Customer Prioritization Matrix


Summary: Visuals such as charts and matrices can help practitioners base important decisions on objective, relevant criteria instead of subjective opinions.

As UX practitioners, we are often caught in a balancing act: usability improvements, tasks to be done, design ideas, personas, resources — the list goes on. The reality is that not everything can be done at once. Making an informed decision on what to prioritize can be daunting.

A prioritization matrix serves to identify the most important problems. This structured, objective approach helps achieve collaborative consensus while satisfying the varied needs of the user and business.

Effort matrix (also known as “Action Priority Matrix” or “Impact vs. Effort matrix”) is a lean prioritization approach which is useful in decision making and which helps to identify what is important (or risky) and where to direct the efforts. The matrix is used by product managers and product owners to grade strategic. Hey, iCertificationHelp Team has found the correct answer to the question According To The Prioritization Matrix, Customer Issues That Are High Impact And High Cost Should Be Prioritized: bellow is the solution to this question, and the correct answer is marked as a “Green Colour“.

Definition: A prioritization matrix is a 2D-visual that shows the relative importance of a set of items based on two weighted criteria.

The term “prioritization matrix” is used in the design thinking community to refer to a variety of prioritization techniques and representations, that, technically, do not all qualify as matrices in the mathematical sense. For the sake of consistency, we use the same term although sometimes our “matrices” would be more accurately described as “charts.” Though the manifestation of each may slightly differ, all forms help teams visualize and communicate priorities.

Prioritization charts have been used for decades in many different fields, in many different ways. Many time-management matrices are based on the Eisenhower Method, which stems from a quote attributed to Dwight D. Eisenhower: 'I have two kinds of problems, the urgent and the important. The urgent are not important, and the important are never urgent.' With this method, activities are allotted to one of four quadrants: important/urgent, important/not urgent, unimportant/urgent, and unimportant/not urgent.

Another popular tool used in science and math is a decision matrix that allows numerous options to be systematically ranked according to some criteria. In UX, we can use a similar method to collaboratively weigh options and make informed decisions that balance our time and resources with the needs of the user.

1. Establish the items, criteria, and scale you will use

There are three initial steps to creating a prioritization chart. First, establish the items you are prioritizing and write them on individual sticky notes. These can be:

  • Projects
  • Ideas
  • Features that you plan to implement
  • User groups or personas
  • Research activities

Next, you’ll define the criteria according to which you’ll perform the prioritization. For prioritizing different ideas, the criteria could be impact on the user or feasibility. For prioritizing personas, they could be percentage of user base and ROI. Regardless of what items you are prioritizing, the criteria should always be derived from the overall goals of the project and business needs.

Once you have the items and criteria, develop the scale. The scale can be as simple as high or low (if your criteria are feasibility’ or impact on the user, for example). Or, it could be made of actual numbers (if you were plotting the percentage of users, the scale could range from 0 to 100).

2. Individually vote based on expertise

Disperse different colored dots to each team member. A general rule of thumb is the number of votes per person is half the number of items being prioritized. While each team member gets the same number of votes, they should vote based only on criteria that fall within their domain of expertise. Use different colors for different areas of expertise. For example, on a matrix plotting feasibility vs. impact on the user, developers may have green dots and rank feasibility, while designers may have orange dots that represent impact on the user.

Team members then silently vote on items. Members are allowed to place multiple votes on one item. These votes should be educated opinions, so time to research or investigate prior to voting may be needed.

Note that many prioritization techniques do not include this step. However, in UX, where crossdisciplinary consensus is integral to the success of a project, we recommend you begin by voting. This step will not only speed up the process and provide structure for plotting, but it will also prevent the loudest person in the room from dominating the outcome of the exercise.

3. Draw a chart and use votes as a basis for placing items

Using the team’s votes as a guideline, collaboratively place each item onto your chart. There should be little discussion in this step. The goal is only to get the items up onto the plot based on the votes placed in the prior step.

4. Discuss and negotiate placement

Customer Prioritization Matrix

Once everything is placed onto the chart, it’s time to discuss the results and compare where items fell. Some questions to ask the team may include:

  • Are the items that received equal votes really equal? Is idea A equally feasible to idea B even though they received the same number of votes? Why or why not?
  • Do we agree with the items that ended up at the ends of the scales?
  • Why did certain items receive no votes? Was it that we didn’t have enough votes, or do they truly provide no value based on our criteria?

Throughout discussion, the team should feel free to collaboratively move items. At the end, there should be agreement on the final placement of all the items.

5. Share out and drive action

Following the plotting and discussion, the map should be documented and shared with stakeholders. The exercise should result in a clear action plan and timeline.

One of the strongest characteristics of this technique is its adaptability depending on your team’s needs and goals.

Increase the number of criteria.

One can use an arbitrary number of criteria, though visualization becomes difficult with 3 criteria and extremely hard with 4 or more. Thus, if possible, we like to stick to 2 criteria.

If more criteria are truly important, split them into pairs, as shown below, then compare the two charts. (If there’s only a single criterion, you don’t need any decision tools: just pick the option with the highest score.)

Create multiple plots to compare across criteria.

When there are more than two criteria that influence decision making, you can plot items across multiple graphs. Doing so allows the team to access multiple variables that may be important to users or to the business. For example, an idea may rank high in impact on the user and feasibility, but have very little effect on ROI.

When setting up multiple matrices, always place the best outcome on the far right or top left of your axis. This allows you to easily compare several matrices and identify the best items as those that consistently fall in the top right of your matrix.

Incorporate a more rigorous scale.

The above examples employ a simple, binary scale; however, you can use continuous scales when appropriate. For example, rather than just using a high–low scale for feasibility, you could use the estimated time for implementing a feature (e.g., 1 year vs. 2 weeks). Resources could be ranked according to a quarterly budget: $50,000 vs. $1,000.

If the outcome of the prioritization activity has significant repercussions, build additional rigor into the process. For example, have team members rank their voting dots (for example, by writing 1, 2, and 3 onto their 3 dots). When placing their votes, team members must determine the weight of each of their votes, rather than simply the top three. Thus, the outcome is not simply which items got the most votes, but which ones had the most top (1s) votes and so forth.

Items may receive ranked votes, which reflect how important they are to each voter. The ranked votes are used to determine placement onto the matrix.

Vote in private.

The process can also be adapted to meet the needs of your team. If your team’s culture is prone to group think or the HIPPO effect (highest paid person's opinion), then vote in private or digitally, rather than openly, to make the process truly democratic and prevent bias.

Apply it to life.

Prioritization charts are helpful outside of work, as well. If you are considering a new job opportunity, try plotting opportunities against the things most important to you: pay, travel, growth, or mentorship. If you are contemplating a big trip, perhaps you plot cities against what you value: weather, culture, price, food, or sights to see. In addition to better personal decisions, the extra practice will help you at work.

There are benefits from both the process of creating a prioritization chart and the tangible artifact itself:

  • Facilitate important discussions

The process of creating a prioritization matrix brings together a collaborative group to use its expertise for making an informed decision. Regardless of the outcome, the exercise promotes productive, structured conversation: the options at hand weighed against the criteria important to the business.

  • Create a shared mental model

While the process is the primary purpose of a prioritization exercise, the artifact that comes out of it is equally beneficial. The chart represents a shared visual representation of collaborative ranking and indicates a democratic process, rather than the opinions of any one individual. It is a valuable tangible artifact that documents the team history and process. Anyone can glance at the wall and understand what the team collectively agrees on.

  • Provides structure and removes emotion

Prioritization plots are a quick and easy, yet consistent, method for evaluating options. They allow teams to consistently make informed decisions regardless of the emotion or bias in the room.

Everyday decisions affect the outcome of our work. As UX practitioners, it is our job to understand the opportunities at hand and pursue those that maximize business and user benefits. We cannot risk that these decisions be arbitrary or made in a silo.

Prioritization charts give us a simple way to assess and analyze what is most impactful to the user and business, in a collaborative, disciplined way.

Learn and create prioritization matrices in our full-day course Generating Big Ideas with Design Thinking.


Brown, Tim. 2009. Change By Design. Harper Collins.

Gray, D., Brown, S. & Macanufo, J. 2010. Gamestorming – A playbook for innovators, rulebreakers and changemakers. Sebastopol, CA: O’Reilly Media, Inc.

IBM Enterprise Design Thinking Toolkit. Prioritization Grid.

Turn your feature backlog into an actionable matrix of prioritized initiatives.

In order to make the best use of your team's limited time and resources, you need to master the art of effective prioritization. Of course, that's easier said than done—looking at the big picture can be difficult when you have a large number of opportunities to choose from and a ton of stakeholders, all of whom want different things.

A matrix is a simple tool you can use to visualize each potential feature in the context of all the other potential features you could develop. If you're already managing lists of feature requests and user stories in Airtable, the latest addition to the Airtable Blocks platform—the matrix block—allows you to automatically create a prioritization matrix from your existing information.

There are many different kinds of prioritization matrices, each optimized for different purposes. Today, we'll focus on a few of the most popular types of prioritization matrices for product planning: the value-complexity matrix, the value-risk matrix, and agile user story mapping.

One of the most intuitive and straightforward methods for prioritizing your product roadmap is categorizing potential new features by their expected business value and implementation complexity.

“Business value” can include any of a number of different concepts depending on your company's overall strategic objectives: how useful a given feature will be for customers, employees, or suppliers; the ability of a new feature to generate more revenue, traffic, or publicity; or the positive impact the new feature might have on the product's performance, security, and reliability. “Implementation complexity” is a similarly broad category, encompassing how much time it will take for a feature to be implemented, how technically challenging it is to implement that feature, and how much it will cost to develop that feature—to name just a few examples.

The simplest type of value-complexity matrix is a 2x2 grid of quadrants: the value for a given project can be either low or high, and the complexity for a given project can be either low or high. To make this sort of matrix for your own team, start from a table of feature requests or potential new features, and make two single select fields for value and complexity.

If you don't already have a product planning base, you can start from our template here.

Next, add a matrix block to your base. After selecting the appropriate table and view, pick the Value field to define your rows and the Complexity field to define your columns.

If any of your records are missing values in the Value or Complexity field, they'll be mapped onto separate cells for records with empty values. This is useful for moving cards around the matrix on the fly, if you're not yet sure where a given feature falls.

High-value, low-complexity items can be considered “easy wins” or “low-hanging fruit” and should definitely be considered for your product roadmap. However, a common pitfall is to only prioritize these features, at the expense of your high-value, high-complexity features.

High-value, high-complexity items are typically larger strategic initiatives that will require a lot of effort and time—but will ultimately be worth the hard work and pay enormous dividends in the long run. One way to approach these features might be to consider whether it's possible to break them down into simpler, less complex tasks.

Client Prioritization Matrix

Low-value, low-complexity items might or might not be worth your time eventually, but definitely should not prioritized above your high-value features. You can always revisit these features in a later development cycle or consider alternate approaches that might make them higher value.

Low-value, high-complexity items should be deprioritized or reconsidered altogether.

The value-risk matrix is an alternative to the value-complexity matrix that also categorizes potential projects by their expected business value—but (as you might expect) it categorizes them by how risky they would be to implement, rather than by how complex they would be to implement.

Risk is inherent in product development: there might be uncertainty about your estimates for how long a feature might take to complete or how much it might cost, uncertainty about your team's ability to execute on the feature, or uncertainty about how much executive support a project might receive. The value-risk matrix is especially useful when you're less certain about your underlying assumptions—meaning that it's a particularly useful framework when you're building out entirely new products or initiatives.

The simplest type of value-risk matrix is a 2x2 grid of quadrants: the value for a given project can be either low or high, and the risk for a given project can be either low or high. To make this sort of matrix for your own team, start from a table of potential new features, products, opportunities, or initiatives, and make two single select fields for value and risk.

You can also make a copy of our risk-value matrix template here.

Next, add a matrix block to your base. After selecting the appropriate table and view, pick the Value field to define your rows and the Risk field to define your columns.

If any of your records are missing values in the Value or Risk field, they'll be mapped onto separate cells for records with empty values. This is useful for moving cards around the matrix on the fly, if you're not yet sure how valuable or risky a feature might be.

In general, high-value, low-risk items should be prioritized.

High-value, high-risk items should be carefully considered before investing time and effort—but at the same time, depending on your team's circumstances and risk tolerance, you might want to prioritize some of these items above some of the high-value, low-risk items.

It is often the case that high-value, high-risk items will have a much greater impact on the product as a whole than the high-value, low-risk items will. Avoiding risky items entirely might lead to a situation in which you build out a large portion of your product before ultimately hitting a wall. On the other hand, pursuing risky items can cause you to waste a ton of time developing a feature that you never end up using. Use your most careful judgment here: when and how often you should pursue high-value, high-risk items depends on the nature of your product and your team's risk tolerance.

Low-value, low-risk items might be worth your time eventually, but should prioritized below any high-value features.

Low-value, high-risk items are not a good use of your team's time and effort and should be avoided.

The previous two techniques are very much internally oriented toward the needs of your product development team. Sometimes, however, you might want to explicitly foreground the customer experience in your analysis instead. User story mapping, developed by product management consultant Jeff Patton in 2005, is one type of prioritization technique that can help you and your team seem how each potential new feature fits into the customer's experience of your product. If you're already on an agile team and comfortable with thinking about your product development in terms of “user stories” and “epics,” this technique should feel fairly intuitive.

A story map is a matrix that you can use to organize your user stories, where the X-axis is the chronological sequence of actions that a user takes as they interact with your product and the Y-axis is an assessment of how important each user story is to the user's overall experience. (If you're not familiar with the concept of user stories, they're basically brief, high-level descriptions of a user's requirements.)

To make a user story map for yourself, start with a table of user stories.

If you don't already have an agile product planning base with user stories, you can start from our template here.

Then, make a single select field called Usage Sequence with dropdown options for each of the steps in your usage sequence. For example, if your product is an online storefront, the activities in your usage sequence might include “searching for a product,” “product page,” and “checkout screen.” This field will be your matrix's X-axis—the one you use to define the columns of the matrix.

Next, make another single select field called Necessity, which you can use to assess how mission-critical each user story is. Following the MoSCoW method, you could make a single select field with dropdown options for “Must have,” “Should have,” “Could have,” and “Won't have,” or you could use a simple rating field instead. Either way, the Necessity field will be your matrix's Y-axis—the one you use to define the rows of the matrix.

Once you've done that, add a matrix block to your base. After selecting the appropriate table and view, define your rows with the Necessity field and your columns with the Usage Sequence field.

Feel free to move around user story records as necessary to build out your complete user story map.

Once you've fully mapped out your user's journey and defined different levels of necessity important they are, you can start prioritizing by moving stories between rows. Everything in the topmost row—the must-haves—represents the features necessary to create a minimum viable product that will allow the user to progress through the entire usage sequence successfully. In general, a good rule of thumb is that your releases should include a roughly evenly distributed mixture of stories from each stage in the usage sequence.

You can take this a step further by actually defining which features will be completed for which releases. Try making a table of releases, then use a linked record field to link features to releases. (Generally speaking, the must-have features should be in your earlier releases, with should-haves and could-haves coming after that.) Then, you can make a separate planning matrix in which the rows are specifically defined by the different releases, rather than by their necessity per se.

These three examples are only scratching the surface of how your team can use matrices. For example, if cash on hand is the most pressing concern for your team, you could adapt the value-complexity matrix to create a value-cost matrix instead. Your team's circumstances and goals will not only inform what should and should not be prioritized, but also how you'll determine what should and should not be prioritized: a tiny startup that needs to launch a minimum viable product as fast as possible before it runs out of money has different needs from a larger team embedded in a established company.


Ultimately, prioritization is more of an art than a science; there no objectively “correct” way to prioritize your roadmap, which is why it's vital to get stakeholders involved in your prioritization discussions. Make sure that your team is taking an active role in defining the process, rather than letting a rigid process define how your team does its work.