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Case Study

Proximus Delivers a Quick Resolution to Customer Requests with Intelligent Automation

SLAs met Corrections are made with agreed-upon timeframes
700 Errors corrected each month
Customer satisfaction Rapid resolution improves experience
"Camila handles all the work with ease and never gets tired or demotivated when waiting times in various systems take a bit longer.""
Jan Vandekerckhove RPA Developer, Development & Automation Solutions Team

Based in Belgium, Proximus is a leading telecommunications company. Never resting on its laurels, Proximus was looking for ways to increase operational efficiencies, while boosting customer satisfaction. However, the process to correct work order errors was causing the company concern. With tight, service level agreements (SLAs) in place that govern how work orders must be handled, Proximus needed an innovative solution. They found it in a team of Blue Prism digital workers.


Like most telcos, Proximus connects customers to mobile and broadband networks using a wide range of plans. In practice, this means Proximus receives tens of thousands of plan activations, deactivations and alterations every month. In dealing with such high volumes of transactions, invariably errors occur. Not only is this costly for the business to rectify, but it can impact customer satisfaction. With strict SLAs governing how and when they should respond to customer plan changes, the team at Proximus realized they needed a new approach to ensure their customers remained happy.


To spearhead the customer access program, Proximus turned to one of its Blue Prism intelligent digital workers, fondly known as “Camilla.” This digital worker was quickly up and running and now handles more than 700 error corrections per month. When an error is detected, Camilla accesses three different systems to resolve the issue. So not only is Proximus better able to adhere to its strict SLA requirements, but its customers are being better served with faster response times and a quick resolution of any issues.

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