Putting Computer Vision at the Heart of a Seamless Customer Experience

Providing a seamless customer experience is a core mission for most customer-centric businesses. Yet when it comes to customer services, companies still struggle to provide a frictionless customer journey. When a problem is resolved with a single interaction, the customer is happy. It doesn't matter if it's a call, a chatbot, or a self-service page on your website. A fast resolution increases brand trust and customer satisfaction.

However, customers often need multiple interactions with the company via calls, messages, emails, or even in-person to get their issues fully resolved. We are all familiar with how frustrating it can be having to explain your issue multiple times to each agent. Customers feel like their time is being wasted, uncertain of whether they are talking to the right person at any given time, and ultimately doubting whether the company can handle their queries efficiently within an ecosystem that might seem totally out of sync to an outsider.

Besides providing a sub-par brand experience that erodes customer satisfaction and trust, this lack of operational efficiency also creates huge overhead. Each agent during any interaction is somehow trying to identify the problem with little or no context. Imagine going to a doctor without access to your medical records. The doctor would have to interrogate you every appointment to make an educated assessment, and even then, without access to previous analysis results, scans, or historic data, the doctor wouldn't have all the necessary background information to make the best-informed diagnosis.

What if customer service teams and agents had a way to easily share and access information to create a seamless experience for the customer? More importantly, what if each representative was able to see with her own eyes what the customer is experiencing? Which light of your router is flashing red? Which part of your fridge door is broken and causing it not to close properly? Which message is your smart coffee machine displaying when it gets stuck?

Becoming Your Customers' Eyes and Ears

The computer vision revolution is here. Its application to improve customer journeys will be a game changer with the potential to radically enhance the overall customer experience. This doesn't mean dropping traditional communications channels but modernizing them with an added visual layer to help capture crucial customer data to help inform every interaction.

Customer experience teams can now use traditional self-service channels, such as automated chat, phone, and messaging, to capture visual information, including video and images. More sophisticated teams leveraging computer vision can even guide customers to perform activities in real time using computer vision and artificial intelligence. With all this rich visual data, if and when a live session with an agent is needed (remote or in-person), all of the captured information is at the agents' fingertips.

Many companies go above and beyond to ensure that every customer interaction, whether online, offline, or through self-service, is exceptional and delightful. However, during the switches between agents and transitions between platforms, things fall through the cracks. In the customers' minds, even if each agent is extremely pleasant and tries her best to help, if the interactions are disjointed, they provide a frustrating overall experience.

A key metric of success for customer experience teams, especially around customer service, is customer effort. Of course, the holy grail would be to resolve all queries in a single interaction that is as brief as possible. Most customers even prefer to solve issues themselves with some self-service support when available. However, situations will always arise when follow up calls, visits, or assessments are needed.

When multiple interactions are needed, companies need to pay closer attention to their channel-switching practices, which has been proven to be the leading factor in increasing customer effort, resulting in lower customer satisfaction. High-effort interactions include needing to repeat information, connecting a second time, experiencing generic service, the lack of a self-service option, or needing to exert additional mental effort to have an issue resolved.

What if your live agent could see the self-service solution a customer tried before as he picks up the phone? What if his colleague could see the visuals shared on the previous call? What if the field agent had access to all the visual records before walking into the customer's house?

Access to contextual visual data provides the missing link needed to make interactions more efficient and effective. A seamless contextual transfer of data between self-service, live remote service, and field service interactions will significantly drive improved customer satisfaction and agent performance scores.

Daniela Levi is director of product marketing at TechSee.