7 Key AI Technologies that Can Deliver Customer Engagement Benefits Today
- 12.04.2017 07:30 am
For those organisations that still see Artificial Intelligence (AI) as an emerging technology that they probably don’t have to start thinking about yet, customer contact technology specialist Sabio has a wake-up call: AI is here already and busy powering many of the best practice customer journeys.
To help businesses take advantage of the opportunities enabled by AI, Sabio has identified ‘7 key AI technologies that can deliver customer engagement benefits today’. Deployed correctly, these technologies are available to support all aspects of the customer journey, from understanding customers and simplifying processes through to eliminating bad demand and freeing agents to respond to customers directly.
“Given all the inevitable hype around AI – particularly around the rise in robotics and jobs destruction – it’s hardly surprising that for many businesses there’s still some caution,” explained Daniel Whaley, Principal Solutions Manager for Digital at Sabio. “However, rather than seeing AI as a potential threat to activities, organisations need to recognise the potential power of AI in
supporting all aspects of customer engagement.” “Analyst firm Gartner has already predicted that by 2020 some 85% of customer touch points will be offered without human assistance, however 2020 really isn’t that far away and we’re finding that a growing number of organisations are keen to find out how they can take advantage of AI and machine learning within their own operations,” he
Sabio’s 7 Key AI Technologies that can deliver customer engagement benefits today: Predictive Intelligence Technology – Allows organisations to take advantage of machine intelligence to improve the customer experience. This is achieved by bridging the gap between digital channels and contact centres and providing contact centre agents with immediate insight into a caller’s related website activity both before and during calls. Virtual Assistant Solutions – With analyst firm Gartner predicting that the number of customer interactions handled by a virtual assistant is set to grow 10x over the next three years, there’s clearly going to be increased demand for conversational virtual assistants.
This technology can optimise the experience offered based on where customers are in their journey and their individual preferences. Conversational Commerce Technology - With continued improvements in natural language understanding, voice control is on its way to becoming ubiquitous, particularly as research suggests that customers prefer automated interactions where they can speak directly to an AI-enabled assistant or a chatbot. However, for successful conversational experiences, organisations also need to have access to the right IVR, natural language, UX and customer journey design skills.
Human-Assisted Service – AI-enabled customer service needs to work both ways: recognising both when a human agent is needed to help the customer, and also when an agent might benefit from some additional support. Understanding where and when this is necessary, and successfully managing the hand-offs between AI and human service will
prove increasingly critical.Speech Analytics - The latest speech analytics solutions take advantage of real-time analysis and machine learning to deliver contextual guidance. This has the potential to alter the outcome of interactions while a caller is still on the line.
Cognitive Artificial Intelligence – By applying the Big Data captured in millions of customer conversations, organisations can use machine learning techniques to look beyond their most common engagement scenarios to leverage the more complex ‘long tail’ contact reasons that until now have been too difficult to automate. Voice Biometrics – Biometrics technology has been using neural nets for a long time to provide organisations with a more natural, effortless way of authenticating customers securely by allowing them to use their voice as their password. New facial recognition technology is also now being paired with voice biometrics to broaden the scope of AI-enabled authentication solutions.