Financial Product Development: Leveraging Choice-Based Models for Product Feature Optimization


Let’s assume you have developed a great product that you know meets the needs of a sizable market. You’ve done your preliminary research and concept testing–assessing that the product addresses a job to be done and meets an unmet need in a way that gives you a competitive advantage. What’s next to get this product ready for market? You will want to decide on the right combination of features at the best price relative to your competitors to determine your market potential. One way to answer this question and optimize your product for launch is to conduct a survey among your target market that leverages a series of trade-offs (choices) of product features, brand influence, and price, leveraging a choice-based model such as Conjoint Analysis or Discrete Choice. The result is the ability to simulate market response to create the best product.


Financial Product Development: Leveraging Choice-Based Models for Product Feature Optimization 1


Choice-Based Models: Conjoint and Discrete Choice


Conjoint Analysis, which includes Discrete Choice, is used to understand what customers value, what features they want, price points, and other product and service aspects that can impact market success. This market research technique asks study participants to compare scenarios of features and components, choosing their preferred scenario, uncovering a derived value for each presented aspect. Trade-off exercises using choices reveal how much respondents value each attribute of the hypothetical product or service. Conjoint studies can also gather information to inform a successful pricing and go-to-market strategy for the launch or innovation. Discrete Choice is a form of Conjoint Analysis and has become a popular form of Conjoint as it allows us to look at multiple scenarios, or profiles, simultaneously and can be a more sensitive way to measure market share when considering the competition.


Benefits of Conjoint Analysis and Discrete Choice Studies

  • Understand customer preferences: Insights garnered from Conjoint analysis and Discrete Choice of preferred product features help you understand what customers value most in products or services. This assists in tailoring offerings to better meet customer needs.

  • Determine optimal pricing: Conjoint analysis and Discrete Choice can help you determine the optimal price for their products or services by understanding how customers value different features and how much they are willing to pay for them.

  • Attribute importance: Conjoint analysis and Discrete Choice insights can help you understand the relative importance of different attributes and levels of their products or services. This helps you prioritize which features to focus on when developing or improving your offering.

  • Mimic real-world trade-offs: Insights from Discrete Choice exercises allow you to simulate real-world trade-offs that customers make when choosing between different products or services. This can help you understand how customers make decisions and what trade-offs they are willing to make.

  • Market simulation: Discrete Choice can also be used to project market share and adoption of new financial products or services by simulating how customers might respond to different offerings.

Product Development and Innovation with Conjoint and Discrete Choice

For financial and fintech product and service development, Conjoint Analysis and Discrete Choice techniques can be used to uncover the insights that inform the features and attributes customers value most and that need to be included. For innovation of existing products, Conjoint Analysis and Discrete Choice can help identify opportunities for innovation by understanding where customers want improvements or changes. In addition, Conjoint Analysis and Discrete Choice can also be used to project market share and adoption of new financial products or services by simulating how customers might respond to different offerings.


Product Optimization Use Cases Leveraging Conjoint and Discrete Choice

Use cases for leveraging Conjoint and Discrete Choice for financial and fintech products range from things like consumer checking accounts, to managed advice, to credit cards and B2B payment platforms, and trading platforms, and many more scenarios where you want to determine the best combination of features, packaging, pricing, and potential share.

  • Checking account use case: To understand what features customers value most in a checking account, such as no monthly fees, overdraft protection, or rewards programs, Discrete Choice can be used to understand sensitivity around fees relative to the importance of specific features and identify the best checking account configuration for specific customer segments

  • Credit card use case: To pinpoint what drives choice when it comes to credit cards, Discrete Choice can be used to understand how customers and prospects value different rewards programs, interest rates, and fees when choosing a credit card to optimize card configuration and forecast market share.

  • B2B payment platform use case: To prioritize features for the development of B2B payment platform and understand which features will contribute the most value to the product relative to the competition, Discrete Choice is leveraged to create a market simulator that identifies the optimal combination before spending money and resources.

Integrating Conjoint Analysis and Discrete Choice Studies with Product Launch

There are many factors that influence customer behavior, and Conjoint and Discrete Choice studies are part of the toolset for any research and product development team supporting your organization’s product launch. Logica will bring its deep expertise and experience in the financial world to build a custom study to help identify as many aspects (and research methods) needed for a full insights picture. Logica works carefully with you to select the most important attributes and levels to include, as well as other research to complement the results (such as qualitative or competitive research), so that the resulting insights are accurate and actionable.

Let’s Get Started!

Ready to optimize your financial product development or innovation? Logica works with you to leverage advanced choice-based techniques such as Conjoint and Discrete Choice tailored to the financial industry so you can understand what features your customers value most, determine optimal pricing, measure potential share, and prioritize product attributes for success. Reach out today to get started.

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