Life’s full of choices!​⁠ From picking the perfect outfit for a date to agonizing over career paths, each decision shapes our lives. This is equally true in business, where every choice, from marketing strategies to product features, can make or break success.

Take app development, for instance.​⁠ Imagine a brand new music streaming app. Let’s call it Streamify. Customers seem happy, but reviews mention difficulty finding healthy options. Should they build a complex filter system, highlight healthy restaurants, or partner with local health food stores? Each option has its pros and cons.

This is where feature prioritization frameworks come in.​⁠ These frameworks act as a compass, guiding businesses through this maze of choices by analyzing features based on factors like customer demand, development effort, and potential impact. From the MoSCoW method to the RICE framework, there are powerful tools to help you make informed decisions.

Ready to navigate the exciting world of feature prioritization? Let’s dive in!

The Feature Prioritization Landscape

Streamify has several features that they’re interested in incorporating into the application. Which do they build first? Feature prioritization frameworks help with the decision-making process. There are several of these frameworks, each serving specific needs and suiting specific contexts.

In the realm of software development, there is almost never a “one-size-fits-all” approach. Each software is unique, having a unique user base, demands, and business goals. A framework that suits one might not be right for another.

For instance, you may prefer to leverage the MoSCoW or Kano Model, both of which simply differentiate between essential features and nice-to-haves. On the other hand, sophisticated frameworks like RICE, Weighted Scoring, and Value vs. Complexity suit more complex environments.

Each framework comes with its own strengths and weaknesses. To pick the right one, you need a deep understanding of your objective, audience, and product. In this blog, we take you through various frameworks to improve comprehension and help you make the right choice for your needs.

Which Feature Prioritization Framework Should You Use?

Here are a few popular frameworks that Streamify could consider:

Let’s get into it below.

RICE Scoring

The RICE framework (or Reach, Impact, Confidence, and Effort framework) evaluates the software based on four aspects.

  • Reach (number of users the feature reaches per month): High, as many users listen to music regularly
  • Impact (impact the feature has on conversion): Medium, as it may boost user engagement/retention
  • Confidence (confidence product managers have in the feature: Medium, as data on user preferences might be limited initially
  • Effort (the time a feature requires from the team): High, as it requires complex algorithms and data analysis

Once you have all these scores, you multiply the scores of R-I-C, and divide it by E. That’s your RICE Score: (High * Medium * Medium) / High = Medium

Value vs Effort

In this kind of scoring, you take the list of considered features and weigh their value against the effort needed. While using this framework, use as much data as possible to back up your estimation. Additionally, you can consult your application development services provider – the professionals are likely to have valuable inputs, to make the entire process easier and quicker.

Consider a feature for Streamify, the option to download songs for offline listening. How do you determine the Value of the feature? Ask:

  • What value does it hold in terms of revenue generation?
  • What will be its benefit to current and potential customers?
  • How will it impact business goals?

In our example, Value is High as users often request it for travel or limited internet.

Determine the Effort required by asking:

  • What is the monetary cost of development, and can we afford it?
  • How complex is it to build this feature?

In our example, Effort is Medium as it requires server storage and integration with playback functionality)

The aim should be to prioritize those features that hold more value and can be created with less effort.

MoSCoW Method

The MoSCoW Method stands for features that are Must have (Mo), Should have (S), Could have (Co), and Won’t have (W).

In this framework, features are prioritized based on immediate business value. Similarly, other features are deprioritized and dropped if resources are limited or deadlines are close at hand.

  • Must-Have: Features that are essential for the product to be functional, such as basic music playback functionality (play, pause, skip).
  • Should-Have: Features that are important but not time-sensitive, such as search for songs, artists, and albums.
  • Could-Have: Bonus features that would enhance user experience, such as personalized playlists or curated radio stations.
  • Won’t-Have: Features that are not really needed, and can be held over, such as social media integration, and music video streaming (can be added later based on user feedback).

Kano Model

Developed by Japanese professor Noriako Kano in 1984, the Kano Model tests features for their customer satisfaction ranking. In other words, Kano verifies how useful a feature is to the customer, and how satisfied the customer is with it. It measures these two parameters against each other, on the vertical and horizontal axes: functionality and satisfaction.

Kano also classifies features into five categories:

  • Must-have features: Without these, customers wouldn’t even consider the product, like high-quality audio streaming and the ability to create and manage playlists.
  • Performance features: These simplify app usage and boost customer satisfaction, such as song lyrics display, seamless playback across devices.
  • Excitement features: These surprise or bonus features generate customer delight, like personalized song recommendations, and integration with fitness trackers.
  • Indifferent: These features don’t impact customer value in any way, such as an add-on game which is not strictly connected to the core music streaming
  • Reverse: These features should be removed, as they cause customer dissatisfaction, like mandatory customer verification and login to access personalized content.

Kano is more structured, and results in better market predictions and product decisions; however, it can be time-consuming.

Weighted Scoring

Weighted Scoring involves prioritizing features using a scoring system and predefined criteria. The team then calculates the weighted average to determine which feature to prioritize.

Give a weightage to each criterion – the total weightage should be 100%. If each raw score is out of 10, the sum of all weighted scores also gives you a final score out of 10.

A feature with a weighted score of 3.8 out of 10 might be a lower priority. You could also consider criteria like Customer Engagement, User Experience, and more.

Weighting the score becomes easier when you implement automation or use a visualization tool to visualize. Ask your application development services provider for suggestions.

User Story Mapping

User story mapping emphasizes recognizing the user journey through the product. This allows teams to see the product from the user’s point of view.

As you define and study these stages, you understand which can be simplified and improved. You can then rank these tasks based on priority and improve them through the right new features.

For example, consider this epic (large functionality within Streamify): Enhancing Music Discovery

It is built on several user stories (specific features), as below:

  • User Story 1: Implement personalized playlists based on listening history.
  • User Story 2: Introduce curated radio stations by genre or mood.
  • User Story 3 (later): Integrate with music review platforms for recommendations.

By using these frameworks with different strengths and perspectives, you can make informed decisions about which features to prioritize for your music streaming app.

Choosing The Right Framework

Take certain factors into consideration to pick the right prioritization framework.

Project Type (Agile vs. Waterfall)

First, consider the product development approach you’re using. For Agile, you can choose a relatively light framework like MoSCoW or User Story Mapping. Frameworks for Waterfall need to be more comprehensive, and you could choose the Weighted Scoring technique.

Team Size and Experience

Next, consider your team and team size. Those with small teams and less experience should go for frameworks like RICE; more experienced and larger teams can pick up models like Kano.

Availability of Customer Data

You should also consider the amount of data you have. With rich customer data, you can rely on frameworks like Kano Model or User Story Mapping. With limited customer data, choose the RICE or Value vs. Effort.

Quantitative vs Qualitative Analysis

Quantitative analysis involves numbers and answers questions related to “How”. For example, “How many users visited the page last month?

Qualitative data focuses on insights and answers questions related to “Why”. For example, “Why did people visit this page often?

Putting The Framework Into Action

Once you have considered all the factors, including relevant stakeholder inputs, choose the right prioritization framework.

To keep the process as transparent as possible, communicate clearly with all partners. Accept their feedback and make sure that feature prioritization aligns with business objectives.

While feature prioritization frameworks provide a valuable structure, you should also consider other factors to make an informed decision.

  • Market trends
  • Competitor analysis
  • Realistic timelines for development
  • Long-term product vision

In short, use your chosen framework as a tool for decision-making; don’t make it a replacement for informed judgment. By maintaining a balance, you can harness the power of the framework and your own lived business sense, to fuel strategic thinking.

A feature prioritization framework is not a one-time implementation event; rather, it’s an ongoing process where you evaluate, adapt and evolve. Based on the progress of the project, customer data availability, and the current scenario, you can use a feature prioritization framework to ensure that your development efforts remain aligned with user needs and organization goals.

Remember that a framework only provides guidance along the way. To gain success, you must embrace strategic decision-making, ensure collaboration, and maintain transparency.

At Ziffity, we’ve had a strong track record providing feature prioritization to our clients. Through this service, we help you further improve the return on investment on application development.

Rely on Ziffity for software product engineering services and beyond. We act as an integral part of your team to comprehend your product and work with you to ensure timely and apt feature prioritization. We understand your product and business objectives and, with the help of the right framework, help you make wise decisions to optimize feature availability.