Customer Segmentation Software – Rules Engines as a tool for enhanced targeting

Łukasz Niedośpiał
February 6, 2024
Blog

Customer segmentation stands as a pivotal component in the realm of modern marketing, directly influencing campaign success and customer engagement. As highlighted in an article by Salesmanago, businesses utilizing advanced segmentation strategies can achieve up to a 760% increase in revenue. 

At the heart of this paradigm shift is the Business Rules Engine (BRE), a revolutionary technology that refines customer segmentation by leveraging precise, rule-based algorithms.

Customer segmentation can prove useful and guarantee a dominant market position, as shown by the case of PayPal and Venmo. PayPal ventured into the payment market, recognizing a shift towards digital transactions. They targeted a niche, focusing on Millennials who sought an alternative payment method. This led to the creation of Venmo, designed for splitting bills and rideshare costs, epitomizing a strategic move towards a specific, serviceable market.

Why is customer segmentation important in insurance and finance?


Customer segmentation is a critical strategy for businesses aiming to understand and cater to diverse consumer groups. Several reports and articles from McKinsey, Deloitte, and EY highlight its importance:

EY emphasizes that effective customer segmentation is a strategic approach to growth. They illustrate how a global wealth management firm significantly benefitted from understanding client needs and developing a new digital service model through effective segmentation​​.

Another report from EY discusses the evolution of the consumer experience, moving from a transactional approach to one that builds deep, enriching relationships at every step of the customer journey. This shift requires a sophisticated understanding of consumers, which can be achieved through detailed customer segmentation​​.

Deloitte highlights the role of customer segmentation in healthcare, stating that it's essential for targeting messages, using resources efficiently, and designing personalized products and services. This approach varies depending on the type of organization and the data available. The most advanced organizations rely on segmentation as a key element of their consumer strategies​​.

Deloitte Turkey points out that customer purchasing power is increasing with technological advancements and changing market conditions. Companies need to identify customer needs accurately and provide value proposals in line with these needs. Recognizing the differences in customers' needs and expectations is crucial for effective segmentation, which in turn guides channel strategies, new product development, organization structures, pricing approaches, product portfolios, and service levels​​.

In the dynamic world of insurance and finance, understanding your customers isn't just a nice-to-have; it's a must-have. Let's dive into why customer segmentation is the game-changer these industries need.

The Magic of Data Mining in Understanding Customers

Gone are the days of one-size-fits-all financial services. Studies like those by Namvar, Gholamian, and KhakAbi (2010) have shown how data mining, particularly K-Means clustering, can be a goldmine for customer insights. By clustering customers based on behaviors and transaction data, financial institutions can tailor their services to meet the specific needs of different customer groups.

Note that with Business Rules Engine implemented data could be categorized and sorted the moment it goes into your CRM. 

The Power of Predictive Analytics

Think of customer lifetime value (LTV) as a crystal ball. Researchers like Khajvand and Tarokh (2011) used LTV to segment banking customers, allowing for predictions about future customer behaviors and preferences. This level of foresight is essential for crafting strategies that resonate with each customer segment.

Personalized Customer Experiences

It's all about making each customer feel special. By segmenting customers, as seen in the work of Zadeh, Faraahi, and Mastali (2011), banks can create personalized experiences that retain existing customers and attract new ones. It's about knowing what makes each customer tick and delivering that.

The Art of Profitability and Retention

Segmentation isn't just about understanding customers; it's about keeping them. Ahuja and Medury (2011) showed how segmentation can help identify the most profitable customers, ensuring that marketing efforts are directed where they count the most.

Tackling Customer Attrition

Last but not least, customer segmentation helps combat customer churn. Studies like Goonetilleke and Caldera's (2013) demonstrate how segmenting customers based on various data points, including demographics and policy details, can help insurance companies anticipate and prevent customer attrition.

In a nutshell, customer segmentation in insurance and finance is like having a roadmap in an unknown city. It guides companies to understand who their customers are, what they want, and how best to serve them. And in an industry where customer loyalty is gold, segmentation is the compass that keeps businesses on the path to success.

The Importance of BRE in Customer Segmentation

Business Rules Engines (BRE) play a pivotal role in enhancing the efficiency and accuracy of customer segmentation. BREs automate decision-making processes based on pre-set business rules, enabling businesses to categorize their customers more effectively and swiftly. This automation is particularly valuable in identifying and responding to the diverse needs and behaviors of different customer groups. 

By implementing BREs, companies can tailor their marketing strategies and product offerings to align more closely with the specific preferences and requirements of each segment, thereby increasing customer satisfaction and business efficiency. 

The use of BREs in customer segmentation streamlines the process and ensures a high degree of precision in targeting, which is essential for businesses aiming to optimize their marketing efforts and customer engagement strategies​.

The study on customer segmentation and profiling in the insurance industry, utilizing K-Modes Clustering and Decision Tree Classifier, aligns closely with the application of Business Rules Engines (BRE) in a similar context. BREs can effectively automate and refine the customer segmentation process depicted in the study. By integrating BREs, insurance companies can systematically apply complex rules derived from the insights of data mining techniques like K-Modes Clustering and Decision Trees.

Leveraging Rules Engine for Customer Segmentation in the Insurance Industry

BREs can automate the categorization of customers into segments like “Potential High-Value Customers,” “Low Value Customers,” and “Disinterested Customers” based on predefined criteria. This automation ensures consistency and efficiency in segmentation, crucial for developing targeted marketing strategies and personalized insurance plans. The use of BREs further enhances decision-making, as seen in the study where the Decision Tree with Gini model achieved an 81.30% accuracy rate. BREs can replicate this by applying similar decision-making logic to customer data, leading to highly accurate customer profiles.

Response to Customer Needs: Tailoring Products and Maximizing Cross-Selling/Up-Selling Opportunities

In the insurance and finance sectors, responding precisely to customer needs isn't just about service; it's about strategically tailoring products. With the data-driven insights provided by Business Rules Engines (BRE), companies can now fine-tune their product offerings. This approach isn't just about meeting customer needs; it's a powerful tool for identifying cross-selling and up-selling opportunities. 

By understanding customer segments, firms can present the most relevant products, enhancing the likelihood of customers purchasing additional services. This method increases revenue and also boosts customer satisfaction, as clients receive offers that genuinely match their needs and preferences.

Benefits of Using BRE as a Customer Segmentation Tool

There are many customer segmentation tools in the market. Segmentation is now easier than ever. 

Business Rules Engines are among the best customer segmentation tools, because:

  • Automated Decision-Making – BREs streamline complex decision processes with automated, rule-based operations, enhancing efficiency and accuracy.
  • Dynamic Rule Application – They offer flexibility to swiftly adapt rules in response to changing business strategies or market conditions.
  • Integration Capabilities – BREs seamlessly integrate with existing systems (CRM, customer data platform etc.), augmenting rather than replacing them.
  • Consistent Decision Logic – These engines ensure uniform application of business rules, maintaining consistency across customer segmentation.
  • Ease of Updating Rules – BREs allow for quick and straightforward updates to business rules, accommodating regulatory changes or strategic shifts.
  • Scalability – Designed for scalability, BREs effectively handle increasing volumes of data and complex rule sets.
  • Specialization in Business Logic – BREs are specifically tailored to implement intricate business logic, making them ideal for complex segmentation scenarios.

The implementation of Business Rules Engines (BRE) in customer segmentation brings several key benefits.

Enhanced Efficiency and Accuracy 

By automating decision-making processes, BREs enable businesses to segment their customers more efficiently and accurately. This leads to more precise targeting and personalized marketing strategies, which are essential for maximizing engagement and conversion rates.

Compliance and Risk Reduction

BREs ensure that segmentation strategies comply with relevant regulations and policies, thereby reducing the risk of non-compliance penalties.

Reduction of Manual Tasks

Automation through BREs significantly reduces the need for manual intervention in the segmentation process, allowing staff to focus on more strategic tasks.

Adaptability to Market Dynamics

BREs can quickly adapt to changing market conditions, enabling businesses to respond rapidly to evolving customer needs and preferences.

Error reduction

BREs could work like Japanese factories implementing poka-yoke methods, that prevent errors from happening by making it impossible to make mistake.

Optimizing revenue

The first thing to do in your company would be to model the most profitable customers based on select criteria like personal data and behavior. Then

correctly implemented BREs can sift through customers based on these criteria. If you wanted, you can present these customers with beneficial offers to encourage them to work with you. 

Analogically, your company could avoid insuring customers that are costly. 

Conclusion

the effectiveness of customer segmentation analysis in tailoring marketing campaigns and understanding customer behavior cannot be overstated. By employing the best customer segmentation tool, businesses can delve into specific customer segments, allowing for a more nuanced approach in their marketing strategies. Regular customer segmentation analysis is essential not just for acquiring new clients, but also for customer retention, ensuring that the evolving needs and preferences of customers are consistently met. This approach ultimately leads to a deeper understanding of customer behavior, fostering the development of more effective marketing campaigns and strategies aimed at both retaining existing customers and attracting new ones. Such detailed segmentation and analysis are key to maintaining a competitive edge in today's dynamic market.

Index
Get a personalized evaluation of Higson's potential for your use case
More stories

Streamlining Payroll Management: Innovative Approaches and Technology Integration

Revolutionize payroll with innovative tech! Explore cloud solutions, automation, AI, and rule engines like Higson for accuracy and efficiency.

READ MORE

Optimizing Supply Chain Decisions: Rule Engines for Enhanced Inventory Management

Integrate rule engines, data analytics & IoT for optimized inventory management. Leverage real-time insights for automated decision-making to enhance efficiency.

READ MORE

Enhancing Fraud Detection in Banking with Rule-Based Decision Engines

Enhance your fraud detection with the combination of machine learning, AI, and rules engines. Save your money and protect your clients efficiently.

READ MORE