
Product-market fit is probably one of the most overused phrases in the startup ecosystem.
Founders say they have it when customers like the product. Investors say they are looking for it before writing the next cheque. Employees talk about it when growth starts accelerating. But liking a product, getting a few customers, or even growing quickly for a period of time does not necessarily mean a company has found product-market fit.
At its simplest, product-market fit means that a company has built something that solves a meaningful problem for a sufficiently large group of customers—and has found a repeatable way to acquire those customers, retain them and build an economically viable business around them.
That last part matters. A product can solve a real problem and still not have product-market fit. A founder may have ten customers who absolutely love the product. But if every new customer requires a different pitch, a heavily customised product, a personal introduction from the founder and months of negotiation, the company has found something valuable—but not necessarily something repeatable.
The harder question is whether the company can acquire many more customers like them, repeatedly and predictably.
One of the easiest traps for an early-stage founder is confusing customer love with market demand.
Imagine a founder builds a workflow product for large Indian enterprises. The first five customers are enthusiastic. They use the product every week, give detailed feedback and ask for additional features. It is tempting to declare victory.
But now ask a different set of questions. Can the founder identify another hundred companies with the same problem? Do they have the same buyer? Can the company explain the value proposition in a sentence? Can a salesperson other than the founder sell it? Does the product work without significant customisation? Do customers continue paying after the initial enthusiasm wears off?
These questions begin to separate product-market fit from product-customer fit.
Early B2B sales are often about transferring the founder's enthusiasm to the customer. That can help a company land its first few accounts. But a real business eventually needs a repeatable process that works beyond the founder's personal network and charisma.
This is why we prefer to think about PMF as a combination of customer pull and business repeatability.
There is no single metric that proves PMF. Instead, there are several signals that become stronger when they appear together.
The first is demand. Are customers actively looking for the product, or does the company have to persuade them that the problem exists? Strong products tend to create some degree of pull. Prospects return, referrals begin appearing, sales cycles shorten and customers start asking when they can get access.
The second is retention. A customer signing a contract is not PMF. A customer continuing to use the product and pay for it is much stronger evidence.
This is particularly important in software. Early revenue can be misleading because founders can personally drive sales and customers may tolerate an immature product. Cohort behaviour tells a more useful story. If customers acquired six or twelve months ago are still using the product, expanding usage and renewing contracts, the evidence for PMF becomes considerably stronger.
The third is repeatability. Can you acquire the next ten customers using roughly the same proposition, targeting a similar buyer and solving a similar problem?
This is where many startups discover that what looked like PMF was actually a collection of individual successes.
The fourth is economics. Customers must value the product enough to pay an amount that can support the cost of acquiring and serving them. A business that requires enormous implementation effort, deep discounts or endless founder involvement to generate each rupee of revenue may have demand without having a viable business model.
And finally, there is scale. The problem needs to exist in enough customers to support the ambition and valuation being built around the company.
Chargebee is a useful example of why PMF is not simply a box a company checks once.
The company reached its first $1 million in revenue at an average contract value of roughly $3,000. That was evidence that customers were willing to pay for the product and that there was a viable market at that price point.
But when the team looked at what it would take to build a $10 million business, the maths became different. At the existing ACV, the company would need an enormous number of customers. The team concluded that it needed to move upmarket and reach roughly $10,000 ACV.
That required more than simply changing the price. Chargebee had to build the enterprise capabilities necessary to sell at that level and demonstrate that the sales motion worked repeatedly.
That is an important lesson for Indian startups. PMF is relative to the business you are trying to build.
You can have a product that works beautifully for small businesses and still not have product-market fit for an enterprise strategy. You can have PMF in one geography and struggle to replicate it in another. You can have PMF at one price point and discover that the economics break when you try to move upmarket.
Locus provides another useful B2B example.
Logistics is an enormous industry, but size alone does not create a business. Locus had to identify specific operational problems where software could create measurable value for customers—better routing, improved efficiency and lower logistics costs—and then identify the companies for whom those improvements were sufficiently valuable to pay for.
That is why customer segmentation matters so much in the early stages. Defining an ICP requires understanding the different personas involved in a purchase and mapping the problem to its business impact. The technology itself is rarely the reason a B2B buyer signs a contract. The buyer wants to know what changes for the business.
A useful test for any B2B startup is therefore: Can you quantify what your product does for the customer?
Does it increase revenue? Reduce costs? Save employee time? Reduce risk? Improve conversion? Make an existing process dramatically faster?
The clearer that answer is, the easier it becomes to distinguish a genuinely valuable product from one that customers merely find interesting.
The Indian startup ecosystem also provides plenty of reminders that a compelling product or large user base does not automatically translate into PMF.
Toplyne, for instance, shut down in 2024 after about three and a half years. The company itself said it had not been able to reach the scale or product-market fit it was looking for.
Bluepad also shut down after its founders concluded that they could not see a sufficiently strong need or a reliable long-term monetisation model.
These examples are important precisely because they prevent us from turning PMF into a simplistic growth story. A startup can have talented founders, a technically sophisticated product, early users and substantial investor interest—and still fail to find a sufficiently strong combination of customer demand, retention, monetisation and repeatable growth.
Koo is a useful example of why we should also be careful about retrospective diagnosis. Its shutdown in 2024 followed failed partnership discussions and high technology costs. It would be too simplistic to describe that purely as a failure of product-market fit.
The lesson is not that every failed startup lacked PMF. It is that a startup needs a durable business model around whatever product-market fit it finds.
Perhaps the most important misconception about product-market fit is that once you find it, you have it forever.
Markets change. Customers change. Competition changes. Distribution changes.
Paytm Wallet had strong product-market fit at one point, only for UPI to fundamentally change the market. Clubhouse similarly experienced extraordinary product pull before that momentum faded. PMF therefore has to be continually defended and re-earned as the market evolves.
This is particularly relevant for Indian startups operating in fast-changing categories. A regulatory change, new platform, cheaper competitor or new distribution channel can fundamentally alter the economics of an otherwise successful product.
So the right question isn't simply:
“Do we have PMF?”
It is:
“What evidence tells us that customers still need this, will still pay for it, and that we can still acquire them efficiently?”
There is no magic percentage of retention, NPS score or revenue number that declares PMF.
Instead, look for a pattern.
Customers should be able to explain why they bought the product. New customers should resemble existing successful customers. The product should require less persuasion over time, not more. Sales conversations should become more predictable. Retention should improve as the product matures. Referrals and inbound demand should begin contributing to growth. Pricing should reflect the value being created. And most importantly, the company should be able to repeat the motion without reinventing the business for every customer.
When a startup is struggling, founders should not immediately assume that the product needs to change. Sometimes the problem is the message. Sometimes it is the channel. Sometimes the company is selling to the wrong persona. And sometimes, yes, the product itself needs to change.
That distinction matters because changing the product is usually the most expensive response.
If customers understand the problem but don't respond to your message, you may have a positioning problem. If the right customers respond but your acquisition channel is too expensive, you may have a distribution problem. If users love the product but the economic buyer doesn't care, you may have a persona problem.
Only after eliminating these possibilities should you conclude that the underlying product isn't solving a sufficiently important problem.
At Malpani Ventures, we think founders should be somewhat uncomfortable when they say, “We have PMF.”
Not because PMF doesn't exist, but because it should be demonstrated through behaviour rather than declared through a slide.
We want to see customers who genuinely need the product, who pay for it, who stay, and who look sufficiently similar that the company can find more of them. We want to understand why those customers buy, what economic value they receive and whether that value is large enough to support a healthy business.
A startup doesn't find product-market fit because ten customers say they love it. It finds product-market fit when customer demand becomes a pattern rather than a collection of anecdotes.
And once that pattern exists, the next challenge is turning it into a repeatable, profitable and scalable business. That is when a startup stops asking, “Can we sell this?”
And starts asking the much more interesting question:
“How many more customers like these can we serve and can we do it without breaking the business?”