• Address standardization is the process of accurately registering addresses and converting data to a nation’s official specifications. A high-quality address standardization system will keep a constant and trustworthy single-best record, which is obtained by combining reference data from hundreds of data sources, in order to give complete coverage. By automating the process of transforming addresses into the required forms, this technology decreases the complexity of customer service and database management.

Common Issues found with address data include:

• Missing data, including house number, pin code, and street name.
• Duplicate information: The same client has various addresses, each of which has a unique street or house number.
• Several abbreviations are used for the same information, such as Aptmnt or APT for apartments.
• The same information is capitalized differently depending on the character case, as in the cases of MAIN Street, Main Street, and MAIN STREET.
• Addresses include a variety of structures, such as writing the street name first, followed by the number, or writing the state in some locations on the first line and in others on the second.
• Outdated information: Address data does not represent current, updated information in case someone has moved away from the previous residence.
• Address data is inaccurate since it does not provide actual, legitimate addresses in the city or state that they are referring to.
• Various addresses can be found in two or more datasets, such as the CRM or billing software.
• Addresses are presented in a format or structure that is extremely challenging to interpret or comprehend, rendering the data useless for any intended use.

What is the importance of Address Standardization?

Address standardization is important for several reasons:

Improved data quality:

Address standardization ensures that addresses are consistently formatted and structured, which improves the accuracy and completeness of data. This is important for data analysis, marketing, and customer service.

Enhanced lead segmentation:

Proper lead segmentation is one of the most crucial reasons to standardize your data. You will have a number of inaccuracies in your data if you don’t normalize address data, which will lead to problems with lead segmentation. You will use false data for creating customer personas and conducting demographic analysis.

The inability to categorize present and potential clients by region, ZIP code, city street, and other factors will cause a lot of problems in the future. Your client personas and demographics will be grounded in reality and free from errors and inaccuracies if you have standardized address data.

Cost savings:

Standardizing addresses can lead to cost savings for businesses and organizations by reducing the number of returned or undeliverable mail pieces. This can also help to minimize the cost of customer service inquiries related to undelivered or missing mail. Some industries, such as healthcare and finance, have strict regulations around the handling of customer information. If a business sends confidential or sensitive information to an incorrect address, they may be subject to fines and other penalties for non-compliance that adds to the existing costs.

Efficient mail delivery:

Standardized addresses help postal workers to more quickly and accurately deliver mail. This is particularly important for businesses that rely on timely delivery of mail, such as banks, insurance companies, and e-commerce retailers.

Compliance with regulations:

Many regulatory bodies require standardized addresses for compliance purposes. For example, financial institutions may be required to verify the accuracy of customer addresses for anti-money laundering (AML) and know-your-customer (KYC) regulations.

Fraud Prevention:

You and your clients are better protected against fraud the more precise your address records are. Fraudulent activities such as identity theft and account takeover often involve fake or inaccurate address information. By standardizing address information, financial institutions can easily identify any inconsistencies or inaccuracies in the customer’s address information, which can help prevent fraud.

The truth is that the expenses of fraud prevention are frequently not apparent until after the fact. Yet, compared to the price of fraud protection strategies and solutions, these expenses may be significantly higher. In the end, you are safeguarding your reputation and connections with all of your clients, partners, and business associates.

How to standardize addresses?

Decide on a benchmark:

Choosing which standard to confirm your address data to is the first and most crucial step in this procedure. You must utilize the USPS addressing standard if your company is based in the US. Canada Post standardizes addresses in Canada. Selecting a standard gives the route to the process of address cleaning and standardization because a standard defines the structure that your addresses must adhere to.

Profile for deviations from the norm:

Data profiling is the process of evaluating the present condition of data and revealing obscure aspects of its composition and organization. Data profiling uses the examination of the values in the address column to find prospective data cleansing opportunities. An algorithm for data profiling determines whether certain types of data are:

-Missing

-Duplicate or non-unique

-Follows an erroneous pattern or format

-Falls outside of the acceptable value domain, etc.

You can use this information to determine how closely your present address data complies with the standard.

• Parse Addresses: It’s crucial to parse addresses and determine their necessary parts before beginning the real data cleansing and standardization process. Due to the prevalence of open-text address fields. Enforcing validation requirements on the data being entered is more difficult. As it  increases the likelihood that missing and unstructured values may enter the system.

Address fields are parsed to identify the necessary elements, such as:

• House Number
• Street
• Locality
• Sub Locality
• City
• State
• Pincode
• Make addresses clear and consistent:

You can now start clearing up the mess after profiling and processing the addresses. In order to create a uniform and useful picture across all records. The emphasis is on removing incorrect and invalid information contained in addresses.

Following are a few instances of procedures used to standardize data:

• Add any missing city names, street numbers, state names, etc.
• Delete and replace any punctuation that is empty or useless.
• All letters must be capitalized in accordance with Postal addressing guidelines.
• Substitute variants with conventions, such as 4TH ST. for 4th St.
• Standardize acronyms like: Apartment designators are APT, West designators are W, North designators are N, New York states are NY, etc.
• As per the norm, add appropriate space.
• Use operations (flag, replace, delete): On the terms that repeat the most in a column to eliminate noise in large quantities. For example, remove Corp. or Ltd. to reveal the actual address.

Use Case for e-commerce:

To ensure successful transactions on an e-commerce platform, it’s crucial to verify shipping addresses. Collecting shipping or billing information is often a mandatory step in the backend application of a website to encourage customer purchases. While postal addresses are commonly studied in database courses as a fundamental example of data modeling in standard format, it’s important to consider the client-facing aspect. This is where address validation plays a valuable role.

Use Case for financial sector:

During the customer onboarding process, financial institutions need to collect accurate and standardized address information from customers. This information is necessary for KYC (Know Your Customer) and AML (Anti-Money Laundering) compliance purposes. Address standardization ensures that the address information provided by customers is accurate and consistent across all records and databases.

Overall, address standardization is an important process that helps businesses and organizations to ensure accurate, efficient, and compliant mail delivery, while also improving data quality and reducing costs.