Mobile operators are increasingly focused on improving customer lifetime value (CLV) by boosting operational efficiency, enhancing customer experience, and identifying new monetization opportunities. With operating expenses rising by more than 4 percent for three consecutive years between 2021 and 2023, and ARPU growth expected to remain low at just 0-1 percent in 2025.
While operators have made significant investments in network infrastructure and billing systems over the years โ particularly with the rollout of 5G โ there is one last significant bastion for growth. The mobile device experience remains a largely untapped opportunity, as the primary way customers interact with their operator. Yet it is often fragmented, slow and impersonal.
The root of the problem lies in how customer engagement is approached. Most operators still rely on a product-centric strategy, launching promotions and offers based on internal timelines and business goals, rather than on customer needs or behaviour. As a result, customers often receive generic promotions that are ill-time or service prompts that are reactive and late to the game, after theyโve already experienced frustration.
With the average U.S. operator Net Promoter Score (NPS) sitting at just 31 points, customer dissatisfaction is clear. According to MCEโs survey of 23,000 telco customers, NPS drops sharply at key moments across the device lifecycle โ by 16 points during onboarding, 19 points during in-life service and near the end of the contract, when operators should be maximizing retention and revenue, many fail to offer timely trade-in or upgrade options, resulting in an 18 point drop.
These numbers reveal that customer frustration is peaking during moments when operators have the opportunity to strengthen relationships and maximise value. This is not only resulting in missed revenue opportunities but is also eroding trust, increasing churn and damaging long-term brand loyalty.
To address this, operators must adopt a more customer-centric model โ one that delivers the right experience, in the right channel, at the right time.
What do customers actually want?
Expectations are shifting rapidly. Todayโs consumers demand faster, more convenient, and more personalized experiences across both digital and physical channels. Seventy-three percent of customers expect better personalization as technology advances, and 59 percent prefer digital-first, self-service options. A majority โ 73 percent โ now engage with multiple touchpoints throughout their purchasing journey.
Much of this shift is generational. Gen Zโs global spending power is projected to reach $12 trillion by 2030. As digital natives, they are more likely to value seamless, self-directed journeys and gravitate to operators that know and anticipate their needs.
When mobile operators take a customer-centric approach , the business impact is significant. McKinsey reports that customer-centric operators can achieve up to 8 percent annual revenue growth, reduce service costs by 15 percent, and increase NPS scores by up to 40 points.
While many operators have launched digital transformation initiatives to move in this direction, there is still a gap between aspiration and execution. A new approach to engagement is needed to truly transform โ this is where AI comes in.
AI: the enabler of customer-centric mobile device lifecycle management
In response to rising expectations, 97 percent of mobile operators are now assessing or adopting AI solutions, with nearly half naming customer experience optimization as their top investment priority. AI is already delivering strong results in areas like network management and infrastructure. Still, 44 percent of operators are investing in generative AI for customer experience, the top ranked priority in the survey. The next phase is for customer-facing applications that directly impact the CLV levers.
Mobile operators tend to be reactive in how they engage with customers, typically waiting for the customer to reach out. However, the reasons for a customer outreach are often due to negative experiences, which increases risk of churn and adversely impacts CLV. This leads to poor customer experience and thus a growing cost to serve and reduced ability to monetize.
AI flips the script from reactivity to proactivity by analyzing available customer data โ CRM, mobile device and even conversational (in GenAI cases) โ and takes a more proactive approach, identifying moments when a customer might be ripe for service or an upsell, for example. AI can then engage the customer and capture more intelligence proactively and determine the next best action given a customerโs disposition.
If we look at device care as an example, AI can intake device diagnostic performance and CRM data and then assess the best action for the customer โ whether suggestions on more optimal utilization, repair or trade-in is best.
What does AI look like across the device lifecycle?
AI delivers the most value when itโs used to support a customer-centric approach throughout the entire mobile device lifecycle. By embedding AI into these touchpoints, operators can act with greater speed, relevance, and commercial intent โ creating both customer value and operational impact:
Onboarding
In cases of bring-your-own-device, AI tools can instantly assess its make, model, condition and configuration. This allows the system to identify opportunities for VAS upsell or insurance attachment at the beginning or over the course of the lifecycle.ย
According to internal MCE data, operators can increase insurance take rates by 20 percent with a proactive, data-driven and digital approach.
In-life service and device care
During the in-life phase, AI transforms the way customers manage device issues. On-device diagnostics help customers troubleshoot issues, and if escalation is required, AI can guide customers to the right resolution โ whether self-service, escalating to a live agent or scheduling a retail visit.
In addition to resolving problems more efficiently, AI can offer several options to a customer to resolve the device issue, from device utilization recommendations to repair to a device upgrade.
Leveraging AI for device care can result in a 30 percent drop in support-related OPEX, and up to a $22 increase in ARPU. It can also help reduce no-fault-found warranty claims and improves customer satisfaction, boosting NPS by 20 points.
Retention
As customers near the end of their contract or device lifecycle, AI helps operators act earlier and with greater relevance. By analysing usage behaviour, device performance and plan history, AI can flag churn risk and deliver timely, personalised offers โ such as a trade-in or plan adjustment.
Rather than relying on generic campaigns, this approach allows operators to engage more precisely and improve conversion at the point of decision-making. Overall, taking a digital-first approach, which can include AI, can yield to a 5-fold increase in trade-in volumes, a 78 percent reduction in processing time for in-store trade-ins and a 20-point increase in plan upsell rates.
Real-world example: TELUS
One operator already putting this into practice is TELUS. By implementing generative AI for its mobile app (myOperator) chatbot it transformed customer engagement by initiating an interaction with a push notification, starting a conversation and then pulling real-time diagnostics insights with a device health check. This proactive approach with AI allowed the operator to understand the customerโs disposition and gauge sentiment, offering the best solution to the customer given the conversational inputs and mobile device intelligence (diagnostics and configuration data).
By leveraging GenAI, TELUS saw a 4x increase in chatbot-guided user journey engagement, 3x increase in user actioning of a promotional offer and a 1.5x increase in store locator usage, indicating higher intent to visit the retail outlet.
For mobile operators to unlock the true value of AI, it must be supported by a connected, digitally mature foundation. MCE is a pioneer in customer-facing AI for, offering real-world solutions that are already delivering measurable results. At the core is MCEโs Intelligent dDLM platform, which provides the infrastructure to deploy AI consistently across all customer touchpoints. Together, the platform and AI capabilities help operators improve customer experience, reduce operational costs and unlock new monetization opportunities.
