One year ago, I looked at the promotion track reports of bank cards in my office, frowning. Prior to these track reports, my bank had launched several promotions, such as offering a special dinner in a high-end restaurant, a sales discount at an online travel agency, and more. However, these promotions attracted few customers. The track reports were so dismal that everyone was disappointed. We had made great efforts to negotiate with business partners and had invested heavily in advertising across multiple channels. However the profits were far too low to offset the costs. We asked ourselves what happened. Why didn’t the customers buy the products/services? And what are their true demands?
I felt like a clueless novice when I faced a mass of consumption transactional data. And I realized that retail banking should imminently engage precision marketing leveraged by data analysis. The business model is waiting for a change as the world of information is changing. That’s why I decided to leave my former position as a product manager after dedicating myself to retail banking for more than five years. That’s why I’m back on campus to learn business analytics.
Business analytics can deliver a clear interpretation of data, from which we can understand customer behaviors, meet their demands and even predict their demands. That’s Big Data, a collection of information that knows more about you than you do yourself!
I’d like to lead you into a fascinating world of big data to show you on how business analytics influences marketing strategies in retail banking.
1. Know your customer
Business analytics can integrate information from social media into a more comprehensive customer profile that includes the data of demographics, consumption capacity, risk appetite and customer behavior. The reviews from social media such as Facebook and Twitter become some of the most important data used to compile an integrated customer profile.
For example, can you consider a man a loyal customer if he has never called the service hotline to complain? Bankers can’t determine the answer before obtaining more information from social media because it is now possible for this customer to leave a complaint on social media. Customers are changing their behaviors, and more and more, they prefer to make comments on social media rather than in traditional ways. Therefore, bankers need to change the methods of observation in order to address changes in customer behavior. Knowing your customer better is the foundation of precision marketing and customer relationship management.
2. Precision Marketing
It’s a marketing principle that suggests successful marketing retains, cross-sells and up-sells existing customers. Precision marketing will increase the possibility of purchase, control advertising costs and improve the customer’s loyalty. Here are three aspects I like to emphasize:
Real-Time Marketing
Implement real-time target marketing based on the latest consumption transactional data.
For example, when a customer buys a pregnancy test, bankers can predict the probability of pregnancy by data modeling and then recommend a set of pregnancy suppliers, such as clothing retailers, medical insurers, hospitals and diaper services on a timetable.
Personalized Recommendation
Position the customers based on age, assets, wealth-management preference and risk appetite.
Analyze the potential demands for financial services and products.
Target customer segments, recommending and designing personalized products with different terms and interest rates; for example, term deposits (for those who prefer low-risk options), wealth management (for those with moderate-risk tolerance) and stocks (for those with high-risk tolerance).
Customer Life-Cycle Management
Obtain new customers, avoid customer attrition and win back lost customers.
A sophisticated predictive analytics model can identify the churning customers. The customer attrition rate will decrease if bankers focus on the potential defectors and launch special marketing programs, such as wealth-management products with higher interest rates to appeal to these defectors.
3. Risk Control
Identify fraudulent trading and money laundering in real time.
For instance, a bank can build business intelligence software that can record and manage the customer’s IP address commonly used in online transactions. If the software identifies a transaction with a different IP address or for an abnormally large sum, the software will deliver a message to the customer regarding the abnormal transaction to ensure the safety of the customer’s assets.
4. Operational Optimization
Optimization of Distributions
Banks can monitor the performances of different distributions, especially in online distributions, using business analytics. For example, banks can find out the most popular products in online banking by data analysis. To attract more customers to access online banking for more convenient service and to reduce the operational costs of a physical branch location, a bank can improve its most desirable online functions and launch differentiated products, such as higher interest rates, shorter terms on wealth-management products in online banking, based on data analysis.
Optimization of Products and Services
Using a business intelligence system, a bank can transform customer behaviors into information to help understand the customer’s characteristics and risk appetite, and to analyze and predict intelligently the customer’s demands. And then the bank can push notification by multiple channels to the target segmentation. Sales volumes will increase, and costs will decrease significantly once the products that bankers recommend to the customer match what the customer prefers.
Business analysis can be applied in every aspect of retail banking. The application of Big Data makes it possible to provide everyone a customized plan despite how big the market is. By leveraging the magic power of business analytics, we will win the hearts of customers. Big Data leads to big results.
