The 11 Essential Domains for Product Management in 2024 and Beyond
A comprehensive breakdown of a Product Manager's expertise across developing strategies, aligning teams, and capturing market share.
Product management is evolving, quickly. Successful PMs must navigate a complex ecosystem spanning innovation, multiple teams, proprietary IP, compliance, and organizational cohesion. I've developed a guide to lay out the 11 Essential Domains the greatest PMs (and the greatest founders) must seek to master to build competitive products and sustain growth. From the fundamentals of market intelligence to the complexities of commercialization and pricing strategy and the intricacies of ethical design and role management, I sought to capture the essence of multiple domains. My goal is to continue researching how the latest innovations are enhancing aspects of the many hats PMs wear. This comprehensive framework will enable you to thrive in a future where you can effectively delegate the many hats you wear across AI agents. Below, I present each domain by breaking out subdomains, competencies, and the techniques that define them, presented in tables to contextualize it all.
In this article, you'll learn:
In my piece Chaos to Clarity, I defined product management versus project management. It often gets confused in the professional and especially in the startup context. Let's review.
Product Management is about vision and strategy, the blueprint, the high level thinking behind what product to build, why it matters, and who will use it. Product managers obsess over customer pain points, market research, and feature prioritization. While, Project Management focuses on execution of the plan, while product management is focused on strategizing the plan, what the end goal is why we’re going that way in the first place. In some ways, Product Management encompasses aspects of the Project Management execution.
A product manager’s job is to:
My goal in with these "11 Essential Domains for Product Management" is to introduce Hierarchical Taxonomy Levels that contextualize it all. I split this between the following:
My rationale is as follows: This hierarchical structure should allow for the systematic organization of product management expertise, which...
By utilizing this taxonomy, we can now use a standardized lexicon to evaluate our own expertise. Since PM crosses many disciplines and is often prey to buzzword soup, standardizing these terms will prove crucial for everything from mapping your skills to maintaining consistency in hiring practices, professional development, and communication across all teams.
For the purposes of simplification, I’ll describe the Domains, Subdomains, and Competencies and save in-depth techniques for future articles, where we can explore the specific applications more.
This category focuses on understanding the market landscape and customer needs.
arket Intelligence and Customer Understanding is the foundation that will shape your decisions, from strategy to execution. Without it, you’re flying blind, making moves based on assumptions rather than insights. I’ve been there—thinking I understood the market trends, only to realize too late that I discounted the impact that macro changes were pushing back against the market. The regulatory landscape shifted beneath the team and I, and we did not sufficiently budget in our fundraising strategy to be able to pivot. It’s like setting sail without a compass—no matter how well-built your ship, veering off the trade winds could leave you stranded in the ocean. You need momentum.
Market intelligence isn’t a static process. It’s continuous and layered and requires deep dives into both external factors and customer behaviors. Trends evolve, consumer preferences shift, and competitors reposition themselves—if you’re not keeping up, you’re falling behind.
Secondary research must be utilized. You’ll need to tap into news aggregators, market round-up Substacks, get round-up newsletters, skim over podcast guests and conference vendors—oh god, and even open up Twitter and LinkedIn. Yes, platforms like Gartner and Statista give you the bird’s-eye view of your industry, laying out macro trends and big-picture dynamics—but you’re paying a hefty premium to dig deeper. Trend and narrative analysis is so critical that I will publish a follow-up digging into the big brain strategies to gauge their emergence and ongoing strength. In particular, I’ll give attention to Google Trends, Cogent InCights, Exploding Topics, Brandwatch Analytics, Semrush, Ahrefs, Treendly, and Pinterest Trends—but we’ll return to that.
Relying on secondary research alone is like reading the news—you know what’s happening but don’t see how it affects you personally or where to apply it. You’re downloading new information but not practicing it. That’s where primary research steps in. Getting into the trenches with user interviews or focus groups adds the “on-the-ground” perspective. You want to have ears inside with potential customers, giving you direct, unfiltered insights that competitors often overlook. Crucially, you’ll need to be able to ask questions in a non-leading way. You need to listen to the source, and you need to do it in a scaleable way. You’ll want to dedicate time to the most qualified sources and will need to establish a process to qualify them.
Segmentation is crucial because you can’t aim for everyone anymore—nobody has the budget or bandwidth. Think of segmentation like targeting in archery: the more precise your aim, the better your shot. Whether using demographic breakdowns, psychographic data (interests, values, attitudes, personality traits, and lifestyle choices), or behavioral analytics tools like Amplitude or Mixpanel, segmentation ensures you’re focused on the right customer segments with precision. For example, RFM analysis (Recency, Frequency, Monetary Value) digs into customer behaviors, helping you figure out who your most valuable customers are—not just on a surface level, but in a way that reveals who will spend the most or stick around the longest. Conduct RFM analysis quarterly or annually to identify at-risk customers and tailor retention strategies before launching new promotional campaigns.
Then comes the subdomain of Customer Journey Mapping, which is like plotting out the quest tree for your heroes. A customer’s journey isn’t merely buying the product—it’s about understanding their entire experience, from the moment they become aware of your brand, to the moment they consider using it, to what happens after they’ve used it, to what happens when they’re done. You need to think through those triggers, the roadblocks, where they’re delighted, and where they might fall off entirely. Techniques like Touchpoint mapping and funnel visualization help you spot pain points or gaps in the journey. Understanding where customers fall through the cracks allows you to patch those leaks before too many prospects disappear.
Competitive Analysis is a subdomain more than watching your competitors from the sidelines. It's fundamentally about dissecting their playbook. Think of it like reverse-engineering your rival’s product, you’re not just interested in what’s on the surface, but what’s under the hood. Techniques like Porter’s Five Forces, Quadrant Mapping, and the Blue Ocean Differentiation Canvas give you structured frameworks to break down their strengths, weaknesses, and strategies. The real art is finding out where they’ve left the door open. Utilize quadrant positioning maps to communicate findings to the team. Maybe their pricing model is a bit too aggressive, their messaging doesn’t quite resonate with a particular audience or their distribution efforts are missing a market segment. Exploiting those weaknesses is how you stay ahead.
This category focuses on understanding the market landscape and customer needs.
The domain of Product Strategy and Planning is where the vision for your product gets translated into an actionable roadmap. You're laying out the long-term game plan and determining how your product fits the broader market. I’ve learned that if you don’t anchor your product strategy in reality, and balance ambition with feasibility, you’ll end up chasing moonshots without ever lifting off the ground.
The subdomain for Strategic Roadmapping is your navigation chart. It’s not enough to know where you want to go; you must plot out the course and account for potential storms and obstacles. Whether you’re using OKRs (Objectives and Key Results) to set measurable goals or visualizing your milestones with Gantt charts, keeping your team aligned and moving forward is key. You may have to pivot or reprioritize large-scale efforts as new opportunities arise or unexpected challenges emerge. I’ve often found initiative backlogs in Jira, Aha!, or another OKR platform invaluable here, especially in fast-moving industries. The initiatives in this backlog aren’t just tactical tasks but more significant, strategic moves that require cross-functional coordination. They often include major projects such as entering new markets, developing new product lines, or exploring new business models. You might prioritize initiatives based on business impact, resources, or long-term alignment.
The Business Model Development subdomain is where you determine how your product will generate revenue, scale, and sustain itself. It’s like building your car's engine—you can design the sleekest vehicle on the road, but if the engine can’t deliver, you’re not going anywhere. The BMC will help break down the components of your business model, from value propositions to cost structures. As part of my own proprietary Rapid Prototyping Methodology (RPM), and from looking at that stupid blank canvas more times than I can count, I’ve developed the BMC v3.1, and will likely share it in the future.
As you develop your product positioning, remember that your customers need to see not only what your product does but also why it’s uniquely suited to them. In the RPM, the Value Proposition Canvas exercise is one of the first things you run to help you focus on clarifying why you’re doing what you’re doing, mapping customers' pains to potential gains, and positioning your product as the solution they’ve been waiting for.
But positioning is more than just product messaging. It’s about differentiation, and one of my favorite tools here is Blue Ocean Strategy. It forces you to look beyond competing on features and instead focus on creating uncontested market space. Honestly, it’s such an important tool that I decided to list it twice. You might as well build a new path through the forest if everyone else is fighting for control of the foot traffic of the same trail.
Market Entry Strategy is a subdomain that captures how you bring your product into the world and get it in front of your target audience. A strong Go-to-Market (GTM) strategy isn’t just about launching; it’s about sequencing. You must first decide which segments to target, what marketing channels to prioritize, and how to build momentum. One of the most challenging launches I managed was balancing a phased rollout while ensuring we didn’t alienate our early adopters. By rolling out features gradually and gathering feedback along the way, we could fine-tune the product before pushing it to a broader audience.
This category focuses on understanding the market landscape and customer needs.
Product Development and Execution is the fast-paced, high-stakes domain of product management. It’s where strategy meets reality and where your ability to coordinate teams, manage complexity, and execute efficiently directly impacts your product’s success. Without processes for scoping, prototyping, prioritizing, and releasing features, your product will quickly fall behind—or worse, collapse under the weight of its ambition.
Think of Product Development and Execution not as a single step but as a continuous cycle of building, testing, and iterating. Your roadmap might look clean and linear, but reality is far messier. Features must be scoped, prototypes need testing, and releases need careful planning.
One of the most critical tools in this phase is feature scoping. You're crafting a blueprint and defining each feature's exact specifications, constraints, and goals before it’s built. This is where you’ll decide what’s essential to the product’s success and what’s just a nice-to-have. It’s easy to get caught up in adding “just one more feature,” but this is where scope creep can quickly derail a project. I’ve found that using a MoSCoW prioritization framework (Must have, Should have, Could have, and Won’t have) effectively maintains focus. It helps teams make tough decisions by forcing them to categorize features based on necessity, ensuring that the most impactful ones are delivered first.
After the scope is set, the next step is wireframing and prototyping. A prototype is the first draft of your feature, a quick, interactive model that allows you to gather feedback before you invest serious development time. Whether creating a low-fidelity prototype (like a clickable wireframe) or a high-fidelity interactive mockup, this stage concerns experimentation and early validation. Prototyping saves you from the “build it and hope they come” mentality. It’s like testing a new recipe, you wouldn’t prepare the final dish for an important dinner without tasting it first. Fortunately, some of the new AI tools & plugins across Figma to the Adobe Suite are making this so much faster, and I will return to these techniques in upcoming playbooks.
Once you’ve validated your prototype, it’s time to move into full development, where feature prioritization becomes essential. You can’t build everything at once; trying to do so will spread your resources too thin. Here’s where frameworks like RICE (Reach, Impact, Confidence, and Effort) come into play. This method helps you prioritize which features to build first by considering how many users a feature will affect, its potential impact, your confidence in its success, and the effort it will take to build. It’s a balancing act—you need to get high-impact features to market quickly, but you must also be realistic about your team’s capacity. In a future article, I’ll discuss the most effective mental models for prioritization techniques.
During development, collaboration between product, design, engineering, marketing, and sales teams becomes paramount. But development is never a straight path—it’s iterative. This is where agile processes show their value.
Building a feature is only half the battle. It would be best to release it so that it doesn’t overwhelm your users or cause disruptions. This is where release planning comes in. Think of it like launching a rocket—you don’t just hit the ignition button and hope for the best. You plan the trajectory, test every system, and have contingencies for anything going wrong. A structured release strategy might involve phased rollouts or beta releases, where you release the feature to a smaller group of users before going wide. Feature flagging is a particularly useful technique here—it allows you to turn features on or off for different user segments, enabling you to test in real-time without disrupting the entire user base. LaunchDarkly or Split.io are great for managing feature flags and ensuring a smooth, controlled release.
Once the feature is live, monitoring its performance through post-launch tracking is critical. This is your feedback loop. You’ll want to track adoption rates, user engagement, and any issues that arise so you can respond quickly. Monitoring platforms like Posthog or Hotjar gives you visibility into how users interact with new features, identifying any usability issues or unexpected friction points.
I always find it essential to set up clear KPIs for new features before they launch, whether it’s the number of users adopting the feature, an increase in engagement, or a decrease in churn. Having these benchmarks in place means you’re not guessing whether the release succeeded.
This category focuses on understanding the market landscape and customer needs.
As I discussed in Scrum to PMP, Agile isn't just a buzzword that haunts your dreams—it's a mindset that nothing is ever “done.” It’s also the method that can make the difference between hitting your targets and burning out halfway through. As discussed in that article, for larger organizations or those needing to coordinate multiple teams, Scaling Frameworks like SAFe (Scaled Agile Framework) or Scrum@Scale become invaluable to synchronizing efforts.
At the heart of Agile is Sprint Planning. Think of each sprint as a tactical mission—you need clear objectives, defined resources, and the discipline to stay within scope. In sprint planning, teams take the larger strategic goals in the roadmap and break them down into actionable tasks. This is where you define the sprint goals, estimate the workload, and determine your team’s capacity. I’ve seen teams falter by underestimating this step, thinking they could wing it, but this is where velocity can tank if you’re not careful. A capacity planning session is crucial—it’s like setting a workout schedule that pushes your team but doesn’t leave them burnt out by the end of the sprint.
Once the sprint kicks off, the team rallies around Daily Standups. These meetings are the lifeblood of Agile execution—short, focused, and meant to keep everyone on the same page. Think of them as daily pit stops in a Formula 1 race, where everyone gets a quick check-in to ensure the car’s running smoothly and no one’s about to spin out of control. Whether your standups are synchronous or asynchronous (increasingly common for remote teams), the key is communicating blockers early. Remote teams often rely on tools like Loom for asynchronous standups, where team members record and share their updates at the start of the day.
Throughout the sprint, managing the Product Backlog is an ongoing task. This backlog is a living document, a prioritized list of features, bugs, and improvements that must be tackled. I’ve learned that regular backlog grooming sessions—usually at the end of each sprint—help keep things manageable. It’s like trimming a bonsai tree: you must cut away what’s unnecessary while shaping what’s essential for growth.
Regarding the broader Agile Ceremonies, the most valuable are often the Sprint Reviews and Retrospectives. These aren’t just formalities—they’re where real learning and improvement happen. The Sprint Review is your chance to demonstrate the value delivered in the sprint and gather feedback from stakeholders. It’s like a product launch on a smaller scale, giving the team a sense of accomplishment. However, it’s the Retrospective where the team grows.
Technical Requirement Gathering is the bridge between product and engineering. This step ensures that the product vision is translated into technical terms that engineers can execute. It’s not enough to say, “We need a dashboard”—you need to outline what data it displays, where that data comes from, and how the user interacts with it. User stories, functional specifications, and use case documentation are the tools for this translation process. In the early days, I made the mistake of being too vague with requirements, thinking the engineering team would “just figure it out.” Let’s just say that didn’t end well.
Agile also thrives on Quality Assurance Coordination. In Agile, testing is not a phase tacked on at the end of development; instead, it’s integrated into every sprint. This is where practices like Test-Driven Development (TDD) or Behavior-Driven Development (BDD) become crucial. By writing tests before writing the code, teams can ensure that the product works as intended.
Finally, no Agile process is complete without DevOps Integration. DevOps is the connective tissue between development and operations, ensuring that new features are deployed quickly and safely. Continuous Integration (CI) and Continuous Deployment (CD) are cornerstones of this practice—allowing teams to merge code frequently and deploy updates with minimal disruption. Using tools like Jenkins, teams can automate the entire process, reducing the risk of human error and speeding up time-to-market.
This category focuses on understanding the market landscape and customer needs.
This domain's heart lies Key Performance Indicator (KPI) Definition. KPIs are the signals that tell you whether your product is on course or veering off-track. But simply throwing up a few random metrics won’t get you anywhere. It’s about identifying the North Star metric—the key measure that aligns with your product’s ultimate goal. I like to think of it as the heartbeat of the product. For example, your North Star might be Customer Retention Rate or Monthly Recurring Revenue (MRR) if you're managing a subscription-based product. Everything else you track feeds into these critical KPIs. The challenge is making sure these KPIs are SMART (Specific, Measurable, Achievable, Relevant, Time-bound) so that the team knows exactly what they’re aiming for and so you can course-correct as needed.
Once your KPIs are set, Metrics Tracking and Analysis become the daily grind. This is where dashboards and real-time analytics come into play. Imagine having a cockpit dashboard for your product—tools like Grafana, Tableau, Looker, or Google Data Studio allow you to pull data from multiple sources, visualize trends, and react in real-time. But it’s not enough to track what’s happening; you need to analyze why it’s happening. If you notice a spike in new users, that’s great, but if retention plummets two weeks later, you need to dive into the behavioral data and funnel analysis to figure out where users are dropping off. I’ve seen teams chase vanity metrics—big Web 3.0 projects utilizing major hype and meme marketing campaigns to boost public interactions and their web traffic numbers, masking their deeper issue with engagement and retained users.
A/B Testing is a powerful competency for optimizing features by comparing two or more versions of a product element, be it the new landing page design or the onboarding flows, to see which one performs better. There are several techniques. Split testing has users randomly divided into groups, one seeing Version A and the other seeing Version B. Multivariate testing tests multiple variations simultaneously to see how different elements interact. Tracking performance is done using tools like Optimizely, VWO, or Google Optimize, which capture vital metrics such as conversion rates, click-through rates, or time spent on a page. Deciding when to replace a variation depends on statistical significance—you need enough data to ensure results aren’t due to random chance. Typically, tests should run for at least one full user cycle (at least a week or longer) to capture accurate behavior while ensuring seasonal or time-based factors are accounted for. Choosing which variations to test is driven by hypothesis—you don’t test blindly, rather, you identify specific assumptions. For example, "Will reducing form fields increase sign-ups?". Once a winner is determined, you roll out the successful version to the entire user base, using feature flags to replace the tested option easily. The key is to avoid running too many tests simultaneously, which can muddle results, and always test changes aligning with strategic goals.
Feature Adoption Tracking is the subdomain of measuring how quickly users adopt new features and how often they engage with them. Tools like Heap or Pendo allow you to track adoption curves and see which features are sticky or falling flat. If a feature doesn’t take off how you expect, you must figure out why. Is the feature hard to find? Is it intuitive enough? Maybe it’s valuable to only a subset of users. Understanding time-to-adopt metrics can guide decisions on whether to iterate, promote, or retire a feature.
Retention and Engagement Metrics are arguably the most critical indicators of a product’s health over time. Tracking metrics like Daily Active Users (DAU), Weekly Active Users (WAU), and Monthly Active Users (MAU) can help you gauge overall engagement. But don’t stop there—dive into cohort retention analysis to see how different groups of users behave over time. For example, you might find that users who signed up during a particular promotion are far less likely to stick around after their first month. That’s your signal to re-evaluate your acquisition tactics or tweak your onboarding experience.
Revenue Modeling is where product managers start to think like CFOs. It would be best to build models that estimate future revenue based on user behavior, pricing strategy, and market conditions. Scenario analysis allows you to consider best-case, worst-case, and most likely outcomes, which helps you make more informed decisions. If you’re considering switching from a usage-based to a subscription model, you can predict the potential impact on user acquisition and revenue growth. Similarly, sensitivity analysis lets you see how changes in one variable (like price) affect another (like churn rate), allowing you to fine-tune your strategy before committing to big moves.
Churn Analysis is another pillar of the data domain. You can have the most beautifully designed product worldwide, but if users keep leaving, you’re in trouble. The key is to go beyond just tracking your churn rate—you need to use tools like survival curves and predictive churn models to anticipate which users are most at risk of leaving. It’s like detecting early warning signs before the illness fully sets in. By identifying users on the verge of churning, you can intervene with targeted retention strategies—offering them a discount, reaching out with personalized support, or even tweaking the product to meet their needs better.
Calculating Customer Lifetime Value (CLV) is the holy grail of metrics because it tells you how much revenue you can expect from a customer over their entire relationship with your product. Combining the LTV(Customer Acquisition Cost) ratio with CLV gives you a clearer picture of your product’s profitability. If it costs you more to acquire a customer than that customer will bring in over their lifetime, you’ve got a problem. It’s like running a marathon only to find out the finish line is moving further away. Tools like Kissmetrics or ProfitWell can help you calculate CLV by analyzing user behavior, purchase history, and engagement trends, providing insight to adjust your pricing, retention, or acquisition strategies accordingly.
This category focuses on understanding the market landscape and customer needs.
This domain focuses on acquisition, retention, engagement, and monetization—the core pillars that ensure long-term success. This domain is about fine-tuning every aspect of the product experience to ensure your product scales, retains users and generates revenue. There’s always room for improvement, experimentation, and scaling up. With the right strategies, growth isn’t just a byproduct of success—it becomes a core feature. I’ve worked on promising products that started to falter because they didn’t adapt fast enough or failed to leverage the right growth levers. Integrating growth experiments growth through nifty tactics is crucial.
At the core of growth is Product-Led Growth (PLG)—another buzzword recruiters who think they’re hip like to use—but there’s some meat here. PLG is the strategy of letting your product’s features and functionality drive user acquisition, retention, and expansion. So, going freemium is PLG, where your users access a basic version of the product for free, and over time, you introduce premium features to capture upgrades. However, for this strategy to work, onboarding has to be paramount. Think of it as rolling out the red carpet for your users. A smooth in-product onboarding experience with interactive walkthroughs and guided tours helps users understand your product's value within minutes. Without this, even the most brilliant feature set can be lost in complexity.
Once you’ve acquired users, the next battle is retention. This is where Retention Optimization techniques come in. Cohort analysis is key here—you need to segment users based on when they joined, how they behave, and how long they stick around. By examining these cohorts, you can spot patterns in user behavior. Perhaps users who sign up after attending a webinar retain longer, or those who join via a promotional offer churn faster. Push notifications and behavioral email campaigns can be used strategically to re-engage users at risk of churn. Think of these as gentle nudges, reminding them why they signed up in the first place and pulling them back into the fold.
To keep users engaged over time, Product-Based Engagement Strategies come into play. In-app messaging is a powerful tool for delivering real-time messages that guide users, introduce new features, or encourage deeper engagement. Gamification elements—like point systems, badges, or progress bars—can motivate users to interact more frequently, making the product feel rewarding. But don’t overdo it—gamification only works if it aligns with your users’ goals. Overcomplicating the game will backfire, especially if there are no meaningful rewards. The DeFi/NFT gaming/DAO Tooling ecosystems have been ripe for platform & community-based experimentation in game design, and in future articles, I’ll share some insights.
Monetization Techniques go beyond simply setting price tags. It would be best to consider what pricing model makes the most sense for your users and business goals. Usage-based pricing, for instance, allows users to pay based on how much they use a service—common in SaaS products. Tiered pricing offers multiple service levels, allowing users to choose based on their needs and budget, while dynamic pricing adjusts based on demand. When determining pricing models, consider running pricing experiments to see how different segments of users respond to changes in price.
PLG Retargeting is your secret weapon for recapturing users who have engaged with your product but haven’t converted into paying customers. Retargeting campaigns can remind these users of your product's value at the right time. I’ve found that retargeting combined with customer segmentation yields the best results. You can target users based on their engagement level, sending those who dropped off after sign-up a different message than those who engaged with a feature but didn’t convert.
When it comes to optimizing the user experience, Conversion Rate Optimization (CRO) is where you can squeeze the most out of your efforts. A/B testing (which we covered earlier) plays a massive role in fine-tuning elements like landing pages, call-to-action buttons, or checkout processes. Tools like Hotjar or Crazy Egg allow you to analyze heatmaps and see where users are clicking (or not clicking). Identifying drop-off points and fixing those can dramatically improve conversions.
On the technical side, Performance Optimization can make or break user engagement. Slow loading times, poor responsiveness, and buggy features can turn users off before they’ve even had a chance to explore your product. Speed optimization techniques—like using a CDN (Content Delivery Network) or compressing images—ensure your product runs smoothly and efficiently.
This category focuses on understanding the market landscape and customer needs.
The Service and Product Retirement domain is all about thinking long-term. The real test of a product’s longevity lies in how well you support it after it hits the market and how gracefully you retire it when it comes. This domain is about post-launch service, support, and the end-of-life process, ensuring that every stage of a product’s lifecycle is managed precisely. Done right, this domain strengthens customer loyalty, builds trust, and prepares the ground for future products. Ignoring it, however, is a fast track to frustrated customers and a diminished brand.
Service and Support is the subdomain of building and maintaining the infrastructure that keeps customers happy and returning. A well-handled support issue can turn a frustrated customer into a loyal advocate. Support ticket management is your front line here. Platforms like Zendesk or Freshdesk can help you efficiently track, prioritize, and resolve customer issues. Beyond just resolving complaints, these systems allow you to identify patterns in customer pain points. If a particular issue keeps cropping up, you must funnel that insight into the product development loop.
Of course, service and support aren’t just about putting out fires—they’re also about ongoing customer education. Depending on the complexity of your product, training programs or tutorial creation can help customers get the most value from your product. Well-designed onboarding guides or self-service tutorials can reduce the burden on support teams by enabling customers to troubleshoot independently. I’ve found that creating a comprehensive knowledge base or video tutorials reduces the number of incoming support tickets and enhances the overall UX.
Next, you have to consider cost management in the service stage. Supporting a product isn’t free; without a clear plan, the costs could add up unexpectedly. You’ll need to budget for ongoing maintenance (warranties and repairs in the non-software world). In my experience, many product managers underestimate these costs. Core developers are often on the frontlines of working with specific library dependencies that can break when upgraded. It’s crucial to factor support costs into your product’s pricing model or subscription plan to avoid taking a hit whenever a customer needs help. Done right, though, investing in great support can save money in the long run by reducing churn and increasing CLV.
Eventually, every product reaches its end-of-life (EOL) stage, where Product Retirement comes into play. Managing a product’s retirement is not as simple as flipping a switch. If handled poorly, it can damage your brand or alienate loyal customers. One of the first steps is developing a clear EOL plan that includes public announcements, phasing out support, and managing the remaining inventory. It’s a bit like working a controlled demolition—you want to retire the product with as little disruption as possible while also giving customers time to transition to alternatives. Furthermore, this includes providing legacy product support. Even after you stop selling or actively promoting a product, customers who’ve already bought it still expect some level of support—whether in the form of repairs, bug fixes, or extended warranties. For digital products, this might mean offering security updates or maintaining server uptime for a certain period after the product is officially retired. The key is communicating clearly with customers about what to expect—leaving them in the dark only fuels frustration and resentment.
Sometimes, a product’s retirement is an opportunity to push customers toward your next generation of products. Product evolution is often a natural part of the EOL process, whether that entails an improved version of the original or a new offering built on the same foundations. For SaaS products, this might mean offering incentives for customers to migrate from legacy platforms to your latest version and potentially bundling the transition with discounts or enhanced features.
This category focuses on understanding the market landscape and customer needs.
At its core, the Stakeholder Management domain is about balancing priorities, building influence, and ensuring that every voice, from the customer support team to the executive boardroom, is heard—and aligned. Whether you’re leading a product sprint, presenting to the C-suite, or aligning with marketing and sales, the key is consistent, clear, and strategic communication. When done well, stakeholder management strengthens relationships, reduces friction, and creates a seamless path for product development. Done poorly, it can lead to misalignment, delays, and a fractured team.
At the heart of effective stakeholder management is the domain of Cross-Functional Collaboration. Think of yourself as the central node in a complex web of teams, each with its objectives and workflows. The engineering team might be focused on execution and timelines, while the marketing team is thinking about go-to-market strategies and messaging. Managing these relationships is about getting everyone on the same page and ensuring constant, clear communication. Sprint demos, collaborative requirement gathering, and daily standups are critical for keeping all teams in sync. Even high-level Kanban boards will ensure everyone understands the major initiatives underway, those upcoming, and those in the backlog. Occasionally, including this in the stakeholder newsletters is vital.
The Design Collaboration is the competency defining the relationship between product management and design teams can make or break the user experience. Design sprints or co-creation workshops are particularly effective for ensuring alignment early in the process. Tools like Figma and InVision provide an interactive space where design and product teams can iterate quickly on wireframes, gather feedback, and implement changes before development kicks off. It’s like having a sandbox to play in before committing to building the final structure. I’ve found that getting early design feedback from stakeholders helps avoid costly revisions down the road.
Marketing Alignment is the competency where product managers and marketing teams work hand-in-hand to ensure a product’s positioning and messaging resonate with the target audience. But this is often where friction arises—product teams are focused on features and timelines, while marketing teams are concerned with storytelling and differentiation. I’ve often used messaging workshops and go-to-market alignment sessions to bridge that gap. These workshops bring the teams together early, ensuring everyone understands the product’s core value propositions and how they’ll be communicated externally. It’s like laying the tracks for a train; the product team builds the engine, but marketing provides the direction.
The competency of Sales Enablement means building sales playbooks, FAQ documentation, and feature sheets that break down product capabilities into clear, customer-facing benefits. The sales team often has the most direct contact with customers and must be armed with the proper knowledge and tools to pitch the product effectively. A product manager should be capable of running sales training workshops to ensure the team is comfortable answering technical questions and positioning the product accurately. If your sales team doesn’t fully understand what the product can do, they can’t sell it effectively, nor can they consider means to capture value more innovatively from the customers. Integrating CRMs into the platform’s user database ensures that all product updates and customer interactions are logged in their journey. This will automatically update that loop between the sales and product teams and help them consider retargeting strategies if engagement declines.
Executive Communication is the domain of demonstrating the business case and not being caught up in the nitty-gritty technical details of the product. This requires translating product roadmaps and the commercialization strategy into a strategic pitch. Separate C-level pitch decks and executive briefings work best when they focus on the impact, regarding ROI analysis, financial forecasts, and how the product aligns with the company’s objectives. Executives don’t care about the specifics of a new feature, but they do care about whether it will increase revenue, reduce churn, or capture market share. Sharing a dashboard to showcase performance metrics is essential. Tools like executive dashboards (Metabase, Tableau, Databox, Domo, and others) help communicate performance metrics visually so executives can quickly understand how the product impacts the bottom line.
Managing Executive Stakeholders also involves building relationships beyond the formal meetings. One-on-one meetings with executives, using tools like stakeholder mapping or influence diagrams, help you understand their motivations, pain points, and what they need to see to give their buy-in. It’s much like navigating a political landscape where every executive has their interests, and your job is to align their interests with the product’s trajectory.
This category focuses on understanding the market landscape and customer needs.
Leadership and Organizational Influence is the domain for mastering the delicate balance between authority and influence, aligning diverse teams around shared goals, and navigating the organizational landscape effectively. This requires stepping beyond managing the micro to guide your teams' macro direction truly. In many ways, product management is leadership without formal authority. You don’t always have direct control over the people or resources you need, yet you’re responsible for driving results. The product manager becomes a strategist, a diplomat, and a leader guiding the entire organization toward success. Mastering this domain requires influencing skills, political savvy, and the ability to lead cross-functional teams toward a shared vision.
Leading without direct authority is one of the most challenging aspects of product management. It’s like trying to steer a ship where you’re not the captain, but everyone still expects you to navigate through the storm. Servant leadership is a powerful model here—by focusing on listening and recognizing, enabling, and removing roadblocks for your team, you gain trust and credibility. This means actively identifying bottlenecks, whether external dependency, a lack of resources, or a miscommunication between teams. A good servant leader always asks, “What can I do to make your job easier?” It’s about creating space for the team to do their best work. Facilitating open communication is crucial for making sure your team thrives on transparency and trust. Hold regular 1:1s where team members can voice concerns or ideas without fear of judgment and use team retrospectives to openly discuss what’s working and what isn’t. Recognizing contributions and giving credit where it’s due fosters a culture of appreciation, motivating people to push harder because they know their efforts are valued. When things go right, it’s about amplifying the team’s success, not taking personal credit. Lastly, ask questions that help the team think critically about solutions instead of giving directives. When someone approaches you with a problem, resist the urge to solve it for them—coach them through it and empower their ownership. Over time, you want a team that doesn’t rely on you for every decision.
A product manager needs to figure out how to Navigate Politics. Every organization has its power dynamics, and knowing how to read the room, understand motivations, and align interests is essential for moving initiatives forward. Power mapping and stakeholder analysis are invaluable tools here—they help you identify who has influence, who is likely to support your initiatives, and who might resist them. It’s like strategizing in a chess game—you must anticipate moves, build alliances, and sometimes, work around internal resistance. I’ve learned from sales cycles that influence is not merely getting the obvious decision maker to buy in, but about understanding the informal power brokers and influencers within the team—those who might not have a formal title but hold significant sway over decisions.
Then there’s the art of Influencing Executives. When you’re sitting down with C-suite leaders or board members, the conversation shifts dramatically. Executives think in terms of high-level outcomes, not details. They’re interested in understanding how your product impacts the business—how it drives revenue, reduces costs, or opens new market opportunities. Utilize persuasion strategies. Take a page from high school English class and utilize an ethos, pathos, and logos approach. Balance credibility (ethos), emotional appeal (pathos), and logical arguments (logos) to build a case that resonates with executive priorities. Utilize the Why, How, What logical flow. Persuasion following these techniques is like pitching to investors—except this time, you’re pitching your internal leadership to invest in your vision.
Mastering cross-functional influence—leading teams that don’t report to you directly—is the art of professional cat herding. Every team has its priorities and objectives, which don’t always align neatly with yours. It would be best if you learned how to influence without authority. This requires understanding what each team values and showing them how your product’s success aligns with their goals. For example, if you’re working with an engineering team, you’ll want to frame your requests regarding how this project fits into their technical roadmap and offers exciting challenges that align with their goals. For marketing, it’s about ensuring that the product’s features will support compelling messaging or differentiate the product in the market. Different teams, different individuals, and different projects require different leadership styles. Utilize Situational Leadership to determine whether you need to be hands-on, guiding the team step-by-step (directive leadership). Other times, you must step back, give the team autonomy, and act as a coach (supportive leadership). Learn to be a chameleon and blend into various teams to get the best results without micromanaging or becoming disconnected.
In startups or progressive companies, the traditional hierarchy is often flattened. This is where Organizational Structure and tools like Holacratic Role Mapping come into play. Instead of rigid hierarchies, roles and responsibilities are usually fluid, meaning that product managers must be even more skilled at defining who is responsible for what. A product manager should be able to define their organization’s Circles, Roles, and Accountabilities outside of corporate, titular hierarchy so they can better understand information flows and chemistry. RACI matrices (Responsible, Accountable, Consulted, Informed) are essential for navigating this ambiguity—they ensure everyone knows their role in the project and who they should communicate with. In a matrixed environment, where teams often have overlapping responsibilities, having clarity on who’s accountable for what is crucial to avoid bottlenecks and confusion. In a future article, I’ll discuss the intersection between Holocracy and RACI matrices models and how to employ them.
This category focuses on understanding the market landscape and customer needs.
In the Regulatory Compliance and Ethical Design domain, you build products that customers can trust, align with their values, and set you apart in an increasingly conscientious marketplace. Ensuring that the company abides by the regulatory standards of the jurisdiction you select is everything. Innovation often operates in the grey zone, and regulators are bought by the established powers. Furthermore, abiding by ethical principles is a critical component of long-term brand success. If mishandled, we’re talking subpoenas, cease and desist orders, lawsuits, IP theft, personal charges, hefty fines, brand damage, and a loss of customer trust. The intricacies of selecting a jurisdiction are far beyond the scope of this article. Instead, I’ll focus on discussing the principles of privacy by design, fair and transparent AI, accessibility, and sustainability.
The Data Privacy Compliance subdomain is about adhering to GDPR and CCPA and handling user data carefully. The Privacy by Design competency must be embedded into your product from the outset. Techniques of data minimization, where you only collect the information you need, and anonymization, ensuring that even if data is breached, it can’t be traced back to individuals, are essential. Differential privacy allows you to glean insights from user data without exposing individuals. A commitment to protecting user privacy is a competitive differentiator.
But it’s not just about user data. Industry-Specific Regulatory Compliance competency is another critical area. If you’re working in healthcare, fintech, or similar highly regulated sectors, you must ensure your product meets the specific standards of that industry. For example, in healthcare, you must comply with HIPAA to protect patient data. In contrast, financial products like the UK's Financial Services and Markets Act may need to meet FINRA or KYC (Know Your Customer)/AML (Anti-Money Laundering) standards. Furthermore, there are several best practices surrounding gamification and built-in incentives. The product's design will be essential to utilizing professional services to understand the tax implications for monetizing multi-sided platforms, the payment methods and structures for platform value creators, and monetizing royalties and secondary sales.
Neglecting these regulatory requirements can result in legal action and severe reputational damage. That’s why compliance audits and ongoing regulatory documentation are essential to your product development lifecycle. More established teams utilize a compliance-by-checklist system, ensuring that every feature or service meets the necessary standards before shipping.
For global products, International Regulations add another layer of complexity. Products crossing borders are subject to various national regulations around data storage, privacy, and user interface requirements, requiring you to take a strategic Localization approach. For example, in some jurisdictions, cross-border data flow is restricted, meaning you may need to store data locally. Using legal hubs and consulting local regulatory bodies early in the development cycle ensures you don’t hit roadblocks later on when entering new markets. Including international legal counsel in early product strategy sessions to anticipate these challenges before they become obstacles is a massive cost saver.
Beyond compliance, there’s the broader—and arguably more important—issue of Ethical Design. In an era of increasing scrutiny around AI and ML, products are expected not just to work but to work fairly and transparently. This is where the FAT (Fairness, Accountability, and Transparency) framework becomes invaluable. When building AI models or automation systems, it’s critical to ensure that they are free from bias, and this requires regular bias auditing. Including human oversight through a Human-in-the-Loop better ensures automated systems don’t make critical decisions in a vacuum. This is especially crucial in industries like recruitment, finance, or healthcare, where AI-driven decisions can significantly impact people’s lives. Ethical AI issues are so intricate and complex that they deserve a specific article.
Another component of ethical design for widespread products is Accessibility and Inclusivity. The WCAG (Web Content Accessibility Guidelines) has some of these principles for people with cognitive impairments. Reading these principles and then practically adopting them into the timeline when you’re already backlogged to high heaven is just an egregious display of ignorance on behalf of higher-ups. But beyond the fluff and nice to haves to stroke the ego of that one team member who self-identifies as representing an unjustly afflicted subgroup, there are genuinely some great and practical tools to consider for an overall better UX and improved user journey. Perceivable Principles are crucial for video games, AR, VR, and entertainment products—or if you have some interactive data visualization, be it an interactive map or trading charts. Over time, mainly because browser-based graphics are so much easier to build and run, it’s even more important—including WebGL/WebSockets-based cooperative workspaces. The Operable Principles have some nuggets. Making your platform Keyboard Accessible, meaning utilizing shortcuts for everything in-app from the keyboard, is a significant tool to lock in die-hard retention from your loyal customers. Making your platform Navigable is about implementing a clear and consistent navigation structure, mainly regarding clever ways of locally storing page history. Understandable Principles of Web Page Predictability in consistent design and layout and Input Assistance with helping users avoid and correct mistakes for input form validation are huge quality-of-life improvements. Proving Customization options lets users adjust text size, color schemes, and content density to suit individual preferences.
Lastly, and this is mostly for models requiring significant computation, consumer packaged goods, or other physical goods, there’s Environmental and Social Impact. Sustainability metrics are a checkbox that, when done right, are a competitive differentiator, giving customers peace of mind to know they’re not making the planet even worse. Implementing Life Cycle Assessments (LCA) can help you understand the environmental impact of your product from creation to disposal, including resource usage, carbon footprint, and recyclability.
This category focuses on understanding the market landscape and customer needs.
Proprietary Innovation and Commercialization is where product management intersects with competitive advantage, intellectual property (IP), and long-term monetization strategies. This domain is about turning unique insights, data, and technology into long-term competitive advantages and strategic assets to expand your business model and protect your market positioning. For products rooted in deep innovation—whether AI, behavioral data, or custom hardware—this is where you ensure the value you’re creating is yours to keep and leverage.
The competency of IP Portfolio Development is self-explanatory. If you’re creating something novel, protecting that innovation is non-negotiable. Whether you’re filing patents, securing trademarks, or developing proprietary algorithms, your intellectual property is your moat. Filing Patents for physical products or custom AI models signals to the market and investors that you’re in this for the long haul. Trademarks protect brand elements and trade secrets safeguard confidential formulas or business methods. Building a relationship with a trusted IP attorney early on ensures that as your products diversify, your legal protections scale too. IP isn’t just about preventing imitation—it’s about how you capitalize on it. Licensing agreements can turn your IP into a revenue stream, allowing other companies to use your technology under specific terms. You retain control while extending your reach. It’s a strategic play that transforms innovation into a broader commercial opportunity. On the defensive side, IP audits help you ensure that your portfolio is aligned with your business objectives—spotting areas where you may be vulnerable or where further protection is needed.
The development of Proprietary AI Models and Data Assets is the essential competency in our era of Big Data where these major AI companies are seeking to differentiate and expand their capabilities. Those companies are middlemen for accessing and expanding your reach across many practical vendors. The behavioral data your product captures can be one of your most valuable assets. To capitalize on this, you must turn raw data into something actionable and proprietary. This involves feeding your insights into building and training custom AI models based on that data—whether it’s your recommendation engine or decision-making system. The beauty of proprietary AI is that it’s difficult for competitors to replicate, unlike features or UI.
Monetizing these proprietary assets is about finding ways to generate revenue from your data and AI. This can mean developing proprietary databases that provide unique insights only you can offer. When collected at scale, user behavior analytics can fuel data-driven services that other companies are willing to pay. This creates a secondary monetization layer, where your data and insights become products in their own right. Ideally, you can make participation optional, recommended, and baked into your pricing strategy. Think of it like Netflix’s recommendation engine; it’s not just a feature but a proprietary tool that drives engagement and retention. For B2B SaaS products, this might involve creating usage analytics platforms for customers that offer insights on how they interact with your product, turning data into actionable intelligence.
Proprietary innovation taps into the competency of Reinforcement Learning for optimization. In platforms with dynamic user interactions such as marketplaces or content recommendations, your platform is learning about content triggers and seasonal changes in consumer appetite. It acts as a leading or lagging indicator for market trends. For example, multi-armed bandit models can optimize product offers, adjusting them based on user preferences in real-time. As the system learns, it improves targeting, leading to better user experiences and higher conversion rates.
Introducing a strategy for Open Source expands the field of proprietary innovation. On the surface, open-source tools might seem at odds with building proprietary assets, but they’re not mutually exclusive. Open-source allows you to tap into the prosumer mindset while protecting and expanding the functionality of core IP. If you’re developing an open-source tool, the key is to build it to allow your team or external developers to extend it but keep specific vital components—like AI models, custom algorithms, or datasets—proprietary. This strategy can also lead to commercialization through dual licensing (open core) models, where the primary product is free. Still, advanced features or support services are offered at a premium. Of course, an open-source strategy requires Documentation and Developer Enablement. A product manager should be obsessive about comprehensive documentation to drive adoption and usage. The documentation serves a dual purpose of acting as a communication tool across members of your team and serves as a more practical documentation for the team.
Ultimately, a product manager is best suited to understand the Commercialization Strategy. It’s the tether of the technical roadmaps to closing deals and securing and expanding revenue streams through the help of sales. Proactively considering your sales cycle will help you formulate a more robust Market Entry Strategy. This will help you decide whether to sell directly to end-users, license to other companies, or create developer ecosystems around your platform. You could be licensing an aspect of your data collection from your frontend or considering new channels for more effective distribution. Monetizing proprietary innovation requires building great tech and knowing how to position it within the broader market, whether through direct sales, partnerships, or B2B licensing deals.
Mastering the 11 essential domains of product management is critical for driving innovation and sustained growth. Each domain I’ve demonstrated here serves a unique and vital function. These are the expertise to secure long-term competitive advantages, optimize growth, and ensure long-term profitability. The PM’s job is to balance strategic foresight with tactical execution.
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