Robotic Process Automation for Telecom
Build efficient data flows, reduce operational costs, eliminate errors and improve customer satisfaction with RPA
with measurable outcomes, ensuring lowered costs and high accuracy. Telecommunication companies today face high expectations from users, whose connectivity needs grow along with the complexity of global communication networks. At the same time, the number of back-office tasks related to invoicing, monitoring, data transfer, security, reporting, and so on, can quickly become overwhelming.
The telecommunications industry relies on repetitive, high-frequency, manual processes that follow strict rules. Employees often have to tackle many sources of complex data stored in multiple file formats while trying to deliver a pleasant, human experience to customers - two tasks that are not very compatible, which results in lower customer satisfaction and a stressed out workforce.
Though high reliability and accuracy of process outcomes is absolutely crucial for telecom companies, tasks such as updating data fields and searching through vast knowledge bases introduce a high risk for error. Additionally, prioritizing first call resolution can not only lower operational costs, but also vastly improve customer experience.
Readiness to face increased service demands and scale rapidly is a big part of the telecom industry. On top of that, the volume of rich content transferred between users and apps continues to increase. While infrastructure can often be scaled on-demand, telecom companies are limited by the number of employees they are able to call on when the need arises.
Increase operational capacity and broaden your offer through innovation at a very low cost.
Take advantage of RPA’s high cost efficiency and fast ROI, saving 25-80% on current operating costs.
Deploy a digital workforce that operates 24/7, 365 days a year, and doesn’t make mistakes.
“RPA brings a number of benefits to the telecom industry. Firstly, it can introduce efficient 24/7 competitor price tracking and deep comparative price analysis, as well as AI-powered prediction. Secondly, it can be used to reduce overhead expenses without affecting data security or quality of outcomes. And thirdly, it can help providers achieve a more human, personalized customer experience, positively affecting customer loyalty and improving FCR rates.”
Edyta Pietak, CSO at AnyRobot