A leading Australian motor insurer was looking to improve engagement on its website and broader digital ecosystem through real-time personalisation of their customer experiences.
For their first use case, the insurer used AI/ML to tailor motor insurance policy defaults for their customers. This use case is enabled by their new personalisation platform Atmosphere, and the insurer will continue to scale-up usage across its digital ecosystem.
Client Challenge
For prospective customers, choosing and tailoring a motor insurance policy can be complex and time-consuming, with variables such as excess, payment frequency and policy valuation to consider.
In recognition of these challenges, the insurer wanted to automate and personalise various customer experience touchpoints in order to optimise conversion, satisfaction, and retention.
As a further challenge, as the insurer is unable to send consumer data to the public cloud for privacy reasons, they challenged Ambiata to create a personalisation engine that could be deployed on-premise.
What is Atmosphere?
- Atmosphere is a personalisation platform that helps organisations build ethical next-best-action solutions
- The system learns continuously from customer responses using closed-loop machine learning that adapts automatically
The Solution
In response, Ambiata developed ‘Atmosphere’, a personalisation platform that helps organisations build ethical next-best-action solutions. The platform can be used to enable a wide range of use cases across various areas such engagement, conversion and satisfaction. It was deployed on-premises to meet the required corporate data compliance standards.
For customers, when a motor quote is initiated, an algorithm within Atmosphere uses the details they enter from the quote, along with any previously held data about the customer, and presents one of the various policy options based on their likely preferences. In this first iteration, the algorithm is configured to optimise for quote conversion in order to produce an overall lift in digital conversion rates.
This use case is powered by a contextual bandit algorithm which observes the input details of the customer, recommends an option and then observes whether the action was successful. In this way, it learns continuously from customer responses using closed-loop machine learning and automatically adapts.
Business Impact
The Atmosphere platform has proven to be a success at scaling personalised services through automation. This represents a major capability uplift which enables internal analytics teams to deploy ML models and embed algorithms throughout the customer experience.
Within 6 months of the motor quote personalisation implementation, the use case had achieved an 11% increase in conversion rates and a 5% increase in comprehensive car revenue, when compared with a baseline group. This translates to an increase in millions of dollars in gross written premium (GWP) per year.
“Ambiata were central to enabling our AI journey. They helped us harness the power of AI by implementing personalised recommendations, which delivered tangible improvements for both our customers and business performance”,
Danielle Handley, EGM
Customer Experience, IAG
Business Outcomes
