What is a product launch matrix?
First, let’s get clear on what a product launch matrix is.
Also called a product process matrix, a product launch matrix is a structured framework that guides product managers through the stages of taking a product from development to market.
It outlines essential phases like:
- Planning (market research, marketing strategies, logistical preparations)
- Execution
- Post-launch evaluation (including post-launch support)
Product launch matrix vs. product decision matrix
A product launch matrix is often complemented by a product decision matrix.
Here’s the difference:
- Product launch matrix. Focuses on steps and strategies for a successful product introduction.
- Product decision matrix. Helps evaluate and prioritize different product ideas and features.
The decision matrix is a table. It’s a series of values in columns and rows. Each idea and feature is assigned a ‘weight’ or value, to help you figure out which will be best for your goals. This enables you to visually weigh up several options and make the best possible decision.
A product-specific matrix would consist of a set of viable solutions—the top features that users really want—and would be completed with other criteria or variables that help you analyze each feature.
Why do you need a product launch matrix?
Launching a product without a plan can lead to chaos and missed opportunities.
In contrast, a structured product launch helps you to:
- Maintain focus and clarity within your team.
- Reduce risks by proactively identifying and addressing challenges before they become major issues
- Ensures your product is market-ready, meets customer needs, and is supported by a robust marketing plan
A product decision matrix helps you identify features most users would find valuable in your product. It also helps you to weigh these options against each other using a set of variables to determine the most relevant feature.
With a matrix, you can eliminate guesswork from the decision-making process and help your team understand what is and isn’t a priority.
Product launch, Phase 1: Planning
1. Identify target market and market trends
The planning phase is where you lay the groundwork for a successful product launch. It starts with knowing:
- Who your ideal customers are
- What they need
- How they behave
To do this, you’ll dive into market research to identify key demographics, interests, and user pain points.
You also need to stay on top of market trends. Keeping an eye on these trends helps your product resonate with current demands and stand out in the marketplace.
2. Set clear launch goals
With your target market in mind, it’s time to set concrete objectives for your launch.
Ask yourself what you want to achieve. For example, this might involve:
- Hitting a specific sales target
- Gaining a certain number of new customers
- Establishing a strong market presence.
Well-defined goals give your launch direction and purpose.
3. Assemble the launch team and define roles
A successful product launch requires a team effort. You’ll need to assemble a group of key players who will be responsible for different aspects of the launch.
This could include marketing, sales, product development, and customer support. Clearly define each team member’s role and responsibilities to avoid overlap and confusion.
Establish regular check-ins to keep everyone on track and focused on their priorities.
4. Ensure product readiness
This stage finalizes development and conducts thorough testing. Beta testing comes after initial internal testing, but before the official launch.
During this phase, release your product to a select group of external users. These users share their thoughts on functionality, ease of use, and overall satisfaction through feedback channels like surveys or focus groups.
From there, you’ll iron out any issues and perform rigorous quality assurance checks to make sure your product meets required standards.
5. Set out your marketing strategy
A strong marketing strategy creates buzz, so your product gets the attention it deserves. The goal is to make sure your product has a ready and eager audience when it hits the market.
Your strategy should include a range of channels, such as social media, email marketing, and PR to spread the word and generate interest. Pre-launch activities might include:
- Teaser campaigns
- Sneak peeks
- Engaging with influencers or media, to help create an extra sense of excitement.
6. Prepare your sales team
Your sales team’s job is to present your product to your target customers.
A well-prepared sales team can significantly impact your product's initial success and drive early adoption. Prepare sales materials like product datasheets, presentations, and demos your team can use in their pitches.
Train your team on the product’s:
- Features
- Benefits
- Key selling points
This will ensure they’re fully equipped to talk about it with confidence.
Product launch, Phase 2: Execution
1. Prepare launch day activities
This is when all your hard work and planning comes to life. Coordination is key to ensuring that everything operates seamlessly.
Creating a detailed schedule, which outlines activities such as:
- The timing of marketing campaigns
- Product availability updates
- Any special events or announcements.
Set up a central point of contact for any issues that arise. This helps to streamline communication and resolve problems quickly. It’s also a good idea to have contingency plans in place for any unforeseen hiccups.
2. Establish effective communication with stakeholders and customers
Communicating effectively maintains each party’s confidence in the launch, and allows them to address any concerns promptly.
For stakeholders:
- Keep them updated with regular progress reports
- Communicate any significant developments.
For customers:
- Ensure that your messaging is clear and consistent
- Provide timely information about product availability
- Communicate any promotions that may convince them to give it a try.
3. Monitor and respond to initial feedback
Gathering and analyzing feedback from customers and stakeholders offers insights into how well the launch is performing. It also highlights areas for improvement.
Be sure to:
- Monitor social media
- Look at review sites
- Comb customer support channels for comments and issues
Respond quickly to feedback too. It shows you value your customers' opinions and are committed to addressing their concerns.
If you encounter common issues or questions, be prepared to provide quick solutions or updates.
Product launch, Phase 3: Post-launch analysis
1. Collect and analyze launch metrics
The first step in the post-launch phase is analyzing launch metrics.
This includes:
- Sales performance data
- Website traffic
- Conversion rates
- Other KPIs
These numbers give you a clear picture of how well your product is doing in the market.
AI tools are especially useful for this analysis. When you use a platform like Sprig, you can instantly transform feedback and behavior data into actionable product insights and the user experience.
Sprig’s AI Analysis feature unifies the most useful product opportunities into one centralized feed, with automatic summaries that highlight the top takeaways. This means you can make informed decisions and quickly act on user feedback.
2. Gather customer feedback and reviews
Reach out to your customers, such as via:
- Surveys
- Focus groups
- Feedback forms
Also, see what people are saying about your product on:
- Online reviews
- Social media platforms
- Relevant online forums.
A tool with in-product surveys, such as Sprig, enables you to capture user feedback while the user is actively engaging with your product. You can ask targeted questions, gather real-time insights, and understand the user experience as it happens.
3. Identify areas for improvement
Look for patterns or recurring issues in the feedback data. This identifies the best ways to improve your product.
- Are there common complaints or suggestions for features?
- Are there parts of the product that aren’t performing as expected?
The more data and customer feedback you can gather, the more insights you can draw, the more issues you can identify, the quicker you can address issues, and the faster you can respond to critics or users.
However, to be confident in your decision-making, you may need to gather literally hundreds or thousands of data points, including user feedback, heatmap data, and drop-off analysis.
If gathering this volume of data and taking the time needed to analyze it isn't realistic for your team, you can leverage the power of product launch tools and AI-enabled platforms to do it for you.
11 top product launch tools to understand and optimize your product
Tracking user engagement
To successfully complete a product launch, you need the right tools and resources to understand your users. These tools help you track user behavior in real-time and gather valuable feedback.
- Google Analytics. Google Analytics tracks metrics on audience demographics, traffic sources, and conversion rates. Review this information to better understand how users are interacting with your product. However, it lacks product-specific insights, and requires manual setup for detailed tracking.
- Heatmaps. Visually display user interactions with Sprig’s Heatmaps. See where users click, scroll, or spend time. This helps identify the most engaging features and highlights problem areas. By visualizing user behavior, you gain quick insights into preferences and areas needing improvement, without needing to to sift through raw data manually.
Sprig Heatmaps visually capture user in-product interactions.- Session Replays. Sprig’s Session Replay Software allows you to automate and view recorded clips of user sessions. Sprig AI Analysis can even analyze all your Heatmaps and Replays data, to identify patterns and provide actionable insights for improving your product.
- AI Recommendations. A platform that offers AI Recommendations, like Sprig, can analyze user behavior and feedback to automatically identify friction points along the customer journey. It can then generate actionable product suggestions to help you make informed tweaks and changes that will solve these pain points, and save you hours of time and work.
- AI Explorer. Further analysis of user behavior and sentiment can offer greater insights into their product experience, to boost conversion rates, and reduce friction. Sprig’s AI Explorer optimizes your product across mobile and web devices, and understands different customer personas, for better insights across users.
Sprig’s AI Explorer captures insights in your product and offers AI analysis to improve.Project management
A product launch is only as successful as the plans behind it. Project management tools help you keep your product development and launch on track. Some leading project management tools are:
- Asana. A work management platform that helps teams coordinate and prioritize their work effectively. Asana’s intuitive interface allows you to create projects, assign tasks, set deadlines, and track progress all in one place.
- Confluence. This enables you to create, share, and manage content and documents, making it easier to maintain consistency and alignment on projects. It serves as a central knowledge base where you can store project documentation, meeting notes, and team updates.
- Jira. A staple among software development teams. Jira is designed for agile project management, offering features like customizable workflows, sprint planning, and backlog prioritization.
Designing and prototyping
Create and test your product’s look and functionality before launch. Some of the leading tools can help you to visualize your product and make necessary adjustments.
- Figma. This powerful design tool is a cloud-based platform that allows multiple designers to work on the same project at the same time. With features like vector editing, prototyping, and design systems management, Figma is great for designing interfaces and creating interactive prototypes you can test with users.
- Mockflow. A suite of tools for planning and designing user interfaces. It offers wireframing, site mapping, and prototyping features, making it easy to visualize and refine your product design.
- ProtoPie. This tool makes it easy to create high-fidelity interactive prototypes. It offers advanced features like sensors and conditions to simulate real-world interactions and user experiences.
Case study: How Indeed’s ‘Product Maximization Equation’ helped launch a virtual interview platform
As a Senior Director of Product Management at recruitment platform Indeed, Nissim Lehyani helped the company adapt to the shifting needs of the many millions of job seekers who visited the platform every month, using what he calls his “Product Maximization Equation” matrix.
In a conversation with Sprig CEO Ryan Glasgow, Lehyani describes product management as the act of enabling a better path, to reduce friction between people and a valuable outcome.
Lehyani is driven by one goal: Creating frictionless products that delight users. When he was at Indeed, his commitment helped the company to build and launch products that its users loved.
For example, in 2020, the team launched a video interview platform to make hiring quicker and easier in the social distancing era. More than 20,000 U.S. job seekers were hired thanks to this feature.
Lehyani attributes much of the success of his strategy to prioritizing a user-centric approach, alongside requirements for a high-value product. He used a product decision matrix he called the “product maximization equation.”
The Product Maximization Equation
This matrix, created by Lehyani, includes the following three variables that helped him and his team identify a product’s ideal features:
- Amount of value to be delivered
- Size of the audience
- Length of time to ship
“Having the ability to prioritize and scope is crucial,” Lehyani said. “ You need to systematically identify the ideas that will deliver as much value as possible to the largest audience as possible, and as fast as possible.”
Lehyani used this exact decision matrix to create frictionless products at Indeed, and he’s done it at other organizations, too. When describing this methodology, he emphasizes that “one of the best things you can do is throw out a lot of ideas and rank them based on key variables”.
How the Product Maximization Equation works
It starts with defining the goal of your product—the problem your product solves.
Say you run a burger joint.
Your goal, of course, is to give people something delicious to snack on—a fast-food everyone would typically enjoy.
However, to achieve this goal, you’ll need to constantly listen to your customers to learn about their preferences so you can better serve them.
That’s where the second step comes in: Finding out what most of your customers consider valuable.
If you conducted some industry research, you might learn that similar burger shops are offering more variety.
Perhaps you learn from the industry that there’s an appetite for three things:
- Burgers with pineapple
- Burgers with bacon
- A new 100% vegan burger
The next step would be to use data to note the amount of value to be delivered, the size of your audience, and the length of time to ship.
Using these three variables to determine the best burger option, you can lay out your options and variables on a matrix. The former is arranged in a row and the latter in a column, and you can assign a multiplier to weigh the variables that you view as most important.
How to assign values to the Product Maximization Equation
Lehyani says that PMs should assign values based on the highest priority variables when analyzing and comparing features with one another.
For example:
- Longer speed to market would equal 1, and the shortest possible speed would equal 10.
- A low number of likely users equals 1, and a high number of users equals 10.
These values are assigned based on the importance of the variable.
To go back to the burger example:
- If most people who took a survey said bacon was the best option, assign a nine to bacon.
- And if it takes a longer time to create and serve vegan burgers quickly, assign a two or less based on the assessed speed to market.
And, to go back to Lehyani’s real-world Indeed Virtual Interview Platform example, he used the Product Maximization Equation to determine the feature that users would find the most valuable during the pandemic.
To identify the problems that users were facing, the Indeed team reached out to gather feedback firsthand. They found that users’ main challenge was attending interviews. People could still apply for jobs, but interviewing was a problem. Restrictions and health risks made securing jobs almost impossible.
Employers could no longer hold physical interviews, and job seekers couldn’t commute miles for physical interviews.
Using the maximization equation, the team found that the Virtual Interview Platform was what job seekers around the world valued the most during the pandemic. The team considered the speed to delivery, size of the audience, and perceived value, and determined that this was the feature that would maximize value.
A breakdown of the Product Maximization Equation variables
These are the steps that Lehyani and his team used to prioritize features. You can apply them to your own product, to identify and develop the most impactful solutions for your users.
- Measure the amount of value to be delivered
Measure how valuable different potential product features would be to existing and potential users. That way, you can identify opportunities to make your product more useful, increase traction and customer success, reduce churn, and increase your customers’ lifetime value.
- Measure the size of the audience
The next step is to identify how many people will benefit from using the feature. Lehyani says that the size of the audience is important. You want to deliver the maximum amount of value to the largest group of people.
Start by gathering intel. You want to collect two types of data:- Quantitative data: Numerical. Gives a clear picture of user trend and patterns. For example, do you have clear numbers of outlining total market share for a new feature? Have you conducted research amongst your existing users? Are there third party reports validating a new or existing market? Is there data surrounding the market within other industries?
- Qualitative data: Descriptive. Provides insights into the reasons behind user preferences. Have some of your users communicated that they want something different or have an interest in trying a new feature? Is there a new competitor or feature in the industry that is generating buzz? Are the forums in your community filled with dialog about a certain problem?
Once you've gathered the data, you can analyze it to determine the feature with the largest number of people that can be served (addressable market).
- Estimate time to ship
After measuring the size of the audience that would benefit from your potential new features, you also need to estimate and compare the time it would take to build and ship each potential feature.
You can estimate the amount of work a team member can do within the shortest time possible, measured in weeks and months.
To make accurate and realistic estimations, it's best to collaborate with the engineers and team leads with the knowledge you need.
A simple way to do this is to ask everyone working on a feature or product team to estimate how much time it will take to build a certain feature. From there, you can calculate the average of those estimates, to identify the value you’ll place on time in your decision matrix.
Best practices for using the product decision matrix: 5 key steps
1. Ask open-ended questions
Most PMs avoid using this feedback method because sorting through tons of feedback can be boring and time-consuming. Yet, products like Sprig AI make it easier for you to analyze each user’s feedback, and understand what features users would find most valuable.
Lehyani explained that using blank text boxes when asking for user feedback allows product teams to get open, free-flowing feedback through open-ended questions.
For example, you might ask: “What was your experience like doing XYZ?” or “What feature do you think is missing from [Product Name]?”
Sprig’s feedback templates help you to ask open-ended questions and analyze the answers.2. Share concepts with users pre-launch
Modern-day concept and prototype testing is a PM’s dream. You no longer need to get all of your users in a room and in front of a computer screen with your prototype. With a solution like Sprig, you can show users designs and mock-ups with embedded prototypes, along with video recordings that explain the concept in more detail.
As users go through this prototype demo, you can get feedback through open-ended questions via text or video responses. Then, you can quantify the rich qualitative feedback you receive to identify a score for your product maximization matrix. The Sprig Measure Product Value template, which asks users to rank the product’s value on a scale of 1 to 5, is a great starting point for gathering this type of information.
Sprig’s feedback templates make it easy to gauge user experience.3. Track user behavior in real time
A common way to get insight into what users find valuable is tracking behavior in real-time. You can also target them with experiments at critical moments in their journey. This could involve continuously observing how customers use a new feature, tracking interactions with a new button, or running an A/B test.
Tools like Sprig’s Feedback enable you to do this, capturing continuous feedback in real-time, right within your product. Its AI analysis can help identify opportunities for tweaks and powerful suggestions based on user responses, so you can optimize your product constantly, and at scale. These data-driven experiments help teams better understand what features resonate most.
For example, the Indeed team could have introduced a “conduct your interview online” button throughout their product to gauge user interest, before launching the virtual interview platform. This is a common practice amongst many startups, and is a way to conduct A/B tests among a small portion of their users.
4. Use various methods to gauge interest in your product
The qualitative and quantitative data you gather will give you a good idea of how well your product will address user needs and satisfy overall market demand. You can validate assumptions and identify key pain points using a combination of surveys (such as through a tool like Sprig Surveys), concept tests, and user behavior assessments.
You can also track industry trends and forecasts to discover new audiences for your product. These critical insights will help you make more accurate estimations about the number of people interested in a particular feature, and ensure that your product aligns with current market demands.
5. Choose a specific method for calculating time to ship
When estimating time to ship, there are two primary metrics you can use:
- Person-weeks/person-months. This technique involves estimating the total number of weeks or months over which team members will spend working on a feature.
For instance, if it takes four team members to develop a specific feature within a week, you can estimate that the project will be completed and ready to be shipped in four person-weeks. Quantifying each feature in this way makes it easier to compare each feature option, to determine which one will take the least time and resources.
- Dev weeks. Alternatively, you can use dev weeks. One dev (‘developer’) week is equal to 40 hours (eight hours a day, five days a week, one developer). So, if a feature takes two dev weeks to ship, this means it would take 80 hours to ship, if one developer is assigned to build that feature.
Whichever metric you choose, make sure everyone on your team is on the same page about the one you’ll be using. Clear communication and agreement on how you’ll measure time creates consistency in planning and expectations.
Streamline product launch decisions with real-time user insights
Having a solid prioritization framework is the best way to launch products people want, especially when you’re dealing with thousands of users daily, just as Indeed discovered. A product launch matrix outlines the steps for a successful product introduction, while a product decision matrix, like Lehyani’s Product Maximization Equation, helps you identify and evaluate the strongest ideas for a successful product launch.
By integrating real-time user insights throughout each phase, you’ll be equipped to make more informed choices, align closely with user needs, and launch products that truly resonate with your audience.