Having worked with big telecom companies, we understand the immense value, pattern based analytics powered by Machine Learning adds to telecom services. We also help them capture newer data points about their customers which are beyond their transactional world view and frame of reference.
Algo 8 platform and frameworks for Telecom services enable them in
Create, Conceive and Implement Big Data enterprise solution to store and curate all type of internal and external data on a single platform, which maintains flexibility, security and scalability for any type of data initiative.
Creating a 360 degree view of the customer, their profiling, creating a customer story and enabling analytics driven intervention
CustomizedAI and Pattern based Learning Solutioning for contextual application in enterprises. Creation, Conception and Development of use cases in highly secure environmentsfor
An NLP based brand perception tool, which collates all social chatter about a telecom and its competitors from channels like mail, social media,news,etc. Opini8 also enables customer support through NLP.
A strong and dependable cellular networking system is an extremely crucial part of one’s life and with the advent of 4G, 5G and the soon to be launched 6G, this field holds a lot of promise over how communications in the telecom sector will evolve over a period of time. The role of AI and data science in this regard cannot be underestimated. Interestingly, telecom companies world over have taken note of AI’s tremendous disruptive sector and have invested good money and resources to harness this technology to make their business more sound. UK based telecom giant Vodafone for instance has come up with a host of features that aim to integrate AI into its voice calling and internet facilities. Their proudest moment would arguably be the launch of TOBi- the first live chatbot in the UK telecom industry. Tobi is powered by IBM Watson and also integrated with Facebook Messenger, but now 'his' role has been expanded to answer account-specific questions on subjects like roaming. Another noteworthy achievement of Vodafone is the incorporation of voice biometrics authentication. This will enable customers to use their own voice to authenticate and access their account. Vodafone plans to be link this with artificial intelligence to support self-service too, meaning the customer gets a smooth experience – all from the power of their voice. Vodafone’s Chief Operating Officer and director of customer service, Neil Blagden, remarks, “The continuing operational shift from the firm was designed not only to ensure ‘Seamless’ customer experiences but also to help it attract talent and set an industry benchmark for how things should be done.” Other telecom companies seem to be treading a similar path with relatively similar results. Utilising the power of AI to bolster consumer satisfaction and participation in data mining exercise would be the winning factor in this endeavor.
It’s been rightly said that data is the new oil and mining it in the right quantity at the right time and at the right place is key to maximum profitability for any company. Such a precedence holds more weight for the telecom sector. Given that internet penetration rates across the world are increasing at astonishing rates, it's no wonder that telecom companies are investing in suitable and efficient AI systems to ensure that internet connectivity is hardly ever disrupted. Given that broadband connections relying on fibre optic channels may face resistance from natural or man-made elements, it’s crucial that telecom companies put safeguards in place to ensure that these ‘Digital Lifelines’ are maintained at optimal conditions at all times. US based Verizon has taken important steps in this regard. Until recently, Verizon primarily relied on customer feedback to understand when the speed and quality of its service was falling short of expectations. Now it’s predictive analytics algorithms monitor 3GB of data every second streaming from millions of network interfaces – from customers’ routers to an array of sensors gathering temperature and weather data, and software which “listens in” on operational data, such as billing records. Matt Tegerdine, director of network performance and analytics, Verizon, further chips in by stating, “ The beauty of this is that we don’t just look at one singular data source like interface statistics – we’re also going out and collecting things like environmental statistics, CPU usage on routers. We’re using machine learning to learn what ‘normal’ is.”