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Changing the Game in Customer Care with AI-driven Device Intelligence

Artificial intelligence is helping telecoms transform customer care from reactive cost centres into proactive, data-driven operations. At the forefront of this transformation is CUJO AI’s device intelligence, which not only enables customer care agents to resolve issues more rapidly, but also allows operators to conduct root-cause analyses, measure service quality for every type of device on a customer’s network, as well as make their deployment testing much more representative to avoid issues in the future.

CUJO AI

December 11, 2023

6 Min Read

Artificial intelligence is helping telecoms transform customer care from reactive cost centres into proactive, data-driven operations. At the forefront of this transformation is CUJO AI’s device intelligence, which not only enables customer care agents to resolve issues more rapidly, but also allows operators to conduct root-cause analyses, measure service quality for every type of device on a customer’s network, as well as make their deployment testing much more representative to avoid issues in the future. 

You’d be hard pressed to find a telco that doesn’t boast about their service quality, Wi-Fi coverage, and speed. Network service providers (NSPs) understand that the connected experience has extended beyond the line to a customer’s home – it now includes every connected device, ranging from smartphones to smart home controllers. 

More Devices, More Challenges 

In the past, customer care agents primarily dealt with issues related to the line leading up to the home. Now, they are tasked with troubleshooting issues for thousands of diverse devices inside customers' homes. When the connectivity of a single device fails to meet the user’s expectations, it can create the impression that the entire Internet connection is not working properly, even when the issue lies with the device itself. 

Customer care agents often waste valuable time trying to identify the problematic device, questioning the customer about the device’s type, brand, and model to get a clue about the potential issue. They usually lack contextual data about the customer’s network, beyond a handful of generic hostnames and MAC addresses. 

Additionally, a significant number of consumers (42% in the EU) lack basic digital literacy skills and don’t know what devices they are using, making some customer care cases time-consuming and challenging to resolve. For example, an older router might downgrade the entire network to an obsolete standard because a single IoT device does not support a newer standard. 

This part of the troubleshooting process becomes trivial with AI-driven device intelligence, which identifies devices as soon as they are connected to the customer’s network, giving the customer care agent not only precise data about the device in question, but also its surroundings. From there, localising and solving the problem is a lot easier, even when it is caused by other devices on the network. 

Device intelligence not only speeds up issue resolution for customer care agents but also empowers telcos to act pre-emptively to reduce call numbers by improving the connected experience and solving issues before customers feel compelled to call. 

Transforming Customer Care 

Network service providers can use device intelligence data to analyse their entire user base and identify customers with devices or groups of devices known to cause connectivity issues. If these issues can be resolved by tweaking a setting on the router or remotely restarting it overnight to avoid disturbing the customer, many calls can be prevented. 

For some devices, operators can even automate the process by running service quality tests. This requires rapid device identification, where a device is detected, identified, and classified within minutes of connecting to the network. From there, an automated test evaluates the service quality available to the device according to its capabilities and requirements. 

If a device is not receiving the connection quality it requires, the telco can assist the customer in improving it. For example, when the customer connects a 4K streaming device to Wi-Fi, the telco’s app notifies them that plugging in an Ethernet cable would improve their video streaming quality. The same goes for moving smart phones to a higher Wi-Fi band or, in the case of least-effort IoT devices, moving them to a lower band to improve the connectivity for other devices. 

These quality measurements can also be conducted over time to ensure that the connectivity for every device in the customer’s home is adequate, not degrading during peak times, or when devices move around the home. 

Automated nudges for self-service and troubleshooting don’t solve every connectivity issue. Telcos still need to perform root-cause analyses for edge cases, and device intelligence is a powerful tool that provides crucial bits of data to enhance those analyses. 

Analysis At Scale

Root-cause analysis is a labour-intensive process, often requiring skilled customer care agents to spend considerable time, deploy diagnostic tools, or even send a technician to the customer’s home. With device intelligence, the results of this effort can be magnified and applied to the entire customer base, preventing many similar calls that might result in unplanned truck rolls. 

For instance, an analysis might uncover that a laptop with an obsolete Wi-Fi driver has a connectivity issue with one of the telco’s routers. Device intelligence data allows the telco to quickly find out how many customers with that router configuration use the same device model and determine the best course of action. 

Telcos use device intelligence both to analyse device-related connectivity issues and evaluate their scale across the customer base. Understanding how many customers are affected by a connectivity issue allows the telco to prioritize solutions that impact the most customers and prevent the largest number of calls. 

These analyses are also extremely useful for testing updates and rollouts. Instead of selecting a random segment of the customer base, a telco can create a representative sample that includes edge cases, such as homes with dozens of smart devices. Any connectivity issue that arises during the trial rollout can be evaluated in the context of the entire customer base, informing the telco about the potential impact during the full rollout. 

Customer Care Is Transforming 

Device intelligence allows network service providers to conduct extensive preventive customer care, prioritize issues, measure their scale and impact, and enhance their capability for root-cause analyses, applying solutions across the customer base. It also enhances their ability to do root-cause analyses and apply their solutions across the customer base. As a result, customers experience better connectivity, telcos receive fewer calls, the calls they do receive are resolved faster, and there are fewer unplanned truck rolls. 

While most telcos advertise better connected experiences, only those that focus on transforming connectivity through an evidence-based, data-driven approach will stand out in a competitive market. Our customers’ experience shows that better connected experiences are the result of improved data access for customer care agents, automation, and data-driven decisions built on AI-driven device intelligence. 

CUJO AI’s device intelligence solution Explorer identifies over 50,000 distinct device models and configurations, which allows network service providers and their customer care agents to view, in real time, the number of devices connected to an SSID, their types, brands, models, and even OS versions. For some key devices, such as Smart TVs, device intelligence also provides essential contextual data: for example, whether the device can stream video in 4K. 

CUJO AI Explorer is currently deployed in over 50 million home networks across North America and Europe, with customers including Comcast, Charter Communications, TELUS, Sky, EE(BT) and others. 

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