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March 27, 2023

Methods to evaluate feature prioritization and ROI

Methods to evaluate feature prioritization and ROI

For early-stage businesses that are launching a new product, delivering the most impactful features can be the key to success. With limited resources and tight timelines, it becomes crucial for product owners to prioritize features that will deliver the best return on investment (ROI) and help the product gain traction in the market. In this blog post, we will explore different methods to evaluate feature priorities and ROI. We will provide an overview of each method, discuss their pros and cons, and offer insights on how to choose the right approach for your product development strategy.

Overview of Methods:

Value vs. Effort Matrix: The Value vs. Effort Matrix involves evaluating features based on their potential value and the effort required to implement them. Value criteria, such as revenue impact, customer impact, and strategic alignment, are defined and scored along with effort criteria, such as development time and complexity. Features are then plotted on a matrix to identify high-value, low-effort items for prioritization.

  • Pros: Provides a visual representation of features based on value and effort, helps in identifying quick wins, and supports data-driven decision-making.
  • Cons: Requires subjective scoring of value and effort criteria, may not capture all relevant factors, and can be time-consuming to maintain and update.

Cost of Delay: The Cost of Delay method quantifies the cost of delaying the implementation of a feature based on factors such as potential revenue loss, competitive advantage erosion, and customer dissatisfaction. Features with higher costs of delay are given higher priority.

  • Pros: Provides a quantitative approach to prioritize features based on their urgency and potential impact on ROI, focuses on time-sensitive factors, and helps in minimizing revenue loss.
  • Cons: Requires accurate estimation of costs of delay, may not capture all qualitative factors, and can be complex to implement.

Kano Model: The Kano Model categorizes features into different categories based on their impact on customer satisfaction. Features are classified as basic, performance, or delighters, and prioritized accordingly.

  • Pros: Considers customer satisfaction and delight as a key factor in prioritization, helps in identifying features that can differentiate the product, and provides insights into user expectations.
  • Cons: Requires in-depth understanding of customer needs and expectations, may not be suitable for all products or industries, and can be subjective in categorizing features.

User Story Mapping: User story mapping is a visual technique that helps in prioritizing features based on their alignment with user needs and product goals. User stories are mapped in a visual format to identify dependencies, prioritize features that deliver value early, and align them with business goals.

  • Pros: Provides a visual overview of user stories and their priorities, helps in identifying user-centric features, and facilitates collaboration among team members.
  • Cons: Requires careful mapping and prioritization of user stories, may not capture all business or strategic considerations, and can be time-consuming.

Impact vs. Effort Matrix: The Impact vs. Effort Matrix involves customizing value and effort criteria based on specific product and business goals. Features are evaluated and prioritized based on their impact and effort.

  • Pros: Provides flexibility in defining and scoring value and effort criteria, allows customization based on specific product context, and supports prioritization based on strategic goals.
  • Cons: Requires customization and definition of criteria, may be subjective, and can vary in effectiveness depending on the accuracy of criteria.

Decision Trees: Decision trees are a graphical representation of decision-making processes that can be used to evaluate features based on various criteria and their potential impact on ROI. Features are evaluated based on weighted criteria, and decisions are made based on the branches of the decision tree.

  • Pros: Provides a structured approach to evaluate features based on multiple criteria, allows for weighting of criteria based on their importance, and can handle complex decision-making processes.
  • Cons: Requires careful definition and weighting of criteria, may require expert knowledge to create effective decision trees, and can be time-consuming.

MoSCoW Method: The MoSCoW method categorizes features as Must have, Should have, Could have, and Won't have based on their priority and impact on business goals. Features are prioritized based on their category, with Must have features taking precedence over other categories.

  • Pros: Provides a simple and intuitive approach to prioritize features based on their priority and impact, helps in identifying essential features, and aligns with agile development principles.
  • Cons: May not capture all nuances of feature prioritization, can be subjective in categorizing features, and may not be suitable for all product contexts.


As a product owner, selecting the right method to evaluate feature priorities and ROI is crucial for making informed decisions and maximizing the value delivered by your product. Each method has its pros and cons, and the choice depends on your product, business goals, and team dynamics. It's important to consider factors such as the level of subjectivity, the accuracy of criteria, ease of implementation, and alignment with your product strategy. Experimenting with different methods and continuously refining your approach can help you prioritize features effectively and deliver the best ROI for your company.