Leveraging AI & Big Data In Broadband Industry For Better Customer Experience
With so much in the news these days about the power of Artificial Intelligence (AI) and how it is already disrupting several industries, companies are obliged to introspect about how they could, or more importantly should, be leveraging the technology within their existing businesses before their competitors use it to gain a competitive edge. Of course, certain industries will be more obviously suited to AI use cases, but within the telecommunications and broadband industry important use cases exist that could significantly improve customer satisfaction and quality of service, improving stickiness of customers and reducing the all-important customer acquisition cost.
Of course, in order to develop good AI models, the most important thing is to feed them with sufficient data and real-life examples that an AI engine can use to enhance its learning algorithms, and this is where Big Data comes into play.
Automating Customer Services
The first obvious use of AI and Big Data is to harness the historical data about customers’ requests and issues in order to improve customer services and develop automated processes that can be used to handle customer complaints. Automating customer services will not only result in potentially significant cost reductions, but the reality is most people, especially the younger generation, are now more used to chatbots, virtual assistants and online/mobile tools to resolve their issues rather than wanting to speak to a human customer agent in order to resolve their issues. AI-powered chatbots can ensure 24x7 support for most common customers’ issues and requests, as well as can be more channelled to provide upselling/cross-selling direct to customers, based on the customer profile and their history.
Management Of Network Infrastructure
In order to deliver pan-country services, telecommunications and broadband companies install thousands of pieces of equipment in order to create their integrated network. Managing and monitoring such devices is a massive undertaking and requires vast manpower spread over geographies. Instead, AI-powered cameras and IoT (Internet-of-Things) devices can be used for monitoring and alerting back to a central control room any issues; allowing engineers to prioritise those sites where faults or issues are expected by the AI models to require human-intervention. For example, an AI-powered camera that can recognise whether a fire, smoke, storm or flood is occurring can send necessary alerts to the central control room or automatically raise a ticket for the nearest engineer to address or even dial the local fire department. This “operational and optimisation opportunity” provided by AI is one that significantly facilitates a field engineers output, optimises the manpower spread resulting in obvious cost reductions, but more importantly improves resolution and uptimes significantly.
Fraud detection is another area where Big Data and AI can really help telecommunications and broadband companies, improving their revenue assurance. Being able to assess and identify where customers are misusing their services or breaking fair usage policies of the companies; AI algorithms can learn the difference between faulty and normal user activity, and identify the anomalies.
In the future, this type of network-based companies will also start to develop self-organising networks or SONs that can self-heal and modify their capacity requirements based on learnt algorithms so that the network is able to self-configure itself based on the demand being put on it and optimising the resources within the network. This has great potential in the future to simplify network capacity planning exercises and reconfigurations on the fly virtually eliminating human intervention that can be prone to mistakes and time-consuming to do. This could easily be the panacea for all companies managing large complicated and inter-linked networks made up of thousands of devices, allowing on-the-fly changes to be made based on calculated rules without possibility of mistakes or customer down-time.
Personalised Marketing & Promotions
Lastly, but obviously not in the least, Big Data and AI can give network companies the capability to personalise promotions and marketing to customers across multiple channels. Whilst this is possible even today, managing a virtual myriad of products and prices becomes very difficult for product managers. With AI and Big Data there’s nothing to stop broadband and telecommunications companies offering personally developed pricing and packages that are attractive to the individual consumer on the basis of specific rules that the AI engine can be trained on. The AI engine can also determine the value of each product to the company’s bottom and top line in order to maximise the same.
The opportunities are clearly boundless for AI and Big Data in the telco space and in the next few months and years it will be interesting to watch how these get rolled out across the world and become almost mandatory for companies to implement just like CRM, ERPs and other solutions were just two decades years ago. The impact of these types of solutions could be revolutionary to the industry and result in step-wise changes in both company service offerings and customer satisfaction.
About the author: Vynsley Fernandes is Wholetime Director - Hinduja Global Solutions (HGS) and CEO of NXTDIGITAL
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