Picture this. You’re at a Gourmerican burger joint chomping a cheeseburger, when an outspoken vegan friend starts preaching that you’re killing the planet. Last week, that same vegan downed a pricey glass of pinot before their flight to a far-flung destination, armed with their strongest mossie repellant and first aid kit. Anything amiss?
Data analytics is the key to bringing personalisation back into the way brands engage customers in a digitally driven environment, IAG’s chief customer officer claims.
Speaking at the Chief Analytics Officer Forum in Sydney, the insurance group’s Julie Batch said the insurance giant is working to build out a highly granular, longitudinal view of customers using first-party data assets in order to not only understand them, but deliver a better experience.
“Gaining a longitudinal view of each customer is about taking all data assets, assembling these in one place, so teams can understand the operational, transactional and sentiment pieces of information that give us a rich tapestry of engaging with customers today,” Batch told attendees.
“These first-party data sets are unique to us. Each one of us has a huge history of how customers have interacted with our organisations. You often hear people working from their online asset or utilising third-party data assets to understand customers. While that’s of huge value, it’s not differentiated. How you use it is differentiated but in assembling it, there are lots of people putting that together and selling that to different providers to achieve the same thing, which is customer reach.
“We all have an ability to access our first-party data sets. The problem is they’re hard to get to.”
Batch noted IAG has 144 different systems of data and 18 production systems. “What we have done is worked from our first-party data assets out, in assembling information and putting it together. It was clunky and hard, but we’re now in a position where we take that data and connect it to online assets and provide a whole different level of understanding of our customers.
“What’s also critical is taking algorithms to generate insights from those assets, and then get them from the lab to the factory really fast.”
As part of its push to become customer-led and more responsive, IAG recently reorganised its operations. The new-look business has two customer-facing divisions covering sales, service, and brand and marketing execution covering consumers and business customers.
Three divisions covering customer experience, technology and operations then support IAG’s strategy. These include the Customer Lab, which Batch heads up, which is responsible for customer experience strategy and driving product innovation through data and insights, brand architecture and new business incubations and venturing.
“What we’re trying to optimise the marketing experience, but also the end-to-end experience, whether it’s the brand we present to customers, how we communicate with them before or after they become a customer, how we direct them to the right channels, how we sell and price our products and importantly, how we service them across the entire lifecycle,” she said. “That all comes back to our ability to identify and understand them.”
Batch said the first step for the Customer Lab was to combine customer attributes, such as how many products and types an individual holds with the group.
“We visualise every customer that meets that condition of interest, including those that have departed the organisation, and analyse what we did to customers shortly before they went to another organisation,” she explained.
“We study that so we can extract correlations that drive business insight. We then work with our customer experience teams and innovate new experiences to try and change how customers engage with this.”
IAG has also employed machine learning algorithms to understand the impact of deploying new products and offerings in market, allowing teams to test a massive number of opportunities at any one time, Batch said.
“We feed that back into longitudinal view and know what we can do better to engage,” she said.
Supporting these efforts are sophisticated systems of measurement systems, along with optimisation tools, she continued. A final key in using data for business differentiator is the ability to conduct experiments in market in real time to drive better outcomes that teams can pivot and learn from, Batch said.
As an example of IAG’s data analytics activities in action, Batch pointed to customer-based portfolio management. Taken by product, IAG found four segments it could study in detail: Astute shoppers, bargain hunters, VIPS, and those that love the brand and are future potentials.
“We grabbed 12 customers from each segment to understand and analyse what’s happening with each so we can design an experience around them,” Batch said. “What we found was we were losing customers that were extremely valuable to us and who held tens of thousands of dollars in policies. We’d lose that entire customer and value set on the back of one ill-informed offering or policy that didn’t consider the customer as a whole or in context of lifetime value.
“Through data, we were able to look at those customer renewals with significant policy holdings, and redesigned the way we engage with them in order to engage on lifetime value.”
A second example of data in action was in optimising the claims experience during the recent Sydney storms to process a whopping 18,000 claims received in two days. To do this, IAG created a randomised control group of about 1000 people, managed using their normal processes and practices.
The organisation then set up six cohorts of customers and treated each one of these slightly differently to see which generated the best customer and business outcomes. This included a group where IAG tried to settle claims immediately, or pushed to different operators. Batch said it then measured and tested responses to all of these.
The end result was that people who received an optimal approach and had their claims closed quickly and without debate were not only more efficient in terms of management, but also all renewed their policies and more rapidly than before.
“We normally have a 90-92 per cent renewal rate… this showed real business uplift and real speed and delivery of when to optimise the experience through data and analytics,” Batch said.
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