Address validation solution improves customer support experience


Automation saves time, improves delivery rates & scales easily

For a high-tech client, invalid address data increased product shipping errors in the support process. Manually validating addresses added time to customer support calls, putting strain on support centers and frustrating the customer.

Automating the address validation process through data enrichment and machine learning models reduced support interaction times by an average of four minutes. It enabled smooth product delivery – improving efficiency and the overall customer experience. With early success, the solution scaled from one to five countries and counting in the client footprint.


4 minutes

Saved on average per dispatch call.

5 countries

Scaled to from the initial solution.


Improved efficiency and customer experience.

The need for change -
Addresses gone awry

Countries and cultures around the world commonly structure their addresses differently than the standard approach in the U.S., from listing the street name before the number to more contextual variations such as listing directives like “across from the mall, blue door.”

One global high-tech company faced numerous package delivery failures due to incorrect addresses in their database for customers across Central and South America.

The data issues could be attributed to general typos, the order in which digital forms ask for information (jumbling street names, numbers and building numbers/letters) or just a more contextual approach to address writing. Regardless of the error origins, this led to two challenges for the client:

  • A high volume of logistics rejections and product losses, which, in turn, created a poor customer experience on top of operational inefficiencies.
  • A manual support process which required the customer to contact a support agent to change and validate the address, taking several minutes and occupying agent time while frustrating the customer.

The client needed a way to automatically gain accurate addresses and geographic coordinates to reduce processing time and increase successful shipments.

Applying machine learning to existing technology for easier data validation

Building upon the client’s technology stack, Aligned Automation designed and implemented a solution to automatically correct and validate address data.The solution included several key deliverables. First, the team cleansed the address database and standardized the address format. Next, they matched addresses with geo-location data to associate precise coordinates with mailable addresses.

Because the algorithm learns from provided information, accessing accurate addresses in the database is essential to validate future address quality. In other words, they needed to teach it what good looks like and how to get there. For the support agents who use the system daily, the team created a user-friendly interface.

Through the custom web application, support agents now easily perform their address checks. If the system determines the address is mailable, they ship the product. If the system determines the address is non-mailable, the algorithm automatically begins resolving the issue. Through assessing a combination of historical dispatch data, multilingual detail translations and customer geo-location data against the “good” addresses in the database, the system updates the address information and ensures mailability.

Scaling success to expand a positive customer experience

In Phase 1, the team deployed the solution across one country and saw positive results, including an average reduction of four minutes per support interaction. With that success the team progressed into Phase 2: expanding the solution to serve five countries across the multi-national company’s footprint. The company now saves support agent time and money from shipping costs and lost product.

Customers in these regions are more likely to receive the correct shipments on time because of the corrected address data, and will spend less time engaging with the support agent in the event a ticket must be opened.

While this case provides just one piece of the customer service puzzle, it is indicative of how digital transformation enables an organization to save time, easily scale solutions, break down regional siloes and enhance cross-collaboration. Ultimately, as this client shows, the most successful organizations will do this with a primary concern: improving the customer experience.

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