Data analytics, artificial intelligence and machine learning are reshaping the travel industry, both operationally and in terms of customer experience, according to speakers at The Future of Travel, an international travel technology summit organised by Enterprise Ireland.
What these technologies offer travel companies is an opportunity to create customer engagement with “real time, in the moment relevance”, delegates heard.
In the experience economy, customers expect no less, said panellist Oisin Hurley, chief technology officer at Swrve.
AI improving customer experience
The Irish company uses AI and machine learning to hone engaging customer interactions for its customers’ customers.
Hurley was participating in a high-level panel discussion exploring the ways in which ‘deep tech’ is shaping customer experiences and expectations. It included moderator Mark Lenehan, head of air and rail propositions at Travelport Digital, John Burnes, founder of Ai Collaborator and Paul Buckley, head of social media at Aer Lingus.
At Aer Lingus, the former Irish national carrier now transforming itself into to a travel hub for the North American and European markets, social media is leveraged not just for engaging with customers but for gleaning insights, emerging trends and threat identification, said Paul Buckley.
For start-ups in this space, the key to winning enterprise customers is to move past the technology and instead articulate the solution, said Byrnes. Ai Collaborator, his business, provides a complex matchmaking service between AI innovators and industries, including travel, with pain points in need of solving. “If it doesn’t resonate with the buyer, they won’t buy,” he said.
It’s not about the technology, it’s about the effect on the customer and on the business, agreed Buckley, cautioning that any new solution must work alongside the existing technologies deployed in an enterprise.
Integration enables holistic view of travel customer
Aer Lingus already licensed a tool that integrated all its social channels into one place and provided good analytics, before it more began working with Irish personalisation platform Boxever, which uses data and AI to improve customer interactions.
The integration of the two tools gives Aer Lingus’s customer service agents a much more “holistic” view of the customer they are speaking to, when responding to questions, he said.
“Having those two platforms working together creates a synergy, something that we never envisaged when we went out and got the two services in the first instance, and that inherently makes both of those two service providers more sticky,” said Buckley.
Marketing and customer engagement company Swrve helps leading brands scale their communications to millions of customers in real time. It does this by capturing, processing and segmenting billions of simultaneous data streams across apps, devices, channels, clouds and enterprise systems, to deliver engagements with greater customer relevance.
Start-ups must find use cases asap
For start-ups looking to follow in its success and sell into the travel sector, the key is to find a use case as early as possible, agreed Oisin Hurley, its CTO. “Get in the door and solve one problem into a cocked hat, delivering it completely,” he said, acknowledging that, at enterprise level, that is easier said than done.
It helps to pick a champion within the organisation “and make it your job to get that champion promoted,” he said.
Once in, further use cases will arise. Your role then is to “engineer them as quickly as you possibly can, to develop the level of stickiness you want.”
Beware silos. “Silos are always the enemy. If you are putting up another order of business in front of people who are already using one set of tools, and yours looks different, is different, requires a different log in or isn’t integrated with the other system, then it’s kind of dying on the vine,” said Hurley. “So be thoughtful and try to find out where your solution is going to fit.”
Lead with problem solving
When selling, don’t lead with the technology – no one cares how cutting edge it is. Lead with the problem you are solving, he said.
For example, Aer Lingus wasn’t looking for a new AI technology, it simply needed to identify possible issues early and AI technology provided the solution.
“Anything that happens, happens early on Twitter,” said Paul Buckley. If something happens at an airport where it doesn’t have direct staff but relies on ground handling agents that work for a number of airlines, Twitter can be invaluable in letting them know about incidents that might impact on its business.
It uses social listening tool SAM, which sends early stage alerts to Aer Lingus staff members. “I’ve no idea what SAM does or how they do it, but they do it well to make sure we’re aware of certain situations,” he said.
As a member of a business angel network, John Byrnes pointed to a travel solution he has backed that has installed tablet devices in 10,000 hotel rooms in North America. These create a “command and control” centre for guests, through which they can order room service, notify housekeeping or control room temperature.
Machine learning suggests optimal time to buy
Machine learning recognition technology sitting underneath the application identifies if the guest is in town for business, in which case it might suggest good lunch spots, or for leisure, when it will suggest fun activities, “so guests can use the concierge service in a very personalised way,” he said.
Predicting the optimal timing for such suggestions is also increasingly possible, delegates heard, with statistical probability used to identify times when consumers are most likely to be receptive to information, or most likely predisposed to buying something.
Machine learning and AI are increasingly adept at identifying consumers’ propensity to buy just as they “start to come down that curve,” said Oisin Hurley. This provides businesses with the optimum time to promote a product or service in a way that allows them to “catch people casually”, he said. “Put something in front of them and they may purchase.”
The constraints facing the area include data privacy regulations, particularly as you move across geographies, delegates heard, as well as an inability to harmonise with existing customer technologies.
Loosening out corporate purse strings is always an uphill struggle too.
“It’s about prioritisation. Something really needs to be on the agenda in order to get the resources required,” said Paul Buckley.
Aer Lingus uses extensive guest surveys to identify pain points for customers. It feeds responses in to generate a ‘heat map’ that helps determines the ease of implementation and the benefit of any solution.
The greater the ‘heat’, the greater the chance a solution will secure investment.
Chat bots is one area of AI he predicts will grow quickly. “I’m a firm believer that it can make a big difference in customer experience and I see that developing rapidly over the rest of this year and next,” said Buckley, admitting there is a conflict between what the customer values and the airline’s ability to be efficient and reduce costs.
“To a certain extent there is a trade off between the human approach and the efficient and streamlined service a chat bot can offer, but there is a sweet spot in the middle,” he said.
The creation of a seamless handover between the two is something the airline is working on right now.