Automation has become the theme of today’s business world, enabling users to accomplish a wide range of repetitive tasks from booking a service, refund requests, order status inquiries to cancellations. Technologies powered by Artificial Intelligence (AI) are significantly reducing the workload on human service agents, freeing them up to focus on more complex and high-value engagements. Jay Hinman, VP of Marketing, DigitalGenius, in an interview with Analytics Insight tells us how the AI-powered, automated customer service is the future of businesses and how the company is helping enterprises understand and automate customer interactions without a human agent.
Kindly brief us about the company, its specialization and the services that your company offers.
DigitalGenius was founded in 2013, and we’ve made it our mission to transform organizations by bringing practical AI and machine learning into their customer service functions. Our AI platform is used by KLM Royal Dutch Airlines, Perfume Shop, Air France and many other forward-looking businesses to drive conversational process automation through the use of deep learning.
Our AI platform puts customer support on “autopilot” by understanding conversations, automating repetitive processes and delighting customers. This platform is powered by deep learning that understands a customer’s objectives (i.e. what problem they’re trying to solve), then drives automated resolutions through APIs that connect to companies’ own backend systems.
This not only makes for happier customers, who can now get rapid answers to their questions without ever having a human involved, but also happier customer support reps, who no longer have to engage with mind-numbing, repetitive questions, and can instead turn their attention to the more complex customer queries that their human brains were built for.
Tell us how your company is contributing in the AI industry of the nation, and how the company is benefiting your clients.
We’ve been working to solve complex customer service automation problems since we were founded, and have created some very practical AI-powered solutions which are both extremely customer-friendly and that also reduce cost in the contact center.
Our AI platform automates the tasks that customer service representatives spend a significant amount of their days on. Customer service teams that use our technology can now focus their efforts and valuable time on solving those more complex queries that require a human element.
For example, KLM Royal Dutch Airlines enlisted our help to support their contact centers. As our AI platform learned from their historical records over time, it has been able to produce AI-suggested responses for KLM agents that use a deep learning algorithm that works on any channel, and in any language. With the most common questions on any subject, KLM is now able to automate those answers without a human service agent.
Another good example – this time of end-to-end automation into back-end systems – is Course Hero. 33% of all of their inbound inquiries are now supported by DigitalGenius, with half of those inquiries now resolved end-to-end, including their back-end systems, with zero agent interaction. We are seeing these numbers continue to grow as our technology learns over time.
What is your biggest USP that diﬀerentiates the company from competitors?
You’ve undoubtedly heard of Conversational AI – which focuses on producing natural and seamless conversations between humans & computers – and Robotic Process Automation (RPA), which automates mundane rules-based business processes, linking systems together to save time and cost.
DigitalGenius marries these two big concepts together into a proprietary technology of called Conversational Process Automation. This is the AI-driven integration of customer conversations with backend systems and processes into the contact center. It allows for end-to-end resolution of customer inquiries through deep learning and open APIs. We focus it on customer support organizations, who use it to understand customer intent cost-effectively, while connecting information from disparate systems to achieve agent-free resolution of their most repetitive (but expensive) tickets.
Please brief us about the products you provide to your customers, and how do they get value out of it.
DigitalGenius effectively provides one product – an AI Platform for Customer Service – which has the following three key components:
• AutoPilot, which uses conversational process automation to allow for full resolution of repetitive, expensive tickets through an end-to-end platform that connects to external systems through a robust set of APIs.
• CoPilot, which answers and provides recommendations and case intelligence to assist live customer support agents.
• And a Control Center, which provides a dashboard with AI Model management & analytics to tie it all together.
All of this is powered by the DigitalGenius AI Engine, which uses deep learning to understand and automate customer service conversations.
How is DigitalGenius helping customers deliver relevant business outcomes through adoption of the company’s technology innovations?
Some of the major measurements in the worlds of our customers are reductions that they’re looking for in average handling time; increase in customer satisfaction (referred to as CSAT); cost savings in the contact center, and a decrease in personnel/hiring costs.
One of our customers, Magoosh, augmented their customer experience with DigitalGenius and very rapidly increased efficiency. 83% of all of their tickets are now supported by DigitalGenius, with 10% of their total ticket volume now resolved end-to-end without agent involvement. This provides impressive cost savings, but also a much better customer experience.
Another client, TravelBird, had their customer satisfaction rose to 90% after implementing DigitalGenius, and their AHT (Average Handling Time) plunged by 30%. Their average agent retention even rose from 8 to 12 months, because they were now able to use AI to make their jobs easier, which allowed them more time to focus on the truly challenging customer cases.
How does your company’s strategy facilitate the transformation of an enterprise?
The cost of complex customer conversations is only going up, and the number of channels with which to reach agents is also increasing. Enterprises now serve customers via email, web forms, chatbots, phone calls, social media posts and so on – in fact, we just published a new survey that shows just how many channels the modern enterprise is using to talk to customers.
These contact centers know that their customers won’t wait for them to catch up to their rising expectations. Our objective has always been to automate the most repetitive conversations, and to seamlessly drive that automation through backend systems – which not only saves money and agent handling time, but also dramatically increases customer satisfaction – via whatever channels enterprises have deployed to their customers.
This allows customer support to no longer be seen as a cost center, but rather a profit center for the enterprise. Now that many tickets are automated in customer-friendly ways, support agents have more time for upselling products to customers; and they can give “white-glove” treatment to more people than even before, which increases customer retention. Our recent survey found that 43% of customer service leaders said that the higher their CSAT scores, the higher the revenue generated from their customers.
Do you also feel that the right kind of talent is a challenge in the industry?
Even with the increase in communications channels and the introduction of AI and machine learning into customer support ecosystems, the success or failure of a customer service organization ultimately comes down to how good its human agents are at resolving queries, and using new tools and channels effectively in order to do so.
This means that hiring and retaining strong, qualified agents is supremely important. More than half of customer service leaders (56%) say that it’s “very difficult” or “somewhat difficult” to hire qualified customer service agents. It points to a struggle to find the sort of human agents who are required to both manage the new reality of inbound, asynchronous communication from email, web forms and social tools, yet who also have the people skills and ability to think on the fly to effectively resolve tickets that start as phone calls.