[Column] Data and AI’s Advantage in Improving Customer Experience for Telcos

Telcos are most successful when customers feel as though their operator truly understands them. Data is the key to building that trust because it can reveal insights that lead to effective problem resolution, and identify customers’ needs, wants, and opportunities. To take things a step further, CSPs can also invest in automation and artificial intelligence (AI) to support proactive customer engagement by automating business processes and solving issues on-the-fly.

Data analysis can be the differentiator, because it provides the insight telcos need to create a better customer experience overall. With this in mind, CSPs may be even better positioned to tap into the data’s value than digital players, because they have the resources to invest in a long-term change, deep knowledge of both their business and the industry, plus — most importantly — many years of customer behavior data such as call and SMS history or location-based data, which is a manifestation of customers’ specific needs. CSPs know to go beyond network data in order to get a 360 view of the customer and can factor in the NPS (net promoter score), service tickets that users have opened with customer service, rate and subscription plans and more, in order to get the full picture.

Customer experience is the new competitive frontier for telcos, and it would appear traditional operators are losing the battle to best-in-class digital players such as Google, Amazon and Apple. As a result, customer expectations for digital experiences are being set in other industries, and those expectations are trickling into the telco space; so CSPs must be ready in order to stay relevant.

Although telcos are sick of hearing about how their net promoter score compares to digital champions, the reality is that CSPs rank far worse than the digital-only heavyweights in terms of customer satisfaction. Ultimately, it’s all about creating a toolkit of capabilities and technologies that support perfectly timed customer engagements.

Data Supports Effective Decision-Making

Recently, the CEO of a CSP wanted to find out what was causing customer churn. Though he had an idea, he wanted to see proof in the data. The analysis showed that his intuition was correct: The customers who spent the most money were leaving in search of a better deal elsewhere.

However, he hadn’t known about a second group of customers who were also leaving — customers who paid too little. Those customers weren’t engaged and didn’t get enough value from the service.

The insights gleaned through data analysis enabled the telco to design several marketing campaigns to address these two potential problems. First, if a customer called and indicated that they were paying too much, the telco gave them the option to lower their rate. Second, the telco reached out via email to customers who were paying too little and offered a better deal expand their services and get them engaged enough to stay.

Intuition is almost always right, but it is not a holistic view of the situation. Data analysis helps to complete the picture and find trends that you might not otherwise see.

AI Enables Digital Time

At the same time, data analysis can do more than reveal opportunities based on past information. When it’s supported by AI, real-time data analysis empowers CSPs to analyze usage and customer behaviour in-the-moment — driving contextually relevant engagements in this era of instant gratification.

For example, imagine a specific mobile customer uses Netflix more than any other video-streaming application, but is also dangerously close to reaching the monthly data cap. By analyzing the IP address’ traffic patterns, a telco can uncover the perfect moment to offer this customer a data package that includes unlimited Netflix streaming.

Now, imagine if this entire process was automated — from AI-driven analysis to automated offer generation to immediate fulfillment and accurate billing. In this scenario, it’s possible for the customer to hear about a perfectly tailored service package at the peak moment of interest (e.g. right at the data limit).

This is how customer perceptions toward CSPs start to change, when they view offers not as an annoying or unwelcome intrusion, but as a relevant and perfectly timed solution to an immediate problem. And it’s already possible, especially as AI continues to make its way into the CSP technology stack. If CSPs are to remain competitive with encroaching digital service providers, it’s time they start viewing certain aspects of their business as assets and not liabilities. Telcos may be the “legacy” player in the game, but that legacy includes decades of customer data, plus the resources to invest and maximize emerging technologies like AI. The opportunity is ripe for personalized customer engagement, and AI-powered data analysis can enable it.

This column was submitted by Henrique Vale, the Head of Nokia Software for MEA at Nokia and Santeri Jussila, the Head of Analytics Product Line Management at Nokia.

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