Historically, video has played a limited role in the contact center, but things are rapidly changing. For customers, video is part of their digital world and extending that to their customer service needs is not a big stretch. It is also much easier for contact centers to support video now, and it can be treated as another digital channel to support customers.
AI is another technology vector that makes video a valuable data stream, not just for improving CX, but for agent performance as well. Video is a digital medium, so it natively produces a rich set of data, making it AI-friendly. Video captures customer interaction data in ways no other channel can, so it’s not surprising to see more live customer support solutions and CX use cases as contact centers become more focused on AI.
Customer-based use cases for video have been addressed in earlier posts. To get a fuller sense of the business value, CX leaders need to consider internal use cases, especially among contact center employees. This post examines video for three use cases – front-line customer support agents, technical support agents, and supervisors.
1. For Agents: Creating stronger connections and spotting security risks
Video helps provide a more authentic connection between agents and customers, especially in scenarios where body language and visuals can help resolve the issue. While this connection is important for customers, it can be an important factor for agents as well.
Video can help agents with customers in two ways. With video, agents can be more empathetic by using eye contact and reading body language, especially when customers are in high-stress situations.
If video is only being used on the agent side, it can still make customers feel more comfortable knowing they’re dealing with a human, not a bot. So long as the agent engages in a friendly manner, the customer will be more likely to open up, which can lead to a deeper engagement and more meaningful CX.
Not only does it help agents better relay empathy during a customer interaction, but video also helps to identify potential security threats, like someone impersonating a customer. Facial recognition is not widely used in contact centers to authenticate customers, and customer data is usually sufficient for bypassing gatekeepers and getting agents to do their bidding.
Technology like facial recognition and other biometrics could go a long way to mitigating fraud. However, until it becomes more widely used in the contact center, video provides agents with a way to look customers (and fraudsters) in the eye and notice any suspicious activity. Video removes anonymity from the interaction and could serve as an effective deterrent, especially when agents are trained to deal with security threats face-to-face.
2. For Tech Support: Delivering faster solutions with visual context
Sometimes, the contact center includes a dedicated team of technical support specialists who operate within a particular department or line of business related to the product or service. A holistic view of CX needs to consider all employees – not just those in the contact center – and technical support agents have a crucial role to play as part of a live customer support solution.
When customer requirements extend beyond what an agent can do, there must be a seamless handoff to tech support, especially to assure the customer is now in the right hands. Most handoffs are done via voice or chat, so there is often a moment when the customer doesn’t know what is happening and might feel they are being sent down a rabbit hole.
With video, the customer will see the tech support agent’s face right away. Since technical support can be dry and unemotional, video can help the agent display empathy in a way that voice or text won’t allow. Customers will find that mode of engagement more relatable, making it easier for agents to do their best work and elevate CX.
Additionally, video provides technical support agents with a direct view of the issues customers are facing. Customers can use their camera to show the exact problem, which will help to streamline troubleshooting and allow tech support to provide fast and effective resolutions.
3. For Supervisors: Turning video data into actionable insights with AI
Supervisors are an important part of the contact center employee base and have a direct impact on CX. Supervisors are not often customer-facing, so video isn’t about being seen by others. Rather, it’s about helping them monitor and manage their pool of agents.
Video provides supervisors with another quality assurance layer that can help with compliance or resolving issues between agents and customers. Compliance issues may be based on what was said or written in conversations between agents and customers, but video can add clarity when the intent of those communications is ambiguous.
For example, a comment by an agent may appear non-compliant at face value, but the video may show body language indicating the agent was being playful. Video also presents a training opportunity for supervisors to show agents the need to be more nuanced in their communication.
Another example is for problem resolution between an agent and a customer, where there is a dispute over how an issue was handled and who bears the responsibility. Whether this is related to the conduct of people or the content of the communication, video can provide clarity that might otherwise be lost in a voice or text-based interaction.
Even if only the agent is on video, this gives supervisors more recourse to either defend the agent’s position against a customer claim or take appropriate action to remediate things with the customer.
It is also important to consider the impact of AI when it comes to live customer support solutions, quality assurance and training. Supervisors cannot watch every video feed to monitor agent interactions, but with AI, they don’t have to. With AI tracking every interaction in real time, this data can be helpful to supervisors for training and managing agents. By focusing on behavioral anomalies, AI can identify which agents need training for making eye contact, changing their body language, and conveying the right sentiment and tone for a given situation. To some extent, supervisors can do this based on verbal or written interactions, but video provides a much richer data set that can only be tapped by using AI.