Your customers who reach the core workflow use your product repeatedly. Support receives positive feedback. The engineering team keeps improving performance, and the few accounts that understand the product seem to genuinely value it.
But sales misses the target.
The pipeline is slow, demos do not convert, and prospects disappear after saying that the product looks interesting. Product believes sales does not understand what it has built. Sales believes the market does not understand why it needs the product. And marketing needs another quarter to improve the message.
A product can be technically good and commercially difficult. It can solve a real problem but take too long to show value. It can delight one user while confusing the person controlling the budget. Or it can generate a lot of activity without producing enough evidence that someone is ready to buy.
Good products do not sell themselves.
They create the conditions for a better sale.
A good product does not automatically create product-market-sales fit.
Product-market fit is usually treated as the final confirmation. The product solves a problem, users like it, and now the organization only has to scale.
But scale requires another kind of fit.
Andreessen Horowitz describes this as product-market-sales fit: the product, target market, and go-to-market motion must support each other. A complex enterprise product may require implementation, security reviews, procurement, and several stakeholders. A simple self-serve tool may need the user to experience value before speaking to anyone.
The same sales model will not work for both.
This is where many good products become stuck. The team proves that the technology works but does not prove why the buyer should change, where the budget will come from, or how the product will move through the organization.
One of the most useful questions raised in the a16z discussion is simple: How would the customer make the business case to their boss?
If the customer cannot answer that question, the product may be useful without being buyable.
The sales problem may begin inside the product.
Imagine that trial sign-ups are healthy, but most users leave before completing a meaningful workflow.
Sales may call them unqualified. Marketing may say the leads need nurturing. But the user has already entered the product and failed to experience its value.
That is not only a lead problem. It is, in reality, an activation problem.
Amplitude defines time to value as the period between sign-up and the first meaningful benefit. Its 2025 benchmark, covering more than 2,600 companies, found that 69% of products with strong seven-day activation were also strong three-month retention performers.
The distinction between activity and value matters.
A user can create an account, complete onboarding, and log in five times without solving the problem that brought them there. These actions make the dashboard look active, but they do not make the product easier to sell.
Before asking sales to improve conversion, ask whether the product provides an early and honest proof of value.
Product-qualified leads connect product value with sales timing.
Traditional lead qualification begins outside the product.
A marketing-qualified lead may download an ebook, attend a webinar, or visit several web pages. A sales-qualified lead may confirm the problem, authority, budget, or timeline during a conversation.
A product-qualified lead begins with a different form of evidence: the person has used the product and experienced some measure of value.
Pendo describes a PQL as someone who has achieved success using the product, not merely shown interest in it. This could mean creating the first useful report, connecting an important integration, inviting a team, reaching a usage limit, or repeatedly completing the workflow the product was designed to improve.
But there is no universal PQL event.
For a project platform, creating one task is probably too weak. Creating a project, assigning team members, and completing work may be more meaningful. For an analytics product, connecting data is necessary, but generating and sharing a useful insight may be the real value event.
The signal should answer two questions: –
- Has the user experienced the product’s value?
- Does their behavior suggest that help, payment, or broader adoption is the natural next step?
If the answer to only the second question is yes, the sales team may be arriving before the product has earned the conversation.
The B2B product is used by one person and purchased by another.
PQLs become more complicated in B2B because the most active user may not control the purchase.
An analyst may use the product every day. A manager may advocate for it. IT evaluates security and integration. Finance examines the cost. Procurement negotiates the agreement. And an executive sponsor wants to understand the organizational outcome.
Mixpanel warns that one power user can make an entire account look healthy. If one person creates nearly every report while the rest of the team remains inactive, the usage numbers can hide a fragile account.
This is why B2B companies should also think about product-qualified accounts.
A product-qualified account combines individual behavior with account-level evidence: –
- How many relevant people are active?
- Which roles are using the product?
- Is usage becoming broader and deeper?
- Has the product entered a recurring workflow?
- Is someone attempting to access features connected to security, collaboration, administration, or scale?
One user proves personal value. Several users, repeated workflows, and a visible business case begin to prove organizational value.
Product-led growth does not remove the need for sales.
There is a popular version of product-led growth where the product performs every commercial function. People discover it, try it, understand it, purchase it, and expand without speaking to anyone.
This can work for simple products and smaller contracts.
But enterprise buying introduces work that the product cannot complete alone.
McKinsey studied 107 publicly listed B2B SaaS providers and found that only a small group of product-led companies produced outsize performance. The stronger model was often a hybrid: the product creates demand and proof, while sales helps the customer navigate the larger purchase. In its survey of 625 SaaS buyers, 65% strongly preferred a combination of product-led and sales-led experiences.
Sales still has the vital role of communicating value. Of offering the consultative approach.
The salesperson can help the champion build an internal case, bring decision-makers together, answer security questions, structure a rollout, work through procurement, and connect product usage with a larger business outcome.
The product demonstrates that value is undeniable. But the salesperson is still the one selling it.
What should you do when the product is good but sales are not?
The answer is not to send every trial user to an SDR. Nor is it to assume that more product features will solve the revenue problem.
The organization needs to find where value stops moving.
1. Prove that the product is good with customer evidence
Positive feedback is useful, but it is not enough.
Look for repeated value, retention among activated users, willingness to pay, referrals, expansion, and customers who would struggle if the product disappeared. Speak with the users who stayed and the ones who left.
If customers enjoy the demo but do not return, the product may be impressive without becoming necessary.
2. Map the journey from discovery to revenue
Break the commercial journey into clear transitions: –
- Discovery to sign-up
- Sign-up to first value
- First value to repeated value
- Repeated value to a PQL or PQA
- Product qualification to a sales conversation
- Sales conversation to purchase
- Purchase to retention and expansion
A weak transition from sign-up to first value is not solved by more sales activity. A healthy activation rate with poor closing may point to pricing, positioning, procurement, or the wrong buyer.
Find the leak before selecting the solution.
3. Define the product-qualified event
Study the customers who retained, upgraded, or expanded. What did they do before buying? Which actions were common, and which only looked impressive on a dashboard?
Combine product attainment with customer fit and commercial intent. OpenView recommends looking at usage frequency, high-value feature adoption, growth in usage, firmographic fit, and actions such as requesting help or visiting pricing.
Treat the first definition as a hypothesis. Test whether PQLs actually convert and retain better, then revise the model.
4. Route different customers into different buying journeys
A small team with a simple use case may prefer self-service. A growing account may need sales assistance. An enterprise buyer may require a proof of value, security review, implementation plan, and direct commercial conversation.
Do not force every customer into the same motion.
The price, product complexity, organizational risk, and number of stakeholders should determine when a person becomes involved.
5. Give sales the context behind the signal
A PQL score without an explanation becomes another arbitrary number.
Sales should know what the account did, which users were involved, what value they may have experienced, where they became stuck, and why the timing matters.
The outreach should begin with curiosity: “Your team has started using this workflow across three projects. What are you trying to achieve, and is anything preventing broader use?”
That conversation feels different from a generic call made five minutes after sign-up.
6. Bring sales learning back into the product
Sales hears the objections that analytics cannot explain.
The buyer may like the product but lack a budget category. The champion may need an ROI case. IT may reject an integration. Procurement may find the packaging difficult. Or users may understand one feature while missing the broader value.
Product, marketing, sales, and customer success need one feedback loop around these problems.
The goal is not to prove which team was right. It is to make the next customer journey easier.
Atlassian understood that low-touch does not mean no-touch.
Atlassian became famous for growing through strong products, transparent pricing, and self-service purchasing. The story was often simplified into a company that did not need sales.
But as larger and more complex organizations adopted its products, Atlassian added people it called enterprise advocates. OpenView notes that these teams helped customers with questions and complexity that self-service could not resolve.
The product created adoption from the bottom up. Human support helped convert that adoption into an organization-wide purchase.
Sales did not replace the product-led motion.
It completed it.
Measuring product qualification is about finding proof of commercial value.
Businesses can begin with: –
- Activation rate: The percentage of users who reach the first meaningful value event.
- Time to value: How long it takes them to experience that outcome.
- PQL and PQA rate: How many users and accounts meet the qualification criteria.
- PQL-to-paid conversion: Whether product-qualified users buy at a higher rate.
- Account breadth: Whether value is spreading across relevant users and roles.
- Sales-assisted lift: Whether human involvement improves conversion, deal size, or speed.
- Retention and expansion: Whether qualified customers continue receiving enough value to stay and grow.
The PQL should be tested against revenue and retention. Otherwise, the organization risks creating another score that everyone reports and no one trusts.
Product qualification is value becoming evidence.
A good product is the foundation, not the complete commercial system.
The market must understand the problem. The user must experience the outcome. The buying group must justify the decision. And the sales process must help the customer move through whatever the product cannot solve alone.
Product-qualified growth does not mean sales disappears. It means sales begins with better evidence: when product behavior, customer context, and human judgment work together, the organization stops asking why a good product is not selling; rather, it begins learning exactly what must happen before it can.
