Technology has changed the rules of business forever. For the banking sector, technology has spawned new competition in the form of fintechs and tech giants and allowed customers to bank in a new way. Today, it is clear that a static and homogenized strategy of service and participation among all retail banking customers does not work.
Customers expect hyper-personalized, relationship-based and value-driven experiences, and traditional segmentation methods cannot support customer-centric banking strategies. Behavioral and dynamic segmentation strategies are now crucial for retail banks to continue to establish and deepen their relationships with their customers.
Static targeting no longer works
Customer segmentation is an old strategy to segregate customers into broad groups and offer them specific products and services that would be useful to them. Previously, with the rudimentary technology available to them, banks used a variety of demographic factors such as age, gender, location, income, and banking business value to segment customers.
This remained largely static as banks did not have the means to quickly change it based on changes in the customer life cycle or the business with the bank. Understanding a customer’s value to the bank was also limited, as most banks operated in silos with fragmented data related to a customer’s relationship with them across multiple touchpoints and lines of business. It goes without saying that this static segmentation approach cannot meet the expectations of modern banking customers.
Dynamic segmentation can ensure customer service
Banks now need to move to dynamic segmentation strategies. These not only consider customer relationship and value across the ecosystem, but also consider changes in their life journey that may impact their evolving financial needs.
Dynamic segmentation is a more nuanced approach that divides customers into micro-segments that considers multiple factors to classify customers into smaller unique segments. In other words, banking is now considering a dynamic ‘segment of one’ for its operating and engagement strategies. This is now crucial as customers no longer see banks as a mere provider of financial services.
They expect their banks to be partners and advisors who understand their financial goals throughout their lives and help them achieve them to ensure financial health. A cookie-cutter approach is bound to fail under these circumstances, leading to customer attrition and lost revenue.
Additionally, research suggests that customers are 82% more likely to renew and continue with the same bank if they feel it offers personalization and value. They are also 86% more likely to increase spend and 97% more likely to share positive reviews within their peer group to attract new customers. Given these findings, banks simply cannot afford to ignore the importance of personalization based on dynamic targeting.
The Basics of Dynamic Segmentation
So how can banks apply their dynamic segmentation approach?
Banks can segment customers based on factors visible to customers (also known as customer components). These factors are used to design and recommend products and services to customers, enable customization, and earn loyalty benefits.
Client components include:
- Consumption Profile: Understand customer spending habits and identify patterns;
- Investment Profile – Understand that even if a client doesn’t spend much, they may have significant investments and even high-value transactions;
- Diligence profile: identify clients with pending payments, verify identity, evaluate third-party information sources and perform due diligence processes;
- Portfolio Profile: Identify customers who are open to trying all the offerings a bank has to offer. They are good candidates for cross-selling and up-selling;
- Digital profile: How a customer accesses banking services, mobile banking vs. Internet;
- Customer emotions: understanding their dreams, aspirations and loyalties and
- Customer Life Stage: Understand factors such as their marital status, employment, education, age.
For example, a customer who primarily uses online payment methods, invests heavily, and maintains a diligent payment schedule will reap more rewards and benefits than one who doesn’t. Someone who is young and in his first job and open to trying all the bank’s offerings may be considered a good prospect for upselling and cross-selling, but only if his diligence profile is exemplary. Banks may consider combinations of multiple factors to create personalized offers and rewards.
Additionally, customers can be segmented based on factors visible only to banks (also known as components of that bank).
Items that banks should consider include factors that impact revenue
For example, a customer in a gold segment may have lost their job. During that time, the bank can continue to keep you in the gold segment, taking into account that your risk profile has changed. This risk profile influences the financial relationship that the bank has with the customer. Such commonly considered banking components include:
- Risk index: Analyze banking behavior to assess the risk index of a client and segment it accordingly;
- Affordability Ratio: Assess how much customers can afford based on their assets and spending history, and
- Profitability ratio: Establish customer profitability metrics and understand their profitability.
Address customer expectations and banks’ need for profitability
These metrics are strictly from the bank’s perspective and are compared to customer components to arrive at a holistic picture of customer value and potential value to the bank. Together, these components are invaluable as banks design a personalization strategy that addresses both customer expectations and the bank’s need to increase profitability and revenue.
The next step is to understand that a person’s financial needs can change throughout their life. With dynamic segmentation, banks can offer relevant products and services that meet your requirements at every stage.
Dynamic segmentation can also help banks quickly change the offerings they make available to customers.
For example: smart school plans and prenatal insurance schemes for children, education loans once they become teenagers, mortgage options, car loans, mutual funds, home loans when they start working, and finally, retirement plans. health and pension when they approach retirement age.
This type of vertical segmentation can help banks partner with customers at every stage of their lives and build deep, lasting relationships. Of course, banks must juxtapose this vertical segmentation with financial performance, reliability, and the overall relationship the customer has with the bank, and change their segmentation accordingly.
The technological basis for dynamic segmentation
The reason banks were unable to perform dynamic segmentation until recently is simple. Previously predominant technology capabilities did not allow for micro-segmentation, behavioral analysis, or dynamic changes. Banks have always had the data to refine and deepen their segmentation strategies, but they needed the technology to break down organizational silos, consolidate the data, and effectively analyze it to create micro-segments and continuously monitor it.
This technology is already available. Banks don’t even have to touch their legacy cores to implement these platforms. They can simply work with third-party vendors who can provide robust cloud-native platforms that can sit on top of the legacy core and help implement dynamic segmentation. These solutions can analyze large volumes of data in real time to predict customer behavior and help the bank develop targeted offers in real time to prevent lost revenue. They can track the customer journey and anticipate changes in their life stages so that the bank can offer them products and services that meet their requirements.
The fight for the customer’s share of the wallet is intensifying and banks must focus on delivering the hyper-personalized, relationship-based experience that customers expect. Dynamic segmentation is no longer a good strategy, but one that is crucial for customer retention and revenue growth in an increasingly competitive market.
Divya VS is a Senior Architect at SunTec
