Banks, armed with large amounts of customer and transaction data, are deploying predictive techniques in an effort to deliver better customer experiences at scale.
While the value of data driven modelling is well understood, executing it without “personal and business bias” in a way that predicts customer behaviour remains a challenge, according to the report titled The Shift to Predictive Engagement from Which-50’s Investigates Unit. But it is one Australian organisations are quickly taking up, the report says.
- Download Which-50 Investigates – The Shift to Predictive Engagement. Produced in partnership with Genesys
Predictive engagement, defined in the report as “the result of modelling solutions based on historical and real-time data to predict customer journey outcomes” allows organisations to anticipate customer journeys rather than reacting when the moment has passed. And, crucially, advanced technology like AI and machine learning provides decision makers with hard data.
According to the report, which cites Gartner figures, the predictive engagement software market will reach $US1.88 billion by 2022, with a 20.6 per cent CAGR from 2017. But in Australia organisations are taking a measured approach to predictive engagement, cautious of its resource requirements, ethical considerations and a local skills chasm.
- Read More: Cover Story: Which-50 Investigates: Mastering Predictive Analytics Will Enable Predictive Engagement
- Read More: A peek into the future – Identifying the benefits of predictive engagement
Early movers include the financial services industry. The Commonwealth Bank has employed a “next best conversion strategy”, arming marketers and contact centres with realtime data insights and AI tools.
The Investigates report, quotes Karen Ganschow, a lecturer at the Macquarie Graduate School of Management, and previously a senior marketer at some of Australia’s best known banking brands.
During her time at NAB, Ganschow says the bank was indeed moving towards predictive engagement.
“Customer data and analytics are used to ensure the customer is taken through the appropriate steps and communications for their needs, and ideally not to generate interventions and communications that are not relevant for the individual customer,” Ganschow said.
“If you are only reacting, you are usually too late to have great effect.
“Predictive tools allow you to intervene with customer events that precede the final step of a customer finally deciding to take their business elsewhere.”
Predictive engagement can provide the early signs a customer is questioning their relationship with a brand, according to Ganschow, providing organisations with a vital head start.
“It helps you see the preceding events that start to make a customer question so you can intervene before they have committed to taking their business away.”
Ganschow cautions predictive engagement is “not a silver bullet” and should be seen as a complementary piece in a marketing or support strategy. Still, predictive engagement does increase “the likelihood of positive outcomes”, she says.
According to the report, that advantage can be further leveraged to help drive a culture and infrastructure of “unbiased data-driven decision making [that] is foundational to ongoing sustainable business success”.