How can AI technology deliver customer engagement?
Artificial intelligence is seeping into our lives. From asking Siri and commanding Alexa, we are adopting AI.
So how can AI technology deliver customer engagement?
We’ve written about various forms of AI before, from artificial intelligence and machine learning to cognitive computing. The team at Sabio have identified 7 specific benefits of AI within customer engagement which we’ve developed further here.
Predictive Intelligence 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. This means joining the data loops together, so that an individuals’ online behaviour is connected to their call centre profiles. A key challenge here is ensuring that the right data protection permissions have been identified and addressed.
Gartner, key analysts, predict that the number of customer interactions handled by a virtual assistant is set to grow tenfold 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. The retail store Very uses conversational virtual assistants. Customers can start a conversation in the app seeking help – a little like the Messenger chatbots. These work based on understanding key questions asked by customers and providing ready-made answers.
They’re not alone and we read how the American auto insurance company GEICO lets you speak to Kate via your app.
Like virtual assistants, conversational commerce technology is also based on an understanding of language used and questions posed by customers. In this case, the aim is to progress the sale. This has been helped by continued improvements in natural language understanding. As a result, 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.
Read about how the use of voice interaction is increasing, whether it’s Siri, Cortana, your Amazon echo, dot or Google Home.
Amazon dot
AI-enabled customer service needs to work both ways:
Understanding where and when this is necessary, and successfully managing the hand-offs between AI and human service will prove increasingly critical.
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 computing or AI is when a computer can simulate human thought processes. It involves systems and algorithms being learnt that can then recognise patterns, mine data and process natural language to mimic the brain. 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.
Share your examples of disruptive technology with us!
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