoding services for addresses worldwide as part of Informatica’s suite of data quality tools.
These platforms may offer APIs, web interfaces, or batch-processing tools to help you standardize and validate addresses in your applications or data sets. Be sure to review each platform’s features, pricing, and coverage to determine the best solution for your specific needs.
Note: This article has been updated with information on the history of zip codes from the team at Smarty.