Outside of regulatory compliance, the biggest challenge facing financial services firms is the competition for customers.
An article from the Banking Administration Institute (BAI) validated this trend, citing “removing friction from the customer journey” as a key objective of banks for 2016. Big data analytics provide FSIs the means to maximize their customer relationships.
Building a stronger customer base and a more effective customer journey requires a three-pronged approach for financial services firms:
Big data analytics plays a critical role in each phase of this lifecycle. Let’s explore how.
As outlined above, the customer acquisition battle is fought on three fronts: better targeting, increasing conversion and optimizing spend. Companies can apply big data analytics in all three areas through:
With big data customer insights, financial institutions have the power to craft customized messages, reach the right audiences and lower their costs. This can be done by adding more data around demographics, behavior and social media, and by applying rich analytic functions to identify attribute clusters, map conversion paths and pinpoint behavior patterns.
Financial service customers will undergo a journey with their firms — ideally a long-term one. To maximize the lifetime value of a customer, institutions need to continuously engage in three key ways: understand how products are used, watch how digital services are used and put forth compelling cross-sell and up-sell offers.
With big data analytics, firms can:
Generate deeper insights by adding more data to engagement analytics such as transactions, mobile service logs and richer demographics. Advanced analytics can identify use patterns, zoom in on mobile experiences and recommend offers for customers.
Engagement is only one part of maximizing the lifetime value of a customer. The second variable in that equation is customer retention. There are three aspects firms explore to retain customers: maintain a high quality service experience, spot at-risk customers and provide effective retention offers. Big data analytics assists for all three by:
The addition of more data, such as call center, product and ATM logs, as well as demographic data, allows big data analytics to dig deeper into the service experience. Through the use of sophisticated analytics, companies can discover the details of service experience problems, uncover patterns that lead to churn and correlate offers with outcomes.
Until recently, customer acquisition, engagement and retention strategies were primarily built based on basic descriptive analytics and gut instincts. To win the battle for customers, financial institutions must leverage big data analytics to master these strategies.
Once they harness the power of data and adopt a more proactive and personalized marketing strategy, the results will follow.
A newly released Datameer solution brief, “Cultivating Customer Relationships Big Data Financial Services“, provides more detail on how big data and modern BI platforms can be used by financial institutions to build stronger, more profitable relationships with their customers.