The telecommunications industry is in a tough economic environment, grappling with challenges to increase revenue. Over the last two years, mobile operators in the U.S., UK and Canada are fighting to improve bottom line figures. Combined with inflation, supply chain issues, and the upkeep of legacy technology, mobile operators face mounting financial pressures.
To meet new customer expectations for AI-driven personalization and faster connectivity, mobile operators must explore novel ways to stabilize and enhance their balance sheets. One viable avenue lies within their existing assets: the very mobile devices they sell to their customer base. They hold untapped potential for improving economic outcomes when operators leverage the intelligence on them more effectively.
So what is device intelligence? Device intelligence refers to device-related information sourced from a customer’s phone, not limited to but including diagnostic data or device configuration information. It allows the operator to create a complete profile composite of the customer and where they stand in the mobile device lifecycle, and to better manage the customer at different stages or journeys. Practically-speaking, device intelligence functions as a guide that empowers frontline representatives to make smart decisions in different customer journey situations.
The problem is that mobile operators are neither extracting different kinds of device intelligence nor executing on it at the right time and place. Rather than collecting device diagnostic data, for example, and putting it into the hands of customers or frontline representatives, operators are allowing this data to be gathered at the back end, after critical decisions on a customers’ devices have already been made.
This creates risk and leads to unnecessary losses and incurred costs that could have been prevented had the intelligence been gathered and acted upon earlier. It also inhibits the operator from being proactive and upselling customers while staying risk averse.
The key to solving this is for operators to shift the device intelligence gathering, mainly diagnostic information, to an earlier point in a customer journey and take more control before the opportunity is lost. There are a few powerful examples.
Transferring Device Intelligence to the Frontline to Reduce Costs
We can look at warranty deflection and call center operations as powerful examples of opportunities for cost savings. Typically, the process to assess and execute a warranty claim includes simple, manual and minimally- standardized methods that transfer all the power to an OEM that is downstream to determine if the warranty should be honored. In cases of no fault found (NFF), which compose an average of 40 percent of customer mobile device warranty claims in the U.S., operators are at very high risk for no payback and are left holding the bag.
By shifting device intelligence to the frontline – giving representatives digital tools to accurately evaluate a device and comprehensively check for a warranty void – operators can significantly reduce risk and significantly improve NFF case deflection.
The same strategy can be deployed with customer support. In call center support, operators are delaying acquisition of device intelligence within a customer journey leading to reduced customer satisfaction. Rather than being empowered to resolve device care issues on their own, customers are forced to call support centers for assistance, delaying resolution time and causing frustration and incurring more cost of service.
In this scenario, operators can deliver customers device intelligence and empower them to troubleshoot on their own. Practically, using a self-help diagnostic tool on the operator’s app, a customer can self-resolve rather than reach out to customer support for help. This can help the operator deflect more calls and reduce unnecessary customer service costs.
Converting Device Intelligence into Upsell Opportunities
Acquiring and placing device intelligence into the hands of frontline representatives also presents an upsell opportunity for mobile operators. Insurance is a primary example of this, whereby operators can identify customers who are eligible for insurance attachment and make a proactive offer and also stay risk averse.
In cases of bring-your-own-device (BYOD), frontline representatives in a retail setting can assess a device’s diagnostic performance and proactively offer the new customer insurance. In remote settings, customers who execute an on-device health check at home can also be offered insurance proactively. When a device health check reports indicates strong performance and eligibility, an insurance offer can be programmatically triggered and sent to the customer.
The life blood of mobile operators is also the feedback loop for increasing customer ARPU and becoming more operationally efficient at the customer engagement point. It’s only a matter of taking control of the device lifecycle and putting intelligence into the hands of the frontline teams and the customer. Explore how MCE’s digital device lifecycle management platform (dDLM) platform enables mobile operators to achieve this.
