How do consumers benefit from hyper-personalised technology?

Improving the experience with technology

Businesses are increasingly using machine learning and AI to assist with anything from communication to administration processes. This provides the ability to anticipate what the customer needs, and it also allows more energy to be put into addressing larger problems with automation of the more menial jobs. Allowing customer service agents to address complex, human-centric issues and provide more values-based and higher-level interactions.
 
The way marketing technology has drastically improved over the last 5 years is also indicative of how many different departments are moving towards eventually adopting AI. It’s no longer a space dominated by tech-heads. The integration of automated yet hyper-personalised marketing capabilities designed to understand behaviours for example, is a huge, unexplored sector.

Marrying technology and humanity

OFX has been on an 18 month journey to adopt these strategies and build greater capabilities to optimise the customer experience and meet their needs more effectively. The role of transferring money is more than following regulations and compliance measures, there also needs to be an understanding about the people behind the transfers.

“What I’ve learned since being here is that there’s so much emotion, and exciting and aspirational elements to why people are moving money overseas. For me it was about how we can embrace that and be much more human in the communications, but also contextual,” Chief Marketing Officer at OFX Rebecca Shears says. 

OFX is currently using ‘human intelligence’ and analytics to understand customer behaviour and timing, and by defining that logic it can deliver a better customer journey. Rather than sending communications constantly and with no direction, the focus is on making sure that the communications are relevant to the right person, when they have a need. 

“Our plan has never been to automate everything, the technology looks to scan and automate where we understand that it can add value to the customer,” Rebecca explains.

“What we’ve worked really hard to do is to understand how that technology and automation work hand in hand with outbound calling and checking in on customers.”

What can businesses do to adapt?

Context can really help to understand when a customer might have a need coming up, and how a company can assist with that to ensure a seamless experience. Michael Joo, General Manager at Datarati, a customer experience and journey agency and partner of OFX, explains how many businesses are often not focussed on the right perspective when it comes to customer experience.

 “Unfortunately, there’s still a lot of organisations now that, when you design and look at journeys and automations and experiences, if you actually deep-dive into it, they’re not focussing on the customer and what they want and need. They focus more on the company and what will drive revenue or help to expand into another market, instead of that customer-centric focus.”

 Michael also explains that for a new company to be able to adapt to the changing landscape, and to really be ready for the growth of AI is to build ‘clean’ data infrastructure and to make sure that everything is connected to customer experience. Otherwise these technologies will always require band-aid solutions, which ultimately uses more resources than it is saving. 

 “AI requires a lot of data, so it can learn through that data and figure out the best possibility - it’s a mathematical game at the end of the day,” says Michael.

 “If you think about the data we have, and everyone has a lot of data, but it’s not clean and it’s all broken. Until organisations clean up their infrastructure and their data, none of this will ever work, not correctly.”

Will AI ever replace the human experience?

The reality is that AI is more than just a tool to make people’s lives easier through automation. It’s also likely not trying to steal people’s jobs and take over the world.

For many companies, AI can take an enormous amount of data and detect trends and patterns - a job typically reserved for data scientists. In this instance, rather than being a threat, data scientists have the opportunity for more collaboration across departments.