The impact that telecommunication companies have on our everyday lives cannot be understated. For example, in a country like India, the world’s second-largest telecommunications market, the industry is said to have enabled 35% of the country’s GDP during the pandemic. From the consumption of content to gaming and browsing, telcos have made a massive contribution by democratizing knowledge and enabling people from all walks of life to connect in real time. Despite this and connecting people over decades, telecom as an industry is struggling. For many years a relative lack of innovation – especially when compared with the likes of Google, Netflix, Amazon, and others – has made telcos more vulnerable to competition. Telcos have an abundance of in-depth customer data at their fingertips, yet they struggle to personalize their customer interactions.
The spray-and-pray method worked fine during the initial days of digitalization, but it has drastically changed with the advent of big data and AI/ML technologies. Customers demand contextual personalisation and companies want to make it a business priority. It is significant to note, that companies that excel at personalisation generate 40% more revenue than average players.
Today, leading telcos have turned to context-driven personalisation that utilises real-time data and insights to cater to the customer’s current and latent needs with the use of advanced analytics, machine learning, and data management tools.
Dynamic and evolving customers demand contextual and relevant interactions
While earlier customers may have expected basic services such as call quality or network range to be a benchmark, this has changed drastically over the years with a significant paradigm shift happening during the COVID-19 pandemic. Being locked down and stuck indoors, customer expectations have continued to evolve and set ever higher benchmarks with a majority now considering experience to be just as important as products and services.
While we briefly touched upon the transition to context-driven personalisation, there are a couple of specific examples of how companies have evolved with changing customer demands and reinforcing their engagement strategy to ensure they are contextual and relevant.
In Europe, for example, certain operators have been able to develop a next-best-action churn model. This provided them with the ability to measure each customer’s likelihood to leave for a competitor in addition to grading the reasons behind churn. This analysis for customer churn, therefore, helped the operator to create campaigns on a micro-segment level and ensure highly personalised, contextual, and relevant interactions to address specific pain points with particular customers.
Another approach is telecoms that use network optimization techniques and real-time data to identify any potential network issues and preemptively resolve them to avoid any impact on the customer. Take for example a customer who is regularly experiencing slow mobile internet speeds, the operator can use network optimization techniques and tools to identify the issue, find the reason behind it and resolve the pain point resulting in better customer experience in addition to reducing support costs.
Moving from telco-specific services to a more digital services business model by integrating industry-agnostic offerings.
As technology becomes a more standardized approach across the telecommunication industry, the differentiation comes from how efficiently one can utilize it and offer better services through those technologies. Moving away from a telco-only specific model to a more comprehensive digital services portfolio model by integrating with other industries allowed telcos to offer an upgraded value to their customers.
Telecos may also have to reassess their business models, backend processes, and customer care support but when executed efficiently and at scale, these services can be a game-changer. The integration of newer services and products would require telcos to be customer obsessed and aim to drive value by creating a digital ecosystem that offers personalized avatars of the customer journey. Rakuten in Japan is the best example of how an e-commerce giant is revolutionizing the telecom space.
A company may choose to approach this by tracing the customer journey to truly understand their preferences to provide their customer with a differentiated digital experience via a range of digital services, which in turn enhances customer lifetime value. From payment services to music, advertisements and partnerships with other businesses – telcos must aim to pose a unique value proposition by giving their customers an exclusive omnichannel and holistic digital experience. The advent of 5G will further empower telcos in their drive to comprehensively personalise customer journeys, thanks to the inherent advantages of the technology. Benefits such as faster speeds, more reliable connections, increased capacity, and improved analytics, will also enable newer applications such as the use of augmented reality or virtual reality for a more personalised experience for each user.
In essence, with time and appropriate resources, telcos can be a lot like SaaS companies and provide integrated systems that can expand their service portfolios and revenue streams.
Changing the Customer Engagement Process
Without a doubt, there are multiple case studies on the internet (successful and otherwise) showcasing companies starting their digitalization journey by making huge investments in marketing technology. It is imperative to note that with martech, there is hardly ever a one-size-fits-all solution, and the focus should be on drawing value from the technology being adopted.
There are multiple ways to look at this and strategy will likely differ from one company to the next. Some telcos may prefer to adopt new technologies as greenfield projects, i.e., they choose not to digitize legacy systems yet. However, the telcos that have successfully implemented these technologies were able to integrate various distribution channels and avoid data siloes. This would range from accruing data from external and internal channels to providing a holistic picture of the customer with the ability to act on behaviours and needs, thereby personalizing the engagement and touchpoints to customers.
Artificial Intelligence and Machine Learning in Customer Engagement
Maximizing value from the adoption of new technologies while controlling costs or investments is crucial. The implementation of emerging technologies such as artificial intelligence and machine learning are already on the rise by telecommunication companies and have proven to be game-changers. This AI/ML-powered revolution can be seen in the form of chatbots and virtual assistants, personalised marketing via better customer data analysis and customer segmentation, predictive maintenance to reduce disruption to customers, and fraud detection to improve the security of systems. Various large global telecom companies such as AT&T, Verizon, T-Mobile, Vodafone, and Orange have implemented these novel AI/ML-enabled technologies to bring about a paradigm shift in customer engagement.
While many are aware of the implementation of these technologies in the digital customer journey to enhance experience and engagement, it is interesting to note that AI and ML can also be used in the retail/store setting to remove bottlenecks. In addition, these technologies allow for the integration of the ‘digital’ aspects of the company with physical stores and this is combined with personalized advertisements and targeted offers that reach the customer at the right time and when it is most relevant!
Artificial Intelligence and Machine learning technologies are now being used by telecommunication operators to create holistic customer profiles. Furthermore, these operators are now able to automate tedious and repetitive tasks and thereby reduce the burden on their teams while allowing more time for innovation and brainstorming.
For example, Reliance Jio uses AI, predictive analytics and big data to create real-time profiles of its 300+ million users. This gives the operator a better understanding of the market and helped it outperform competitors.
Another large telecom operator, Airtel, in India essentially created a new revenue stream by launching an advertisement service that leveraged its data science expertise and customer data. This operator ran targeted and uber-relevant advertisements from across industries including FMCG, BFSI, Automotive etc. These are some examples of how personalisation can offer new business opportunities to telcos.
Ensuring that the customer’s journey is managed and that the contextual marketing experience is on-point, can go a long way in altering the customer engagement process resulting in greater customer loyalty, enhanced brand power, greater customer retention, higher customer activation, enlarged range of revenue streams and a higher average revenue per user. To get a better understanding of how to elevate your marketing campaign’s performance, check this article here, which showcases the use of emerging technologies like AI/ML to maximize value.
