Which-50 and LogMeIn recently surveyed call centre managers and C-Suite executives with responsibility for the customer, asking them to nominate the technologies they believe will be most transformative.
AI & machine learning was nominated by more than three quarters of respondents, making it the top pick.
We asked Ryan Lester, Senior Director, Customer Experience Technologies at LogMeIn, to describe where the short- and longer-term impacts of AI are most likely to be felt, and also to describe the impact on contact centre agents.
Lester told Which-50 that AI is the broader umbrella and machine learning is the algorithms you build to improve the quality of your prediction.
- Download: The LogMeIn and Which-50 analyst report, Transforming the Front Line of Customer Engagement
He said brands should be very thoughtful if they are going to do machine learning themselves and invest in machine learning teams. However, he recommended that companies don’t do that.
Rather, he said there are plenty of off-the-shelf solutions that are purpose-built for contact centres or for conversion metrics.
He said, “You can buy a business application versus buying let’s say a machine learning tool or platform.”
Lester said that in the immediate term what companies can do to avoid some of the challenges around a bad investment is to use AI as their first round listening mechanism. Brands can leverage a solution built for the contact centre, and it will listen to these customer conversations over phone calls.
Then LogMeIn can see certain intents, Lester said, “So I’ll say ‘here are intents I’m seeing’. You can also take large databases. If you have chat records from the last year, you can stick those into AI tools that will start to help you identify intents.
“You can take historical data and use it as a place to say, ‘well we should go investigate further here’ and then start building more purposeful applications around those workflows”.
He said companies should build around their existing workflows. They should focus on those workflows today before they invest heavily in either a technology spend or research spend or a headcount spend.
The longer-term impact of machine learning is moving away from inbound response.
Lester said when a customer is contacting a company about a specific problem, the company should operationalise it. That means making it more efficient — so making it self-service or reducing delivery costs. They want to align the right resource to the right problem.
“Where there’s an opportunity longer-term is to think about more of the entire customer lifecycle,” he explained.
Lester said AI will help to discover what types of customers brands should be engaging with through leading indicators.
“We should start being more proactive about engagement for these types of customers with these types of attributes. If we’re seeing retention challenges on particular types of customers, we should be offering up those types of offerings to those customers.”
He believes many of the conversations are still really about inbound customer service, when in the longer term there’s going to be a much bigger opportunity around the entire customer lifecycle.
“Saying, ‘for these types of customers we acquired this way, here’s how we’re upselling them, here’s how we’re better retaining them’ and looking much more at the lifecycle and how AI is helping across that entire lifecycle.”
About this author
Athina Mallis is the editor of the Which-50 Digital Intelligence Unit of which LogMeIn is a corporate member. Members provide their insights and expertise for the benefit of the Which-5o community. Membership fees apply.