Situation
Fortis is an international financial service provider in the banking and insurance sector. With a market capitalization of EUR 39 billion, Fortis is among the twenty biggest financial institutions in Europe. Fortis is listed on the Amsterdam, Brussels and Luxembourg stock markets and has a sponsored ADR programme in the United States.

Challenge
Financial services must primarily aim for customer satisfaction. After all, various banks offer almost the same products. In the competition for customer satisfaction it is essential to know a customer’s individual needs.

"Customer retention has a greater priority than winning new customers. It is important to pay attention to your customers and to see how you can make optimum use of various contact moments. Each time a customer comes into contact with the organization it is important to draw the maximum yield from this," explains Schelbergen, senior analyst at Fortis Bank. 

Solution
Fortis Bank uses predictive analytics software to create and implement targeted direct marketing campaigns. It is able to make better target group selections by using this package. This means that clever(er) proposals can be generated that fit in better with the wishes and expectations of specific customers.

Schelbergen: "Thanks to predictive analytics software we are becoming ever more successful at putting ourselves in the shoes of the individual customer and proposing a personalized offer at the right moment."

Result

• Modeling enables the marketing team to predict the effectiveness of campaigns in advance
• Total campaign volume has been reduced by 20 percent
• Conversion rates have been increased by 50 to 75 percent

By making proposals at the time a specific topic becomes of interest to a customer, there is a high chance that he or she will use the service or product. This is only possible when predicting expected behavior is taken as the starting point.

"We have seen an increase in the conversion rate on our campaigns as customers receive more relevant and timely messages. We currently achieve conversion rates that are twice or three times higher by doing event-driven campaigns," Schelbergen continues. "Of course the important timing aspect makes the prediction particularly difficult."

Yet this is exactly where analysis software offers a solution, because it is not just a specific customer’s behavior that is examined, but also the behavior of the peer group to which a specific customer belongs. Such predictive models also work the other way around: by analyzing customer behavior, you can e.g. forecast whether someone is satisfied with their mortgage and compile a risk analysis of the likelihood that a customer is looking for a mortgage elsewhere. By offering a tailored proposal through the bank at the right moment via the right channel, you have a high chance of retaining the customer. Schelbergen: "The results speak in our favor and we are convinced that they can be even better."

Opening up new channels
Schelbergen: "More than 100.000 phone calls and emails enter our Contact Center each month. This means this Contact Center forms one of the most important sources of information relating to customer behavior and customer satisfaction. As a result of the far-reaching cooperation between Marketing and the Contact Center, we are able to test new direct marketing initiatives from the Marketing Factory directly on a small scale in the Contact Center."

Proven results
The Contact Center was originally a cost center which has since developed into a profit center. The thought that service and sales are very closely linked forms the basis for this. For example, when an operator has a customer on the phone and has performed a service transaction for him, this is an excellent moment to make the customer a personal offer that suits him. The customer does not have to call again or visit a bank office. This creates a win-win situation for the customer and the bank. The operator decides which offer should be made to which customer, supported by the tailored sales recommendations. "We’re increasingly aware of the chances predictive analytics offer and everyone is enthusiastic about the results the software is producing," Schelbergen concludes.