Australia and New Zealand Banking Group

Improving campaign effectiveness through a more accurate understanding of customer needs

These days, businesses no longer need a crystal ball to predict how customers will behave. With the right business intelligence solutions, large organizations can accurately forecast how customers will respond to specific communications, such as marketing campaigns. So what was once guesswork has now turned into a science.

It's a strategy that is working well for ANZ Bank. Head of Customer Analytics at ANZ Personal Financial Services, Scott Anderson, is using SAS Enterprise Miner to better identify specific groups of customers with a need for a particular product or service.

Targeting the right customers
"For example, marketers may want to determine which customers are more likely to need a mortgage," says Anderson. "Using SAS, we can then select a group of customers with a propensity to respond positively to a campaign offering a mortgage."

ANZ did indeed initiate and implement the above campaign after Anderson's team analyzed customer data for the bank's mortgages unit. The data included information on income level, residential information, transactional history, and more – all of which was used in an analysis to help the bank identify customers who were likely to take out a first home loan or an investment property.

"As we could ensure our communication was tailored to their specific needs, there was a significant increase in the number of people taking up the product offer." In fact, the response rate was 3.5 times better than that in previous campaigns that didn't use the same kind of analysis.

Improving lead times
Anderson says that the SAS solution takes subjectivity out of the equation. The selection process becomes streamlined and lead times are significantly shortened. "Before we harnessed the use of SAS Enterprise Miner, it could take us seven to 10 weeks to establish a predictive model of customers. There was more manual work involved. Now we would spend no more than three weeks on the same process."

This means that organizations like ANZ can also formulate more timely marketing campaigns and respond quicker to trends or issues which may have an impact on customers' decisions.

The solution uses multiple techniques (including decision trees, neural networks and regression models), which enable the team to determine the most effective approach for balancing targeting accuracy and business interpretation.

SAS Enterprise Miner not only enables organizations to identify and select groups of customers with a propensity for a particular product or service, it can also help organizations with attrition modeling. For example, using SAS, the bank may be able to identify those customers most likely to switch banks or cancel credit cards. As a result, a pre-emptive marketing campaign may be implemented to "save" the customer.

Enterprisewide application
The bank has also analyzed and identified appropriate customers to target in a campaign aimed at getting them to create or increase periodic payments to a savings account. "We looked at a whole range of transactional-type information to determine what was most predictive about someone wanting to increase their periodic payments," says Anderson.

"As a result we determined a series of parameters for selecting our target group of customers." With this and other factors in mind, Anderson used SAS to select a group of customers with a high propensity towards making periodic payments. "A direct marketing campaign was undertaken and the response rate was twice that of previous campaigns where there wasn't specific customer selection," he says.

Transforming the marketing landscape
Targeting customers is the first step to creating efficiencies – time, cost and resources – in the marketing process. In the past, marketers were forced to adopt a "spray-and-pray" approach, sending out masses of direct marketing and crossing their fingers for a decent response rate.

Technologies, and the right business intelligence solutions, now mean that marketing can be done with almost pinpoint accuracy. Furthermore, it also means that marketing efforts can be quantified, and the impact of specific marketing campaigns can be analyzed for their effectiveness and return on investment. As ANZ is experiencing, SAS solutions are not only significantly enhancing its marketing function, but the results are being evidenced in the bottom line.

Back to Success Stories