View all newsletters
Receive our newsletter - data, insights and analysis delivered to you
  1. Comment
October 17, 2022

Why Dynamic Segmentation is the Future of Retail Banking

If banks are to meet customer expectations and address the need to achieve revenue growth, current segmentation strategies need to change, argues Divya VS

Technology has changed the rules of business forever. For the banking sector, technology brought about new competition in the form of fintechs and tech giants and allowed customers to do their banking in a new way. Today, it is evident that a homogenised, static engagement and service strategy across all retail banking customers does not work.

Customers expect hyper-personalised, relationship-based, and value-driven experiences, and traditional segmentation methods cannot support customer-centric banking strategies. Dynamic, behaviour-based segmentation strategies are now crucial for retail banks to continue to establish and deepen their relationships with their customers. 

Static Segmentation Does Not Work Anymore 

Customer segmentation is an age-old strategy to segregate customers into broad groups and offer them specific products and services that they would find useful. Earlier, with the rudimentary technology available to them, banks used a range of demographic factors like age, gender, location, income, and banking business value, to segment customers.

This remained largely static as banks did not have the means to change it quickly based on changes in the customer’s lifecycle or business with the bank. Understanding of a customer’s value to the bank was also limited as most banks operated in silos with fragmented data pertaining to a customer’s relationship with it across multiple touchpoints and business lines. It goes without saying that this static segmentation approach cannot address the expectations of modern banking customers. 

Dynamic Segmentation Can Ensure Customer Centricity 

Banks now need to move to dynamic segmentation strategies. These not only consider the customer’s relationship and value across the entire 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 consider multiple factors to classify customers into smaller, unique segments. In other words, banking is now considering a dynamic ‘segment of one’ for its operational 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 a partner and advisor who understands their financial goals throughout their life and helps them achieve these to ensure financial health. A cookie cutter approach is destined to fail under these circumstances leading to customer attrition and loss of revenue.  

Furthermore, research suggests that customers are 82% more likely to renew and continue with the same bank if they feel it delivers personalisation and value. They are also 86% more likely to increase spending and 97% more likely to share positive reviews within their peer group to bring in new customers. Given these findings, banks simply cannot afford to ignore the importance of dynamic segmentation led personalisation. 

The Basics of Dynamic Segmentation 

So how can banks go about 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 the customers, enable personalization, and arrive at loyalty benefits. 

Customer components include: 

  • Consumption profile: Understand the customer’s spending habits and identify patterns;
  • Investment profile: Understand that although a customer may not be a high spender, they might have significant investments in place and they may even conduct high value transactions;
  • Diligence profile: Identify customers with outstanding payments, verify identity, assess third party information sources, and conduct due diligence processes; 
  • Portfolio profile: Identify customers who are open to trying every offering a bank has to offer. They are good candidates for cross-selling and upselling;
  • Digital profile: How a customer accesses banking services, mobile vs. internet banking;
  • Customer emotions: Understand their dreams, aspirations, and loyalties and
  • Customer life stage: Understand factors like their marital status, employment, education, age. 

For example, a customer who mostly uses online payment methods, with large investments and maintains a diligent repayment schedule, will be given more rewards and benefits than one who does not. Someone who is young and in their first job and open to trying out every offering from the bank may be considered a good prospect for upselling and cross-selling, but only if their diligence profile is exemplary. Banks can consider combinations of multiple factors to come up with personalised offerings and rewards. 

Additionally, customers can be segmented based on factors visible to the banks only (also known as that bank’s components).

The elements that banks must consider include the revenue impacting factors

For instance, a customer from a gold segment may have lost his job. During such a time, the bank can continue to keep him in the gold segment itself, keeping in mind that his risk profile has changed. This risk profile influences the financial relationship the bank has with the customer. Such commonly considered bank components include: 

  • Risk index: Analyse banking behaviour to assess the risk index of a customer and segment them accordingly; 
  • Affordability index: Assess how much customers can afford based on their assets and their spending history, and 
  • Profitability index: Establish the customer profitability metrics and understand their profitability. 

Addressing customer expectations and banks’ need for profitability

These parameters are strictly from the bank’s perspective and are weighed against the customer components to arrive at a holistic idea of the customer’s value, and potential value, to the bank. Together, these components are invaluable for banks to devise a personalisation strategy that addresses both customer expectations as well as the bank’s need for profitability and revenue growth. 

The next step is to understand that the financial needs of an individual can change throughout their life journey. With dynamic segmentation, banks can offer relevant products and services that meet their requirements at each stage.

Dynamic segmentation can also help banks quickly change the offerings they make available to the customer.

For example – smart scholar plans and pre-natal insurance schemes for children, education loans once they become teenagers, mortgage options, car loan, mutual funds, home loans when they start working, and finally health and pension plans when they approach retirement age.

This kind of vertical segmentation can help banks partner their customers through every stage of their life and establish deep and long-lasting relationships. Of course, banks must juxtapose this vertical segmentation against the financial performance, reliability, and overall relationship the customer has with the bank and change their segmentation accordingly. 

The Technology Foundation for Dynamic Segmentation

The reason why banks were not able to perform dynamic segmentation until recently is simple. The technology capabilities prevalent earlier did not allow for micro-segmentation, behavioural analysis, or dynamic changes. Banks always had the data required to fine tune and deepen their segmentation strategies but they needed the technology to break down organisational silos, consolidate the data and analyse it effectively to create microsegments and monitor it continuously.

This technology is now readily available. Banks don’t even have to touch their legacy cores to deploy 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 analyse vast volumes of data in real time to predict customer behaviour and help the bank to develop targeted offers in real time to prevent revenue loss. They can keep track of the customer’s journey and anticipate changes to their life stages so that the bank can offer them products and services that meet their requirements. 

The fight for customer share of wallet is intensifying and banks must focus on delivering the hyper-personalised and relationship-based experience that customers expect.  Dynamic segmentation is now no longer a good-to-have 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 

NEWSLETTER Sign up Tick the boxes of the newsletters you would like to receive. A weekly roundup of the latest news and analysis, sent every Wednesday. The industry's most comprehensive news and information delivered every month.
I consent to GlobalData UK Limited collecting my details provided via this form in accordance with the Privacy Policy
SUBSCRIBED

THANK YOU

Thank you for subscribing to Retail Banker International