Fueling Exceptional CX in Banking: Applying Customer Engagement Engine
Financial services leaders responsible for customer experience (CX) can learn from Commonwealth Bank of Autralia’s example of dynamic customer engagement. This is a strategy built on real-time analysis of millions of data points to identify and suggest the next best conversation for individual customers and their unique needs.
Rather than relying on the customer and employee judgment, CBA created a dynamic decisioning engine that sits across all its channels. This customer engagement engine (CEE), an example of dynamic customer engagement (DCE), recommends over 2,000 types of next best conversations tailored to individual customers’ needs and context, creating a connected and relevant experience for the customer regardless of channel.
The Customer Engagement Engine – A Connected Experience
The CEE is a dynamic decisioning engine that sits across all of CBA’s channels (see Figure 1). It leverages real-time analysis of millions of data points, including transaction data, demographic data, channel behavior, and contact history, to predict the most relevant actions for individual customers. By directing these actions to the most appropriate channel for each situation, the bank creates a seamless and personalized CX, regardless of channel.
How the Engine Works in Practice
The CEE recommends over 2,000 types of interactions tailored to individual customers' needs and context. Some interactions are suggested to CBA employees, who can make personalized offers or recommend specific actions to the customer. For example, when specific criteria are met, contact center representatives receive alerts suggesting that customers switch to higher-yield savings accounts. (see Figure 2).
Additionally, the engine proactively pushes interactions directly to customers via self-service channels. Examples include alerting customers about recurring fee increases, providing instructions on enrolling in rebates or benefits, and notifying customers about incomplete applications. This proactive approach streamlines the customer service experience and improves overall customer satisfaction.
A Unique Channel/Interaction Strategy
The CEE's channel strategy sets it apart from typical omnichannel approaches. (see Figure 3). Omnichannel strategies allow for a 360-degree view of the customer and can share information across channels, but they do not have the ability to manage the experience across cohesively.
A system with a central decisioning engine like the CEE allows organizations to orchestrate the customer journey based on the customer’s and company’s desired outcome, regardless of channel. This creates a better customer experience because instead of receiving any number of potentially relevant interactions, customers receive the best possible interaction for their needs, at the right time, in the most appropriate channel.
Rightsized Initial Investment
To kickstart a similar automation strategy, service leaders should consider the following:
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Employee-Identified Initiatives
Leverage analog processes to identify interactions to program.
Service organizations can find valuable interactions for automation by tapping into their high-performing employee’s knowledge. Observing and interviewing these employees allows organizations to quickly identify value-enhancing activities that lead to positive customer outcomes. By automating and scaling these successful activities, organizations can improve customer experience effectively.
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We hope this edition provides valuable insights into applying data analysis to create a CEE strategy to enhance CX in financial services. Stay tuned for more from CMC Global newsletter!
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