Amazon head Jeff Bezos is famously credited with saying "Your brand is what people say about you when you aren't in the room." If the service industry were a brand, those conversations wouldn't be very kind. It's not surprising. Our customers live in a world with 20-minute food delivery and instant access to half a dozen streaming services. They expect more from their service experiences than ever before. Many service teams have failed to keep up, damaging their retention, their brands, and their bottom lines.
The good news is that an uncertain economic outlook is forcing change. The winners in the new economy will deliver exceptional customer and employee experiences while improving their efficiency. Threading this needle however, demands a new approach.
Look at almost any corporate social media account and you will find irate customers complaining about their service experiences. When customers message most corporate accounts through social media platforms, they are sent straight to bots. Many of these bots are the corporate equivalent of hold music. The music might be great, but nobody likes being stuck on hold. A recent TechSee report found that nine in 10 customers have lost faith in bots' ability to help them, and seven in 10 only use bots to get through to live service agents. Somewhere, somehow, something has gone very wrong.
The fundamental problem is a lack of contextual understanding. People use social media to talk to friends and family, and those friends and family reply in kind. Many companies, however, want to use the platform to communicate to users, while users want to use social platforms to communicate with businesses. There is a world of difference between communicating to someone, and communicating with someone. What went wrong? The wrong sacrifices are often made in the interest of scale. Staffing social media pages and, for that matter, service chatbots across any environment can be very expensive. However, putting an ineffective automation tool into any channel simply leaves customers frustrated.
In contrast, consider the overnight proliferation of visual support tools. In today's market, everyone knows how to open a two-way video chat with friends and family through Facetime, WhatsApp, and any number of channels. Video support technology allows customers to show agents their issues and allows agents to visually guide customers to resolution.
There is a good reason that customers prefer visual instruction 48 percent more than verbal instructions: Showing is easier than telling. Service leaders have not put automated bots on the other end of video calls; it simply wouldn't work. Service leaders recognize that the added clarity and context of video allows them to serve customers better and faster. Video support has proliferated because there is a clear value to the customer, the agent, and the enterprise.
Which then begs the question, how can service leaders deliver better automation at scale that works for employees, customers, and the enterprise's bottom line? How can they find ways to reduce costs without leaving frustrated customers screaming at bots that cannot hear them?
The answer to service automation at scale lies in computer vision artificial intelligence. Over the past 20 years, this technology has advanced by leaps and bounds. I'm not just referring to driver assistance, autonomous vehicles, and warehouse automation, but applications as common as Google Photos. Google Photos recognizes my family members and automatically tags them in every image and video in my cloud, at every stage of their life, flawlessly. Similarly, we trust the AI on the camera on our iPhone to take the best possible picture. Only the most advanced users are manually configuring their phone cameras because the AI is that good.
In today's economy, there is no technology as practical or transformational to the service industry as computer vision AI. Modern solutions can deliver computer vision models capable of complex job verification, ensuring that technicians have correctly completed the most complex wiring jobs before they leave the site. Think of all the savings in fuel costs alone!
Customers already look to computer vision to tag their friends on social media. What if they could open your mobile app or chatbot, show your AI their issue, and receive automated augmented reality instructions for how to fix it? Imagine how many returns could be avoided if customers could instantly fix or repair a device on demand. This wouldn't just improve the bottom line, it would reduce waste and carbon emissions, improve supply chains, and yes, customer satisfaction.
This isn't just fanciful thinking. A recent study found that 91 percent of consumers are open to using computer vision AI if it will get them faster, better service. The question now is, what are you going to do about it?
In a world of economic uncertainty, rising fuel prices, skilled labor shortages, and diminishing brand loyalty, service leaders are feeling the squeeze. The answer to today's problems won't come from yesterday's shortcuts. It's time we rethink service automation. It's time we bring the customer back into the conversation. It's time to take AI out of the lab and deliver AI for real business. It's time for the computer vision revolution.
Eitan Cohen is co-founder and CEO of TechSee.