Why Product-Led Companies are Leaving Money on the Table

Product-led growth (PLG) has turned traditional sales on its head.

The jig is up—no more pitch decks and discovery calls disguised as demos. SaaS companies have replaced them with free trial sign-ups and freemium products.

This puts buyers directly in the driver’s seat—exactly where they want to be. It also locks go-to-market teams out of the buying process.

Sellers no longer hold the keys to the product, but they get a massive amount of leads in return. That’s the idea, at least.

The trouble is, not all leads are created equal. Without full visibility into buyer identity, intent, and context, you can’t separate today’s trialists from tomorrow’s six-figure deals.

And that puts a cap on growth.

Scale is the Stumbling Block

Contrary to popular belief, sales teams haven’t gone extinct.

Sure, credit card transactions will kick-start your growth. But even the most braggadocious self-serve companies (the ones that like to claim that “the product sells itself”) know you need a sales team to hit revenue at a scale that the public market recognizes.

PLG products have lower conversion rates than their sales-led counterparts. Human touch is necessary to grow revenue efficiently and predictably.

There’s no shame in it. Just take a look at Atlassian and Figma—two self-serve behemoths with massive sales orgs.

So it’s no surprise that 69% of up-and-coming PLG companies have an enterprise offering—and that nearly half of them are investing in sales headcount. It’s the only way to scale revenue.

What is surprising is how many PLG companies are setting their sellers up for failure.

Intent Needs Identity

Product-led companies power their sales plays using product data.

This isn’t a bad thing (quite the opposite!), but it’s not enough.

Product sign-ups show intent, yes, but identity and context are key to separating the high-ACV deals from the small potatoes.

Product-led growth obscures this. The whole point is that users can give your solution a spin without having to deal with sales gatekeepers.

The result? Sellers get disconnected from product users and struggle to hit their lofty quotas.

Imagine you’re an AE at a PLG company.

Someone signs up for a free trial. Great, another record gets added to the thousands sitting in your CRM.

There’s a very good chance this user signed up with a personal email address, so you don’t know that they work at a company that matches your ideal customer profile.

You end up drinking from a fire hose of product data in a sea of new users, many of which have no intent or budget to justify a conversation with sales.

Finding signals in the noise becomes a guessing game. Is this person the economic buyer? What’s the context for their test drive? When should you reach out? Where should you reach out?

You can find all this out on your own…theoretically. Firmographic information is available via Google search and enrichment providers. Product usage data is up for grabs in your data warehouse.

But connecting the dots takes serious legwork, and sellers can’t spend all day filling in the gaps. Sales teams know how to work SQLs (sales-qualified leads), not SQL (structured query language).

The situation is even worse for commercial open-source software companies. They don’t just offer a free trial—they hand over the source code.

Pretend you’re an SDR at a startup with an open-source product. You don’t even have product data to work off of, so you’re crawling through GitHub to see if you can scare up prospects.

A user keeps submitting pull requests to your repo. They’re clearly using your product. They might even make a great paying customer.

But you don’t know who they are, where they work, or whether they’re a good fit. If you’re lucky, you might have a first name to work with, and after Googling or scouring LinkedIn, you might find that person’s full name and see where they’re employed.

There’s no guarantee that they’ll fit your ideal persona, but let’s say that they do. Excellent.

Unfortunately, you have no context for where they are in the customer journey or if they’re even the person you should be talking to at their company.

Are they a forever hobbyist or part of a team spec’ing out a new project? How should you personalize your outreach to increase the chance of conversion?

You can dig into their GitHub activity to try to put the pieces together, but this is a painstaking process.

Now try doing it for all the active users in your repo.

The promise of PLG is that it will bring users directly to your doorstep so you can pick and choose who to focus on. But the more traction your product has, the harder it is to know where to spend your time.

It’s possible to take publicly available data and stitch together high-intent user signals with the identity of the user behind them. The hard part is doing it at scale across every user touchpoint.

Sales teams are still working to cobble together native tools and point solutions that only partially solve the problem.

Light Up the Dark Funnel

Most of the customer journey is happening across channels you don’t own or have visibility into. 

Companies with a self-serve model gain traction across widely dispersed watering holes— LinkedIn, Reddit, GitHub, you name it. People come together in these channels to ask questions, swap stories, and source solutions.

This activity doesn’t just fuel product awareness, activation, and adoption, it generates high-value signals that can tell you who your users are, whether they’re the right fit for your product, what problems they’re trying to solve, and a whole lot more.

The question is: How do you take an ocean of digital activity and connect it to the people and accounts you care about?

Answer: You centralize it, combine it, enrich it, and democratize it so your sales team can take the right action with a. the right people, b. at the right time, and c. using the right context.

It’s different for every product, but the magic happens when you combine those hard-to-see signals with the product and customer data you already have.

When digital interaction, product usage, and customer relationship data all coalesce, it gives you the full view of the customer.

Sales reps only have 5% of a buyer’s time, according to Gartner. The other 95% is a black box.

Product data is only one piece of the puzzle for PLG companies. Meanwhile, many open-source companies don’t even have that piece to work with (there’s no full-proof way to know who’s downloading your code from a repo, or when, or if you should even care).

By identifying, unifying, and mapping every individual’s interactions across all the channels and platforms they participate in, you get a holistic view of their customer journey and product experience.

More importantly, you understand how their activity and role-type ladder up into the larger picture of the organization they work for.

Intent is just the starting point, and product usage is only one type of intent. Sales teams need full visibility into every facet of buyer identity, intent, and context.

Product-led growth has opened up the floodgates. There’s no going back. 

Modern customers have control over the buying experience, and they clearly prefer self-service. You have to decide if you want to adapt to this new paradigm or keep living in the dark.

If you’re a PLG company, you have an unfair advantage: People who love your product and aren’t shy about advocating for it across channels.

If you’re only arming your sales team with product data, you’re taking away their competitive edge.

Common Room puts you in the driver’s seat of the modern customer journey. Tap into product usage trends, social intent, community conversations, and more to grow fast.