Product Feature Prioritization

  • Value vs. effort
  • RICE
  • KANO
  • Story mapping
  • The MoSCoW method

1. Value vs. Effort

Take your list of features and activities and quantify them using value and effort scores as part of this straightforward method for prioritizing.

Pros of using value vs. effort

  • What constitutes value or effort is flexible. For some organizations, Value and effort definitions are open-ended. An effort may just refer to a development effort for certain firms, whereas implementation costs may be included. Any type of organization, sector or product may leverage a flexible priority system.
  • It works well for alignment. Product teams can decide which efforts are more important than others by pushing teams to quantify and rate features numerically. It excludes hazy assumptions and guesswork from the priority conversations.
  • In organizations with highly constrained resources, something as straightforward as a value vs. effort analysis enables teams to concentrate exclusively on the issues that will have the most influence on their business and product goals.
  • Because it doesn’t employ any complicated formulae or models, it is simple to use. All that is needed is an agreed-upon figure that is added to a single overall total.

Cons of using value vs. effort

  • It’s a game of estimating and guesswork, like any other prioritizing exercise. This gives the individuals conducting the estimation a lot of leeway for cognitive bias. The final score for each feature might be overstated or understated.
  • Disagreements might be difficult to settle when it comes time for product and development to vote on how high or low the value/effort scores should be.
  • It might be challenging to utilize for big teams that manage several product lines, components, and product teams.


RICE enables product teams to focus on the efforts most likely to have an impact on any given goal.

  • The effect of innate biases on prioritizing is lessened. The focus of prioritization changes from attempting to predict success to quantifying the level of assertion that each team member has for the features by including a confidence dimension in the calculations. By doing this, the discussion of features’ relative importance shifts from “Here is how much this feature is worth” to “Here is how we are quantifying our level of confidence for each of these qualitative, speculative scores.”
  • Before quantifying them, product teams must make their product metrics SMART. As can be seen in the parameter for the Reach score, SMART stands for specific, measurable, achievable, relevant, and time-based.
  • Dependencies are not considered in RICE scores. Product teams should view the RICE score as a tool rather than the final say in what should be built next because there are times when an initiative with a high RICE score needs to be deprioritized in favor of something else.
  • Estimates are never entirely accurate. RICE prioritization is merely a method for quantifying features while taking into account the level of assurance that teams have in their estimations.

3. Kano Model

On the horizontal axis, you have the implementation values (to what degree a customer need is met). These values can be classified into three buckets:

  • Must-haves or basic features
    Customers won’t even think to look at your product as a potential solution to their issue if it lacks these features.
  • Performance features
    Customer satisfaction will increase as investment in these increases.
  • Delighters or excitement features:
    These features are pleasant surprises that customers don’t anticipate, but which, when offered, produce a delighted response.
  • Teams can learn from the Kano model questionnaire not to overestimate exciting features and to stop underestimating necessities.
  • It can assist teams in making better product decisions and predictions about the market’s acceptance of particular features and the needs of your target market.
  • It can take a while to complete the Kano questionnaire. You need to conduct a number of surveys that are proportionate to the number of customers you have in order to get an accurate representation of all of your customers.
  • It’s possible that customers might not fully understand the features you’re surveying them about.

4. Story Mapping

This product prioritizing framework’s simplicity is one of its greatest strengths. Additionally, it shifts the emphasis from internal team and stakeholder viewpoints to the user’s experience.

  • It helps identify your MVP very quickly.
  • The experiences of the users are at the core.
  • Story mapping is a group activity that involves the whole team.
  • It ignores factors affecting external product prioritization, such as complexity and business value.

5. The MoSCoW method

By grouping features into four priority buckets, the MoSCoW method enables you to determine what matters most to your stakeholders and customers. The acronym MoSCoW, which stands for “Must-Have, Should-Have, Could-Have, and Won’t-Have features,” has nothing to do with the city.

  • To access their account, users MUST log in, for instance.
  • Users SHOULD have the option to reset their password, for instance.
  • “Our app allows users to save their work directly to the cloud.”
  • It’s great for involving stakeholders with non-technical backgrounds in the process of prioritizing products.
  • A quick, simple, and intuitive way to let the team and customers know what the priorities are.
  • Helps with resource allocation thanks to the categorization of the features
  • Tends to cause teams to overstate the number of Must-have features
  • It’s more of a release criteria exercise than a prioritization technique.

To summarize

Since I tried to concentrate on those that I have used more extensively, there are more techniques and frameworks than are given in this quick review. Overall, it’s not a good idea to completely substitute human input in decision-making with product prioritizing techniques, as their purpose is to serve as a blueprint or a structure when thinking about priorities. A strong framework can help everyone understand the bigger picture and the objectives for the final output. Prioritization techniques include weighing the various options that can be considered in relation to a particular feature or concept.



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Alex Borisenko

Alex Borisenko


Creating tools to improve readers’ efficiency and student productivity. Writing about reading, technology, and product management.