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4 minutes
Saved on average per dispatch call.
5 countries
Scaled to from the initial solution.
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Insight papers
Improved efficiency and customerexperience.
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.
Countries and cultures around the world commonly structure their addresses differently than the standard approach inthe 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:
The client needed a way to automatically gain accurate addresses and geographic coordinates to reduce processing timeand increase successful shipments.
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 theissue. 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 informationand ensures mailability.
In Phase 1, the team deployed the solution across one country and saw positive results, including an average reduction offour minutes per support interaction. With that success the team progressed into
Phase 2: expanding the solution to serve five countries across themulti-national company’s footprint. The company now saves support agent timeand 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 ofthe 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.
