One of the many challenges obstructing the operational decision making for telecoms is the virtualisation of networks, to scale them for the 5G upgrade. This is certainly not a quick win but has many stumbling blocks. Not only network providers have to centralise their network management, but they need to ensure the delivery of profitable services to end-customers as well. Tuple applies machine learning algorithms to identify & predict issues in the network and notifies before these issues escalate into emergencies. The data-driven applications provide a centralised platform for unification of all the operational data including device logs, where the automated predictive analysis alerts with valuable insights on the root cause to reduce the resolution time.
Customers today demand more than a generic call & data service from their telecom service provider. Pricing promotions, weaker connection capabilities, slow customer service & billing disputes are just a few of many reasons customers tend to leave a network provider. Tuple uses advanced analytics to provide a comprehensive view on the entire customer journey including product, offer, usage, & rebate history by unifying structured, unstructured data from call centres, pricing & promotions, weblogs & network experience. The advanced algorithms give highly accurate predictions on customer behaviour & identify contributing variables.
Telecom companies tend to have a large user base, with every customer demanding instant resolution. Managing communication through calls & written text for this dense volume is exigent. The customer support teams juggle myriad of queries ranging from network issues, billing to device setup. Tuple’s chatbot is modelled with advanced machine learning algorithms & is programmed to efficiently manage a variety of chats at the same time. By leveraging Natural Language Processing (NLP), the conversational interface of Nova is trained to understand the intent of every message customer used to interact & to account for entire conversation before responding with a resolution of the relative query.
Telecom frauds cost billions to the industry revenue & the complaints continue to add up every year. To avoid fraudulent attempts, companies need to keep a sharp monitoring eye on suspicious calls, as they tend to take advantage of customer’s lax security practice. Tuple puts data analytics in action to analyse the enormous call traffic in real-time, to identify suspecting call patterns. We automate real-time call routing decisions by analysing different data-points like customer status, purchase history with predictive AI and this way, network operators can prevent the fraud before the eruption.
To acquire new customers who would lead to increased sales, telecom companies need to improvise their product recommendations by analysing what exactly their customers are looking for - be it a better price, added volume of internet, or other OTT benefits. Tuple helps network operators in making the right recommendations, to the right customer and at the right time. Our AI-powered recommendation engine gives accurate insight for cross-selling new services, matching pricing plans, or making personalised offers for customers.
Discover how to stay afloat in the crowded world of Tariffs & deliver connected omnichannel experiences.Book A Demo