Optimization glossary

Feature prioritization

What is feature prioritization? 

Feature prioritization determines the importance or order in which different features or functionalities should be implemented, improved, or presented to users within a product or service. The process involves assessing the potential impact and value of each feature and making decisions based on various criteria.   

Often, product teams use product experimentation to take initiatives and prioritize which feature they want to build first. You start by running a test to evaluate different versions of a feature or content. This helps identify which feature or version of a feature a user should see so that it is potentially used more. You then put that into a targeted rule to ensure users receive a personalized experience tailored to their preferences or behaviors.   

Here are a few factors influencing feature prioritization for product teams:

  • Customer needs: Learn to assess how a particular feature affects the user experience and whether it aligns with user expectations.  
  • Business goals: Consider how each feature contributes to achieving the overall objectives of the product or service. This is how you rank features through a scoring system. 
  • Testing and data analysis: It's easy to think of ideas, but you can only know what works by testing those ideas. Set the right metrics so the data from tests and experiments will help you improve your product delivery 
  • Feasibility: Understanding resource constraints and resource availability helps evaluate the complexity and viability of implementing a feature 
  • Market trends and competition: Having a grip on the industry trends and competitor offerings ensures your product remains competitive and up-to-date.
  • Alignment: Each feature you prioritize should align with the long-term product strategy and vision.  

Feature prioritization methods 

Here are 5 scorecard methods to get you started:

  1. Rice method: It considers Reach, Impact, Confidence, and Effort to rank features based on the rice score.
  2. Kano model: It divides features based on performance and impact factors, focusing on the level of customer satisfaction each feature brings.
  3. Moscow method: The Moscow categorizes features into Must-haves, Should-haves, Could-haves, and Won't-haves, aiding in prioritization based on criticality and project constraints.
  4. Effort matrix: This value vs. effort method compares a feature's value against the complexity of building it so teams can focus on high-value, low-complexity tasks for maximum impact. 
  5. Eisenhower matrix: This scoring model analyzes and puts a feature into one of the Urgent-Important, Important-Not Urgent, Urgent-Not Important, and Not Urgent-Not Important categories. It helps to quantify effort allocation. 

The role of optimization in feature prioritization  

Think of your users first, then think of a product plan. What they want when they check out your product or list of features is fewer steps. Like:  

  • Make in-store and online navigation easy for them to find their MVP  
  • Give them relevant product or service recommendation   
  • Tailor messaging to their needs   
  • Offer them targeted promotions for the product they want     

Sometimes, it's a tiny functionality that creates an impact. Our customer Calendly uses personalization for their 20 million users. Two fun use cases:   

  • A lot of users were spending so much time going to Calendly to copy their link, which was >5 steps. Now they get to see their link right there. It takes one click to copy.    
  • Based on data, a reminder is sent to customers on how much they're using the product and what new features to use.    

Learn more about Calendly's journey   

Feature prioritization framework  

Before you go out and start building a product roadmap via a template, think of what a feature prioritization process looks like. Here’s an example:  

Step 1: Identify  

If you want to add a new feature to your product or improve on an existing one, consider running tests for story mapping to identify why you want to do so. User feedback and insights can help you understand how your feature can solve a problem experienced by mass. Use AI to augment customer research and get accurate customer feedback.  

Dropbox founder Drew Houston launched the company when already 50 startups doing data backup and storage existed in the market. He focused on why the problem is unsolved and built the right features 

Step 2: Assess impact and set criteria  

Evaluate the impact of each feature on the overall user. Establish clear criteria for prioritization, such as user value, business impact, and technical feasibility. 

When people wanted faster horses, Henry Ford understood they wanted to go from A to B faster. It is why he created automobiles, instead of focusing on training horses. When building potential features, customer satisfaction is what your development team needs to focus on.

Step 3: Decide 

Leverage diverse perspectives by fostering collaboration among key stakeholders, including product managers, developers, and designers.   

Step 4: Refine 

Regularly review and refine priorities based on changing user needs, market dynamics, and shifting business goals.  

Airbnb started with an idea to make extra bucks and rent. Now it's a billion-dollar company. 

Overall, having a product feature prioritization framework like the one above leads to a product that aligns seamlessly with user expectations and has features everyone wants to use.  

Product feature prioritization examples 

If you're wondering how to prioritize product features and deliver business value, here are a few examples.  

Example 1: Retail website 

Imagine you are a retail website, and you want to run a test to determine if the sort order of products should be new releases first, highest price point first, or lowest price point first.   

So, you run the test to learn that it can vary depending on the visitor:   

  • First-time visitors - sorted by lowest price point first increases add to cart and conversion rate    
  • Return visitors - sorted by new releases first increases add to cart and conversion rate       

You would then take these learning and make them targeted rules - for all new users, the default sort order would be the lowest price first, and for all return users, the default sort would be new releases. 

Example 2: Travel bookings platform 

Imagine you operate a travel platform where users can search and book accommodations. You want to optimize the default display of search results.   

Your options after experimentation:  

  • New users: Sorting accommodations based on the proximity to popular attractions.  
  • Returning users: Sorting accommodations by user reviews first.    

Now, for all new users, the default sort order becomes proximity to popular attractions, aiming to capture their interest quickly. For returning users, the default sort order prioritizes user reviews, recognizing their inclination towards more detailed decision-making. 

Product prioritization frameworks should focus on understanding the pain points and quantifying steps it takes to solve those challenges.

Challenges and considerations 

Staying agile and creative is where you want to be when building new products.

  • Short-term vs. long-term goals: Get quick wins, but keep your eyes on the horizon. Never forget the problem you want to solve, so know how to handle conflicting priorities. Managing stakeholder input is like herding cats. It can get messy but learn to find the sweet spot.  
  • Changing user demands: User stories and market trends are like TikTok dances - constantly changing, hard to predict, and occasionally involving unexpected challenges. Have a research process for every feature request that adapts to every change in a limited amount of time. 
  • Resource limitations: Even if you're struggling with limited resources, break down and categorize basic features into smaller, manageable tasks and prioritize them based on value. It allows for continuous delivery and quick adaptations.  

Remember...  

Feature prioritization is a key part of the feature management and product development lifecycle. But building in-house systems to manage features, often leads to complexity and delivery delays when making product decisions for your team members. This is why thousands of features are often ignored by potential users even before they get tried. 

This is especially true for mobile devices. The way out? Check out this guide on feature prioritization with feature flags and experimentation to deliver high-impact and actual customer value.