What You’ll Find in the Case Study
- Banking Customer Segmentation in the Industry
- Banking Customer Segmentation Challenges Faced by the Client
- Revolutionary Customer Analytics in Banking Solutions
- Broad Perspective on Banking Customer Segmentation
- Additional Solutions Offered by Quantzig
- Key-Takeaways of Customer Analytics in Banking
Banking Customer Segmentation in the Industry
Amid the economic uncertainty, banking sector companies are mainly concerned about implementing decisive steps to optimize their businesses and improve their financial performance. Also, with the recent decline in profitability, leading businesses in the banking sector are adopting new operating models and technologies to address challenges pertaining to improving customer experience and compliance.
In this sector, the consumer is the king, and in this era of heightened customer expectations and new market entrants, it becomes pivotal for the banks to stay relevant in the marketplace. To address such concerns, leading businesses in the banking sector are leveraging customer segmentation solutions.
Customer segmentation refers to proactively profiling the customers based on their preferences. Moreover, identifying the potential customers can occur through three different ways; the needs, buying characteristics, and the customer’s value. With altering consumer preferences, the banking sector needs to clearly define and target their best prospects and satisfy customers’ expectations.
Any financial objective in life must be planned to be accomplished. Every objective necessitates a series of carefully considered and carried out decisions, whether it be saving, investing, building wealth, or guaranteeing a steady stream of income after retirement. Financial planning is a very dynamic activity, which is one of its most underrated characteristics. Customers go through four stages in their financial lives: beginning, dependents, development, and retirement. The financial planning must follow the appropriate stages.
Product developers of the bank employ a variety of data, such as information on previous purchasing patterns, customer test results and feedback, commercial performance, and acceptance of the new product portfolio, to provide customers with the services they need based on their stages of life. To find combinations that can be used to provide a better portfolio, this data can be evaluated using sophisticated machine learning (ML) algorithms.
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Banking Customer Segmentation Challenges Faced by Client
A leading banking sector client wanted to understand customer characteristics to clearly segregate the customers into need-based and value-based segments. Developing a marketing strategy to target specific segments is like taking a blind shot at the target. Therefore, the client wanted to gain a deeper understanding of the company’s most profitable customers and adequately allocate its precious resources in a timely and efficient manner. The primary concern of the client was to gain a clear idea of who wanted to buy the product and gain relevant insights to improve performance against the competitors. The client was not just confined to delivering services to the customers but wanted to offer better customer support and professional services to enhance business performance.
The client wanted to gain a deeper understanding of their customers’ preferences and needs to serve them better. By collaborating with Quantzig the client wanted to identify the key differentiators by compartmentalizing their customer base into specific groups. They also wanted to group their existing customers into different categories based on geography, psychography, and behavior. By making clear customer segments they wanted to further reallocate their marketing resources and efforts to maximize the up-selling of their services and enhance the bond they already share with their customer base.
The client intended to innovate, understand, and determine the potential success of financial planning by covering all expenses and creating a portfolio in line with age and risk tolerance. The product developers wanted assistance from Quantzig to explore and streamline their objectives and goals of wealth creation. Moreover, the client struggled in providing detailed information on managing the portfolio and adopting strategies to handle various schemes.
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After attending one of our webinars, the client connected with our experts to leverage superior customer segmentation in their organization.
Revolutionary Customer Analytics in Banking Solutions
- Customer Segmentation: Companies in the banking sector, who have employed customer segmentation strategies, have realized the fact that every customer is different and should be addressed through different marketing efforts. The customer segmentation banking solution offered by Quantzig helped the client gain a deeper understanding of their customers’ preferences. The banking sector client was also able to discover the value of each segment and accordingly tailor marketing efforts toward these segments. With an aim to tap untapped market segments, the banking sector client was able to maximize cross and up-selling opportunities and encourage the customers to subscribe to more services.
- Enhancing Security: By leveraging the customer segmentation in banking solutions offered by Quantzig, the client was able to identify the customer segment with the highest potential and allocate the resources to target segments accordingly. Moreover, the client also found ways to improvise services at comparatively lower costs, which helped them to meet customer expectations at a larger scale. The payment card sector has always dealt with data security, Quantzig also helped in enhancing their payment card industry data security standard. The customer segmentation analytics solutions from Quantzig enabled the client to measure customer segments based on their preferences and requirements which helped gain a front-liner advantage. In addition, the solutions offered also helped them to determine the profit potential of every segment and analyze the probable revenue and its cost impact.
- Customized Journey Analytics Platform: In the second phase of the engagement, our analytics experts built a customized customer journey analytics platform to integrate these data sets with customer interaction history to gain better clarity into the digital customer journey. A detailed analysis of these data sets using customer journey analytics led to the discovery of actionable insights that helped identify the root cause of attrition. Quantzig’s customer journey analytics solutions also helped the client deploy dashboards for interactive data visualizations which helped them uncover the root cause of the challenges faced by them.
- Customer Insights: Our client was very interested in the ability to gain better insight into current customers. Demographics and current product ownership form the foundation of customer insight.
- Business Strategy: Customer analytics proved to be highly useful for our client in the banking services companies for product and channel development as well as economic forecasting, business improvements, risk analysis, and financial modeling.
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- Managing Customer Experience: Using customer analytics for customer experience management (CEM), we helped our client deliver personalized, contextual interactions that assist customers with their daily financial needs. Customer analytics also enabled real-time delivery of product or service offerings at the right time, thereby ensuring better customer experience.
- Risk Management: One of the more common uses of ‘big data’ today especially for banking services companies is in the area of risk and fraud management. We implemented the applications of data mining well beyond internal purchase and balanced insights. It even includes transaction patterns and social media interactions that provide a leading indicator of potential losses or fraud.
Broad Perspective on Banking Customer Segmentation
Contact center AI can help banks raise customer lifetime value and lower operating expenses while also enhancing employee happiness. Employees can concentrate on more challenging and important initiatives as technology takes on repeated iterations of consumer requests and complaints. Additionally, their workload has been reduced. The time saved might also be used by retraining these workers for the upcoming demands. As a result, employees may have stronger mid- to long-term career possibilities. In cases where extraordinary issues or service requests are not covered by the default template, the staff can supplement the AI-based contact center. As a result, soon, the banking business will be shaped by humans and AI.
The functioning of the banking industry has transformed completely with the advent of emerging technologies such as big data, artificial intelligence, and machine learning. With time, the norms have changed and so have the customer expectations from the client’s product offerings. Quantzig assisted the client by offering the appropriate technology to collect and interpret data on customer experiences with the client’s products. Our technology and solutions helped the client keep a check on the regulatory compliance and trends across global banking. This led to an increased customer base and positive word-of-mouth advocacy.
Additional Solutions Offered by Quantzig Include:
- Divided customers into measurable segments based on their needs, behaviors, and demographics
- Determined the profit potential for each customer segment
- Effectively allocated marketing resources and maximized cross and up-selling opportunities
- Improved customer service by 20% and enhanced customer loyalty and retention
- Stay ahead of competitors and incorporated new services to meet customer expectations
Key Takeaways of Customer Analytics in Banking:
- Customer Segmentation Analytics Helped a Payment Card Industry Client Achieve a 2X Increase in CSAT
- Achieved a 2X increase in customer satisfaction rate
- Improved customer retention, leading to annual growth of 45%
- Improve conversion rate by 13%