Hear from the Experts: Thoughts on the Future of Computer Vision and Visual Self Service
- How Computer Vision Can Improve Customer Service
- Use Cases for Visual Assistance and Self Service
- Computer Vision at Verizon
- Developing a Field Service Technician-Centric Approach
- What trends is the Service Council tracking with respect to the field service technician and how can computer vision and AR technologies address them?
- What is the importance of having a technician centric approach?
- How does visual assistance support this initiative? What other benefits do you see for visual self-service in the light of the market trends?
Customer service capabilities have recently taken a giant leap forward with the launch of Eve Cortex, the world’s first Computer Vision AI platform that empowers enterprises to custom-build their own visual AR Assistants with a few clicks. The technology has ushered in the age of virtual ‘multi-sense’ assistants that can see, hear, read and interact naturally with customers.
With these new developments, a panel of industry experts and thought leaders were gathered together to weigh in on the future of computer vision AI and visual self-service. The panel included:
- Erik Sheehan, Executive Director of Technology, Systems and Strategy at Verizon
- Donna Fluss, President of DMG Consulting LLC and an industry expert in IVAs, self-service and contact center automation
- John Caroll, CEO at Service Council, an industry leader in customer service
- Patrice Samuels, Senior Analyst at Parks Associates and an expert in smart home products and services
- Eric Jacobson, VP Product Field Services at Salesforce.
Let’s hear from the experts.
How Computer Vision Can Improve Customer Service
What opportunities do you see for businesses using computer vision to improve customer service?
Donna Fluss: There are so many benefits that companies can realize. We’re talking about something that’s really revolutionary in the marketplace. Prior to the pandemic, video wasn’t a commonplace thing in a contact center. Now it is. When you combine that with computer vision and other AI enabled capabilities, it changed the whole world of self-service by giving people, whether consumers or B2B customers, what they want.
Patrice Samuels: Our research shows that consumers prefer to set up and troubleshoot their devices themselves. However, 20% of consumers report that the process was very difficult. Interestingly, 65% of consumers still want to set up their devices themselves, even though they know that they can possibly run into issues. We’ve also found that video-based support has now trumped in-home support as a preferred method of receiving support. So a solution that can allow consumers to set up their own devices, while providing whatever support they may need, is very helpful.
Eric Jacobson: I think there’s a lot of opportunity around field service. We are always looking to reduce the need for additional truck rolls. If we can use computer vision technology to enable customers to solve their problems on their own, we’re not only saving that truck roll, but we’re actually enhancing customer satisfaction right off the bat. A true win-win.
Why is the interest in visual self-service growing? Why should a business adopt this technology now?
Eric Jacobson: This past year has truly been groundbreaking for all of us. We never could have predicted a pandemic situation like the world we’ve been in, but it has accelerated changes that were already starting to happen. Being able to embrace technology like computer vision in order to accelerate customer support and self-service support is really foundational. And I think it is going to be the disruption that everybody needs to accelerate that move to make this a mainstream technology.
Donna Fluss: The state of the world changed the business. Anything that could go virtual, did go virtual and at scale. Customers are increasingly using digital channels, and customer self-service has emerged as the preferred way of obtaining help. At the same time, people all over the world got accustomed — and really expect — to use videos for assistance. So we’re seeing a lot of changing dynamics in the world of service with a lot more to come.
Use Cases for Visual Assistance and Self Service
How can organizations select the right use case for their visual assistance?
Donna Fluss: We know that self-service is a great use case. Studies have shown that at least 60% of dispatches aren’t necessary and can be avoided. We also know that there’s a lot of really lengthy technical discussions that can be avoided with images. Organizations should find the use cases that are first and foremost the most beneficial to customers. And then choose the use cases that are going to be beneficial to your company, your brand, and your bottom line.
Eric Sheehan: You have to be pragmatic. Don’t implement technology just because it is different or cool. Start by focusing on the problem and not on what you might want the solution to be. Look at the key initiatives already underway and see if there are areas where visual analysis would help solve a problem, or make something better. Choose a handful of really simple, low cost, low effort use cases, and then use those as an opportunity to kick the tires on the technology, and be ready to pivot if it doesn’t meet your needs. The key point is to use a practical ROI analysis as your north star when you’re making a decision on the technology.
How do you think the technology can impact the smart home market?
Patrice Samuels: Smart home devices are still fairly new to consumers in the mass market. The smart home device setup process is a huge leap in terms of technical complexity and difficulty. With a traditional product, you just plug it in. But with a smart home device, plugging it in is just the very first step. You have to download an app, connect it to a hub, connect your home network, and then control it using your smartphone. Consumers need help with this.
Also, in the smart home space, a lot of brands are startups. And for these companies, providing robust support is cost prohibitive. If these companies had a solution that could help guide their consumers through the setup process and help them troubleshoot issues, then of course that would be really helpful in reducing the cost of providing support.
In addition, the technology also reduces the cost of owning smart home products. We know that the perceived expense of smart home products is a barrier to adoption. Having to hire someone to help set up or install these products increases the cost of ownership. Removing this complexity would lower the cost to consumers. Having a video solution that can connect to the consumer and help them with hardware-related issues is going to be really helpful in the smart home space and really help to improve customer experiences, provide them with faster support, and drive NPS and all those good things to help expand that market.
Computer Vision at Verizon
In what area can computer vision technology have the biggest potential at Verizon?
Eric Sheehan: I think the potential use cases for computer vision are really endless. But from the lens of a field service organization, we’re focused on self-help and providing guidance. For our customers, it’s about making existing self-help better and more effective by adding visual assistance. It also enables new self-help customer journeys that would just not be possible without computer vision. And the same holds true internally for our frontline employees, where we can use computer vision to guide them and make them more effective.
The second area of opportunity is around job verification with our field employees. Computer vision is an automated way for us to confirm adherence to quality and safety standards. It also allows us to tollgate various stages of the job so we can automate the actions and drive efficiencies that way.
The third opportunity is similar to how Stop & Shop uses the Marty robot to identify, for example, that cleanup is needed in Aisle Seven. But in our space, that means really leveraging computer vision to automate the remediation of issues that our field teams may encounter, but may not identify and document through the normal course of business.
What barriers or challenges do you see in implementing computer vision today?
Eric Sheehan: There have been three key challenges impacting the technology. The first is training computer vision models to recognize objects, which has historically required a fairly high level of effort in training a model using thousands of pictures. But now the technology is to the point where you can train those models in a fraction of the time so this challenge has become less of an obstacle.
The second challenge is integrating the trained models into the customer journey in a simple and cost-effective way. Now functionality is being introduced where you can easily create and modify customer journeys simply by pointing and clicking, which is a game changer when it comes to ease of integration.
We also need to consider how we store and protect the visual information. This opens the security and privacy conversation. As we go forward, this will continue to be areas of concern, not just with computer vision, but with AI in general.
Developing a Field Service Technician-Centric Approach
What trends is the Service Council tracking with respect to the field service technician and how can computer vision and AR technologies address them?
John Carroll: The Service Council conducts benchmark research and one of the annual studies that we conduct is called the Voice of the Field Service Engineer, where we surveyed roughly 1000 field technicians. We asked them questions about their day-to-day job, what they would ask management for, what do they spend most of their day doing? There were a few overarching trends that emerged from the data. One is that technician sentiment is particularly low, caused by manual and inefficient processes, such as paperwork and administrative tasks. Two, they’re experiencing pressures from both customers and management for faster resolution. Three, there’s increased product complexity and technical skillsets required at the point of service. And lastly, that it takes too much time to find information.
Also, one of the data points that emerged is that technicians in the age bracket of 25 to 44 are departing the career at a pace of 60%. They are unsatisfied with their day-to-day role. This statistic is further compounded when you take into account the retiring workforce, known as the Silver Tsunami, which is leading to a talent shortage and a knowledge exodus.
And so, service leaders are stating that the biggest challenge they have is capacity planning. They want to know how to meet and achieve customer responsiveness with all of these factors that are impacting availability of skillset, technology, and labor. Organizations are turning to the gig economy and extended labor networks, and empowering them with the same information, capabilities and access that their full-time employees have.
And, of course, we need to create an employee effort methodology, similar to how we’ve seen customer satisfaction evolve from CSAT to NPS to Customer Effort. Certainly, if you subscribe to the theory that employee satisfaction equals customer satisfaction, we need to think about how can we create an easier pathway for our technicians to do their job.
What is the importance of having a technician centric approach?
John Carroll: We just discussed technician sentiment is one of them. It’s also important to understand how technician sentiment impacts the customer sentiment. According to the Voice of the Field Service Engineer survey, 11% of technicians aren’t proud of their company and wouldn’t recommend it as a place to work. If on average, a technician completes four jobs per day, then a workforce of 500 technicians can cover 2000 customer visits per day. That means that 2000 customers are being impacted by a negative sentiment at the technician level. So it’s very important to boost technician sentiment.
How does visual assistance support this initiative? What other benefits do you see for visual self-service in the light of the market trends?
John Carroll: We’re following four key transformations. There’s a transformation at the worker level, where the emerging workforce lacks the skill sets required. As a result, we’re seeing a lot of upskilling and reskilling. Technology and products have become more complex. There is also the customer’s consumerization, and blending into B2B sectors. So the same experiences we have in our personal lives, we expect and demand in a B2B setting as well. Think of it as the Uberization of service.
And then lastly, we’re seeing revenue transformations, which ties back to the skillset and supplemental skillsets being applied at the technician level. We’re hearing some industries think about reinventing the ability for service contractors to offer extended services whereby you can have access to subject matter experts. It’s a new way to drive new revenue growth, so it’s an exciting time.
You can watch the full webinar here: