[PM Talks] How to Recognize When You've Achieved Product-Market Fit

Y Combinator’s mantra is simple yet powerful: Make something people want. Yet, despite its clarity, many SaaS and startup companies struggle to achieve it. True success comes from building something people not only want but are willing to pay for and recommend to others—this is the essence of product-market fit (PMF).

But what exactly is PMF, and how can a company achieve it? Once reached, can it be lost? What metrics should businesses focus on, and what strategies can help along the journey to securing product-market fit?

We explored these questions and more with the one and only Jacqueline Porter, Director of Product Development at GitLab.

Give it a listen or dive into this insightful interview, packed with inspiring takeaways and hard-earned lessons from Jackie’s seven-plus years in product development leadership.

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About Jacqueline Porter:

• Director of Product Management at GitLab
• Strategic product management professional with seven years of product development leadership experience
• Follow Jacqueline on Linkedin

What does product-market fit mean in simple terms?

Product-market fit is when your product solves a significant problem for a specific market so well that customers use it consistently, recommend it to others, and eventually purchase it.

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What are some common misconceptions about product-market fit? Could you look back on your career and share some examples of how companies have achieved product-market fit?

So, first, tackling the misconceptions part—when we talk about product-market fit, there’s a common belief that once you achieve it, you’ll always have it. That’s absolutely not true. Product-market fit can be attained and then lost—it’s not permanent. It depends on several factors, mainly your user base, your market, economic conditions, and even how well your company is growing as part of the product journey.

Looking back at my career, I’ve been fortunate to work at product companies that were really well-loved by their users. I got to see cases where many companies had already reached product-market fit—they were already viable businesses, and we were connecting them together.

For example, when I worked at PeopleAdmin, which was a human resources technology stack for K–12 and eventually K–24, we served a broad spectrum of educational institutions. This included elementary schools, primary schools, and higher education institutions, all using HR management tools. What I found in those roles was that product-market fit became clear through universities recommending our tool to other universities. They saw it as essential for driving efficiency in their organizations. A huge portion of our business came purely from referrals.

Now, I’ve also worked at companies building zero-to-one products—where nothing existed before, and we had to launch something entirely new. A good example is Spredfast (now part of Khoros). When I was there, it was a social media ingest platform competing in a very saturated marketing tools space. We had to ensure we were continuously adding new functionality to differentiate ourselves. By the time of acquisition, the company ended up merging with three other companies to deliver an end-to-end platform. This was necessary because our target market was enterprise businesses, which typically require a full platform to orchestrate their workflows.

So, when we talk about achieving and sustaining product-market fit, it really comes down to maintaining business performance and revenue as a result of your product being in the market.

If we want examples that more people might relate to, let’s take Netflix. Netflix started as a DVD rental company, then transitioned to streaming, and now it’s reshaping the entertainment industry as we know it. Initially, DVDs were popular, but once Netflix moved to digital streaming, it became so accessible that people wanted to keep using it. Today, for many people, Netflix is part of their daily routine—you just turn it on and watch.

On the other hand, a failure example would be Google+. I don’t know if you remember, but every time you used Google, you’d see your Google+ identity pop up. By 2019 or 2020, the product was shut down because there wasn’t a compelling reason for people to switch from Facebook to Google+. Users didn’t feel they needed the functionality, so they just stuck with LinkedIn, Facebook, Instagram, and other platforms that were already integrated into their social media experience.

What are some of the early signs that product-market fit has been achieved?

I have a great example right now. We have this experiment running in our GitLab CI tool.

So, GitLab is a software development tool for developers, and the part of the product I own is called Continuous Integration. This includes all the features a developer needs to test, package, and deploy their changes to a customer.

We've been working on a functionality that improves how someone builds specific tests or steps within their development verification workflow. It’s been in our product for a couple of months now, and we’ve already started getting feedback from enterprise customers saying, “I’m using this—when is it going to go to production?”

That’s a really strong signal that we’re addressing the right problem and solving it effectively. Customers are telling us, “I need this in production now because I want to use it for my production workloads ASAP.”

What I mean here is that people are actively recommending this setup for their own products and customers as GitLab users. There’s also a strong interest in shaping what the feature looks like. This level of engagement is a major indicator that we’re solving the right problem and that people truly want to use it—which is really the definition of product-market fit, right?

What key metrics do you regularly track in your product, like retention rates or NPS scores?

When you're starting to assess product-market fit, the key data points you’ll look at include monthly recurring revenue and retention. Ideally, you’re aiming for zero churn—meaning 100% net revenue retention, month over month and quarter over quarter—which would indicate you’re meeting product-market fit.

NPS, or Net Promoter Score, is a great survey for measuring referral momentum. Another useful metric is the Customer Effort Score (CES). While CES spans both usability and product-market fit, it helps assess how easy it was for users to complete tasks within your product. High CES scores indicate that your product is effectively solving their problem—not just that they’d recommend it, but that it genuinely helps them accomplish their work.

One challenge with in-product surveys like NPS, CSAT, or CES is the lack of role-based targeting. If you have a platform with 10 to 15 different types of users, each using your product in different ways, their responses can be highly variable. At any given time, their experience, mood, job role, or the specific task they’re working on may influence how they respond.

For early-stage startups with a narrow, well-defined product, these surveys can be more illustrative because users have a limited set of jobs they’re trying to complete. But for a mature product with multiple user personas, interpreting survey results can be more complex.

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Do quantitative metrics become more meaningful when you have hundreds or thousands of customers, while early-stage startups should focus more on direct user feedback and conversations?

You're going to see high engagement rates as you move toward product-market fit. As more people recognize the value of your product, you'll start getting more inbound interest than you know what to do with as a product manager. That’s been my experience—when there’s a surge of engaged users actively interacting with the solution, it’s a strong signal that you’re getting there and have likely achieved product-market fit.

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Once you've reached product-market fit, how do you sustain and build on it?

Once you reach product-market fit, you need to start identifying the next features or aspects of the product that require investment to sustain that fit. I’d recommend adding usage instrumentation to track how people navigate through your product and how well they’re utilizing each feature.

It’s also important to analyze different types of feedback, such as support tickets, closed-lost deal information, and qualitative insights that might not come in the form of direct feature requests. For example, if multiple users submit support tickets saying their SSO (Single Sign-On) is failing, that’s a major onboarding barrier. As a product manager, you might recognize that this is creating a top-of-funnel issue that impacts adoption rates.

As you scale beyond product-market fit, you should also consider the holistic user experience and how every touchpoint affects engagement.

Another key step is defining your user cohorts. Since you’re collecting valuable data on retention and usage patterns, start segmenting users based on characteristics like industry, company size, or role. Are they individual contributors or management?

Understanding who is getting the most value from your product allows you to conduct targeted research and design experiences that better serve each persona.

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Should product leaders focus on a specific segment as soon as they acquire their first customer from that segment, pursuing similar companies right away? Or would you recommend keeping the solution broader at the beginning, observing which companies sign up, and only narrowing the focus once there’s a clear pattern—say, after acquiring 10 companies from a particular segment—before doubling down to dominate it?

That’s a strategic question that many product leaders and teams grapple with. When you're in the early stages of product-market fit, you may not see strong signals from a specific industry because you’re often targeting a broad user base.

For example, at GitLab, we target developers—but developers exist across different contexts. Some are independent, some contribute to open-source projects, and others work at enterprises. Despite these differences, they all share the same core tasks. However, when you start examining who is willing to pay for your product, you begin to see more nuance—layers of roles beyond the core developer journey that ultimately drive revenue.

In the early days, many startups lean into a "feature factory" approach, rapidly shipping features to expand their competitive scope. Typically, there's already an existing product in the market, so startups try to deliver everything necessary to erode a competitor’s market share.

So, how do you validate assumptions and ensure you're focusing on the right things—both to delight users and sustain product-market fit while also driving revenue? I’ve found that embracing an experimentation framework—through A/B testing, prototyping, and working with early adopters—is a great way to identify the most profitable or beneficial segments to invest in.

Experimentation helps answer questions like: Do we need specialized solution pages for different sectors? Should we engage different personas and buyers as part of the lifecycle? However, for many early-stage startups, this level of market segmentation is often overlooked. Instead, they tend to race toward competitive differentiation—trying to match or outdo existing solutions—rather than focusing on deeply understanding and delighting a specific segment.

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The Sean Ellis test suggests that if 40% of your users say they’d be very disappointed without your product, you’ve achieved product-market fit. What’s your take on this metric? How relevant do you think it is in modern product development?

First, I want to take a step back and talk about who Sean Ellis is, why he’s important, and why this test was created.

Sean Ellis was a marketer at Dropbox, a company known for achieving product-market fit after multiple failures. The key breakthrough came when they improved their syncing functionality, which ultimately helped them dominate the market. Sean Ellis was responsible for positioning and competitive research at Dropbox, and he developed a survey to measure the signal of when product-market fit has been achieved.

His rule was simple: if 40% of survey respondents say they would be very disappointed if the product went away, that’s a strong signal that you’re reaching—or have reached—product-market fit.

That said, there are a couple of caveats with this survey. First, you need to ensure that the people responding are actually users of the product. While that might seem like common sense, in platforms with multiple user types, the person answering the survey might not be engaging with the core workflow—potentially skewing the results.

Second, the survey requires a statistically significant number of responses to be meaningful. If 40% of just 10 respondents say they’d be very disappointed, that’s not enough to confidently say the product has reached product-market fit.

As for my take on the Sean Ellis test—I think it’s a useful signal, but only when used alongside other PMF metrics that track retention, revenue, and product usage. This survey is purely sentiment-based; it doesn’t measure actual revenue or engagement.

So, in terms of its relevance to modern product development, I’d say it can be helpful for early-stage startups with a small but engaged user base. If you can effectively target the right users with the survey, it may help identify key user segments and prioritize features based on their needs.

Are there common mistakes product teams make in believing they’ve achieved product-market fit too soon?

Sometimes product managers track usage metrics and assume they indicate adoption, when in reality, they’re just vanity metrics measuring absolute usage or feature consumption.

For example, if you see a big spike in usage within the first two or three months after launch, that might signal user enthusiasm—but not necessarily broader market demand. Metrics like downloads, page views, or feature usage counts often just reflect interest, meaning your awareness funnel is working, but they don’t confirm real traction.

Another common mistake is assuming that media mentions, social media buzz, or going viral equates to product-market fit. While these events drive awareness and top-of-funnel engagement, they don’t necessarily indicate that PMF has been achieved or sustained.

Ultimately, focusing too much on absolute counts or vanity metrics won’t tell you whether your product is truly adding value or solving a user’s problem. It only shows that people are engaging with it—which isn’t the same as real, lasting adoption.

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Should vanity metrics like downloads, signups, or page visits be completely disregarded when evaluating product-market fit? Or do they serve as useful signals in the discussion? How much weight, if any, should they have in determining whether a product has truly achieved product-market fit?

I’d say it’s good to have comprehensive usage tracking, and if you’re limited in what you can instrument, something is better than nothing. But to truly assess product-market fit, you need to focus on sustained usage over time—things like how many people are abandoning your product, how quickly users adopt a new version once it’s released, and how long it takes for them to start consuming it. These metrics provide insight into time-to-value and overall product uptake.

Relying solely on absolute counts—such as email signups, click-throughs, page views, or even total signups—can be misleading, especially in today’s world where AI agents and bots are increasingly prevalent. Automated accounts can generate more traffic than real users, skewing engagement data.

As a product manager, it’s important to understand how your product is being interacted with—including by non-human users. If you have no other way to track engagement, those broad metrics can still provide some value. But ideally, you should prioritize instrumenting data that tracks actual consumption, sustained usage, and long-term engagement.

Have you ever seen a product achieve product-market fit with its very first version? Or is it always an iterative process?

You know, I haven’t really looked deeply into Apple’s journey, but I feel like Apple found success early on—even with their iMacs in the education sector. They had MacBooks and computers that fit well within that space, which suggests they did attain product-market fit in education.

But as they expanded, they started facing stronger competition from Microsoft and other computer providers. That’s when they pivoted, shifting their focus toward mobile devices, music devices, and personal consumer electronics—supported by their Think Different campaign. So, you could argue they initially found product-market fit within education, but when they went broader into B2C, they had to redefine it.

On the flip side, how often do we see product-market fit fail with a company’s first version? Honestly, that’s the majority of products. Most start with one idea and end up pivoting.

Take Slack, for example. Today, it’s a globally used messaging tool, but it actually started as a gaming company. Their original idea didn’t resonate, but people showed interest in their internal messaging tool—so they pivoted and turned it into a product.

Instagram and Twitter are similar cases. Both started as something else before evolving into the products we know today. It seems like, more often than not, products go through multiple pivot points in their early journey rather than maintaining their original direction from the start.

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We talked about losing product-market fit after initially achieving it, and you mentioned that market dynamics or economic conditions can play a role in this. Could you share some specific examples where you've seen this happen?

Just look at all the companies that had to shut down when COVID hit. When the pandemic struck, many businesses went under—especially startups that had just been funded at the end of 2019. That was a clear example of how even companies with strong tailwinds before the pandemic struggled to survive.

The uncertainty about the economic future led businesses to tighten their budgets. And when budgets are constrained, companies become more risk-averse, meaning they’re less likely to adopt new products with unvalidated outcomes.

In times of economic downturn, products that emphasize cost efficiency, cost savings, and consolidation tend to resonate more. Companies that can demonstrate a strong ROI for their customers may still reach product-market fit even in tough market conditions. But during the pandemic, many businesses weren’t able to do that—and as a result, they shut down.

Now, if we look at general market dynamics, take what’s happening with AI today. AI companies are everywhere—there’s an abundance of them—and many are achieving product-market fit quickly because they promise higher-quality results with fewer resources. That’s a highly attractive value proposition, not just for businesses but also for individuals who want to do more with less. Because they directly address a strong user need, these AI companies are reaching PMF faster.

Let’s dive into tools and strategies for testing product-market fit. We’ve already mentioned user interviews, feedback, and quantitative tools. What are the best methods you recommend for collecting actionable feedback from early adopters?

GitLab is unique in that we offer both a self-managed installation that customers can host and a SaaS offering. Because of this split distribution, we’ve developed a framework for instrumenting usage tracking that works across both environments.

Typically, we track events using Snowplow and Redis to monitor user engagement. This data is then dumped into a database, where people can layer Tableau visualizations on top. However, this process is time-consuming and requires significant effort. It also makes it more challenging to implement certain product-led growth strategies that other companies might use more seamlessly.

In other organizations, I’ve used SaaS solutions like Amplitude and Pendo for tracking user journeys and product consumption. I’ve also worked with Segment to collect and aggregate data into a central database or data store. Analyzing this data often requires writing specific SQL queries or creating Tableau visualizations.

From a survey and qualitative data analysis perspective, I highly recommend Qualtrics and Dovetail.

• Qualtrics is a robust survey tool that supports both qualitative and quantitative data analysis.
• Dovetail is a user research platform that allows you to create interview templates, upload recordings, generate transcripts, and tag insights across multiple interviews to identify key themes.

These are all valuable tools for assessing and understanding product-market fit.

If you joined a small startup with a team of five and they already had 10 customers, what would be the first thing you’d do? Would you implement any of the tools and strategies you mentioned earlier at this stage, and if so, which ones?

If you have the technical architecture to support tools like Amplitude or Pendo, they can save you a tremendous amount of time when it comes to instrumentation and sharing usage data. So, start with that in mind and be intentional about how you want to track usage in your product. I’d definitely recommend evaluating Amplitude or Pendo to see if they’re a good fit for your needs.

It’s also important to consolidate qualitative feedback in a single place. Whether you use Dovetail or simply store everything in Google Docs and Google Drive, the key is to establish a structured approach to sharing insights from customer interviews in a secure and anonymized way. This is crucial, not only for organization but also for ensuring compliance with GDPR—since storing customer data on local machines could pose privacy risks.

Having a SaaS tool for this becomes even more valuable as you scale. Once you hit product-market fit, you could have hundreds of users engaging with your product, and tracking that feedback in a structured, centralized way makes it much easier to share insights across teams.

What role do MVPs play in testing for product-market fit? How do they help validate whether a product is meeting market needs?

I think it’s important to first define what an MVP is. An MVP (Minimum Viable Product) is the smallest set of features needed to solve a customer problem.

When we talk about product-market fit, it means you’ve successfully solved that problem in a way that resonates with your users. The role of an MVP is to help you incrementally measure how well you’re solving that problem—quickly, cheaply, and efficiently—before committing to building a fully developed system.

It’s much easier early in the journey to launch something small and gather real user feedback than to design and ship an entire solution, only to realize it doesn’t meet user needs. An MVP is essentially the critical path to solving a customer’s problem—a version of the product that can be put into the market to start delivering value as soon as possible.

Do you have any examples of an MVP you tested that later evolved into a product with clear product-market fit?

At GitLab, when I was first hired, I was responsible for introducing release management capabilities. At the time, we only had one core feature that fell under release management: a commit tag. This allowed developers to tag a change, signaling that it should move forward as a versioned software release.

When I started meeting with customers interested in release management, I discovered three key things they really cared about:

1. Cross-team visibility – they wanted a clear view of all releases.
2. Asset attachment – they needed a way to attach relevant files to a specific release.
3. Governance – they required permission controls to prevent unauthorized release creation.

From these conversations, we identified quick wins:

• Creating a dedicated page where users could see all their releases.
• Allowing users to upload artifacts to a release object.
• Implementing permissions to control release creation.

Once we launched these features, interest in the product skyrocketed. We went from 20,000 monthly active users to over 300,000 in just a few months. Users were eager to solve their release pain points—challenges they either couldn’t address within their existing tools or had to pay for separately.

This was a strong signal that we had achieved product-market fit. By tackling the core problems of visibility, sharing, and permissions, we scaled our monthly active users dramatically in less than a year.

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How can companies adapt and stay relevant after achieving product-market fit and scaling rapidly?

I’ll take a step back and talk about something that’s sometimes at odds with customer relevance—preparing for growth technically. Growth can be unpredictable, and it’s crucial to think ahead about the reference architecture of your product.

Ask yourself: What scale are we targeting? A million users? Two million? Four billion? Defining your expected user scale early on helps establish the minimum technical requirements needed to support long-term demand.

One of the worst things that can happen is reaching product-market fit, experiencing 3x growth every quarter, and then watching your system start to break because it wasn’t designed for that concurrent user workload. If you don’t design for scale from the start, your product may become unusable, leading to lost momentum—and ultimately, lost product-market fit.

That’s why it’s important to proactively align with technical architects as soon as you see sustained early adoption signals. Make sure your system is built for the scale you’re aiming for and assess what needs to be done to maintain performance.

Beyond technical scalability, customer relevance is key. Engaging with customers continuously ensures you’re on the right track. Personally, I like to maintain an advisory board of key customers—a group of companies and users that fit the target profile I’m designing for. This allows me to validate direction, test prototypes, and ensure we’re meeting competitive demands in our market.

Lastly, I’d recommend keeping a close eye on market analysts and industry reports. Organizations like Forrester and Gartner publish reports like the Magic Quadrant and The Wave, which highlight the top tools in different segments. Staying proactive about how your product is positioned in these reports helps you manage your brand and understand the broader competitive landscape.

To wrap up our discussion on product-market fit, what final advice would you give to product managers or entrepreneurs striving to achieve it?

I would say focus on solving real problems that your customers are facing. Listen carefully to what your customers are saying—especially those who are willing to pay early.

Don’t spend too much time trying to build a perfect solution. Get something out there, gather feedback, and iterate quickly.

Lastly, don’t fall into the sunk cost trap. It can be difficult to look at the product you’ve built and feel hesitant to pivot or make significant changes. But if you’re truly aiming for scale and escape velocity, you may need to commit to a pivot—even if it means redoing everything you’ve already built.

It might feel like a waste of money, but think about it this way: if you invest $100K now and that leads to $1M in revenue by the end of the year, it’s worth it. But if you stay fixated on the $100K spent, you might never reach that $1M potential.

Could you also share some resources or frameworks you recommend for understanding product-market fit? Additionally, are there any books, tools, or blogs you find valuable for product management in general?

There are a few books that I make a point of rereading every year. One of them is The Innovator’s Dilemma. It’s a fantastic resource for thinking about how your product can drive value for customers while balancing adoption metrics and long-term growth considerations.

Another key book is The Lean Startup. It provides a clear framework for understanding product-market fit and scaling your business—a sort of “PMF in a bottle.”

I also highly recommend Jeffrey Moore’s Crossing the Chasm. This book dives into the strategies needed to scale a business, reach product-market fit, and take your company to the next level.

In addition to these books, I’ve found Y Combinator’s Startup School to be a helpful resource. It offers a wealth of materials for startups, which I utilized several years ago when I was working with private equity companies. We were acquiring numerous businesses and rapidly working toward product-market fit, and the content from Startup School proved valuable. While it may not be as relevant today, it’s still worth considering for early-stage startups.

Lastly, I’d say tools like GPT and Claude, and AI in general, are really changing the game in product management. They can be a valuable resource—of course, with proper validation of the information they provide.

When you’re exploring ideas for your use cases, customers, and personas, these AI assistants can help you ask questions like, “What have other companies done to achieve product-market fit in this segment or business?” This can broaden your understanding of what’s been tried before, identify approaches that might be relevant for your area, and help you experiment without making early mistakes.

AI tools can serve as a kind of “back pocket” resource, giving you fresh perspectives on how to solve problems for your customers.

Let's get to our favorite fives: questions we ask every product manager who joins us on this podcast. First, what is your biggest challenge as a product manager?

User and customer journeys (two distinct things). How a user gets started on your product is different from how a buyer purchases it. It’s essential to understand both.

Getting the balance and prioritization right across these different journeys is challenging. That’s what I find most difficult in my day-to-day work.

If you could choose one key metric, your North Star, to define your success as a product leader, what would that be?

This might sound a bit transactional, but at the end of the day, product leaders are here to drive revenue for the business. I truly believe that a product leader’s ability to manage a P&L and grow revenue over time is the ultimate litmus test of their success.

When it comes to 'build versus buy', how do you decide?

It really depends on the company and its growth goals. For example, if you’re at a company that prioritizes organic growth and the platform experience, it might be more cost-effective to build in-house. Often, it’s cheaper to have your own engineers handle it, rather than spend time and money finding a tool that matches your tech stack, language, and experience—especially when integration costs and timelines are considered.

However, if you’re at a company focused on rapid market share acquisition, you might have a bigger budget to work with, such as a private equity-backed fund that’s pushing for fast growth. In that scenario, buying companies in distress within your segment can be a much faster way to achieve your goals. In those cases, building isn’t always ideal because organic development takes time. But if you have the resources to snap up struggling companies, you can accelerate growth significantly.

What role do integrations with third-party products play in your product?

Enterprise B2B companies bring their tools with them. They expect you to plug into their existing systems because their business logic is deeply intertwined with these tools, and the cost of consolidating or switching products is often prohibitively high.

At GitLab, we’ve made it a point to integrate with multiple solutions to ensure the enterprise adoption journey is smooth and successful. In other companies I’ve worked with, providing wide developer kits and open APIs—and allowing people to publicly develop against those APIs—was critical. That’s just how the enterprise B2B space operates.

Closing remarks

Throughout our conversation, we’ve explored what product-market fit truly means—how it’s not just about initial traction but about sustained customer demand and engagement.

We debunked the myth that product-market fit is permanent and discussed how companies can lose it due to market shifts, economic downturns, or technical scalability issues.

Real-world examples, from Netflix’s evolution to Slack’s pivot, highlighted the importance of adaptability in achieving and maintaining product-market fit. We also covered the role of key metrics like retention, revenue, and qualitative customer feedback in assessing whether a product is truly resonating with its market.

Lastly, we emphasized the power of experimentation, iteration, and listening to customers in shaping products that drive real value.

Whether you're a startup founder or a product leader, the key takeaway is clear: stay close to your users, measure what truly matters, and be willing to pivot when needed.