The Power of Signal-Based Selling for PLG Companies

👋 Hey there, Drew here!

Welcome to TheProductLed’s guest post edition where I asked someone I enjoy learning from to write something they're passionate about.

During my time on the growth team at Netlify, I was learning about Product-led Sales (PLS) as the industry of PLS was finding its own PMF. I spoke to several of the PLS companies during that time…one of them being Pocus. Alexa Grabell and I had a great first conversation and since then, we’ve kept in touch ever since.

I’ve closely followed Alexa and her incredible journey leading one of the top PLS companies: Pocus.

I admire their website strategy, their strong GTM motion of top-down selling (only), their strategic marketing of being a thought leader in product-led sales, and most interesting, the strong brand Alexa has been building from the start.

I asked her to share her passion → why signal-based selling is so important for PLG companies, and I can’t wait to share what she’s written.

Enjoy! 👇️ 

I’m Alexa, the Co-Founder and CEO of Pocus. Pocus is mission control for your pipeline. Our platform brings together product usage and other intent signals (marketing, customer, and 3rd party intent data) to surface top leads, enabling reps to act fast. 

Before starting Pocus, I led sales strategy and ops at Dataminr where I worked with both leadership and reps to help them hit revenue goals. During this time, I noticed a recurring theme: go-to-market teams need data to do their jobs well, but often have the least access. They spend tons of time toggling between browser tabs and tools to find the data they need or working with Revops to cobble together DIY solutions, just to find the signals that matter most. And that’s if they’re lucky enough to get technical resources to help. Then, if and when they get the data, it’s difficult to distill it down into clear signals and actionable playbooks. 

We believe knowing your buyer, understanding their journey, and using signals (not your rep's best guess) to strategically engage should be the standard playbook. 

In this newsletter, I’ll walk through the process of setting up a signal-based playbook system, step by step, using the principles we’ve fine-tuned at Pocus. 

What is signal-based selling?

Ask any GTM team what their number one challenge is and you’ll hear the same answer over and over: efficiently and effectively driving pipeline. 

Companies are finding it increasingly challenging to connect with their target audience as traditional volume-based outbound loses efficacy. Simply put, we know the old-school spray-and-pray approach doesn’t work like it used to. Personalization and precision are key (hint: personalization isn’t just referencing a first name or city).

One of the most impactful ways to personalize outreach is to integrate key signals from your target audience using a go-to-market framework called signal-based selling. The top PLG companies are empowering their sales teams with actionable insights derived from product usage, marketing engagement, intent signals, and community interactions.

These signals drive conversions, increase average contract value (ACV), foster expansions, and enable PLG companies to go upmarket with higher-tier offerings.

But what does signal-based selling look like in practice? Let’s start from the beginning.

Why do signals matter?

Taking a step back, let’s define what signals are. At their most basic level, signals are data points that indicate a customer or lead’s intent, behavior patterns, or mindset. When these signals are properly interpreted and surfaced, they can help GTM teams understand when and why they should reach out to contacts.

Consumer brands have used signals to drive e-commerce sales for years. For example, when you browse items on a retailer’s website they use that behavior as a signal that you’re interested in a specific style or category of clothing. From there, they may serve you ads or send an email to remind you about the item and nudge you to buy. 

In B2B sales, signals can run the gamut from heavy product usage as an indicator of seat expansion opportunity, to a recent influx of support tickets from an account acting as a warning flag that the customer is at risk of churn.

Signals that are easier for a sales team to act on are product interactions. However, a product champion moving to a new company or leaders from target accounts engaging with relevant content on LinkedIn could be harder to surface.

If the right signals are complicated, why bother trying?

The importance of this data can’t be overstated because buyers are becoming savvier where they expect relevant and personalized messaging with a bespoke purchasing experience. Traditional volume-centric approaches don’t resonate with modern customers who want to understand how solutions will address their specific needs and pain points.

By embracing signal-based selling, companies can forge deeper connections with their audience. Signals serve as invaluable indicators of customer intent, enabling sales teams to prioritize their efforts and engage with prospects more meaningfully.

Let’s dive into common pitfalls when integrating signals into your GTM selling motion and how to avoid them.

Common challenges when making the switch

GTM teams run into two main challenges when transitioning from traditional outbound tactics to a more precise signal-based approach.

#1 Leadership needs to have a clear perspective 

At the leadership level, the number one challenge is having a defined perspective on the team goals, who they’re targeting, and which signals should be prioritized — including why they believe these signals matter. 

SaaS companies generate a massive amount of data, which can lead to a lot of noise. Add that to the dozens of enrichment and CRM tools you can layer on, and identifying the most important signals can become a struggle. 

Once key signals are prioritized, leaders face the challenges of building training programs to equip sales reps with the knowledge to appropriately act these signals. Reps need coaching on how to interpret signals effectively and build compelling narratives with customers and a business-level case for the product. Without a clear viewpoint on why signals matter and how they’ll be used, leaders will fail to secure the buy-in they need from their team, and outbound efforts will flounder rather than flourish.

#2 Reps need the right data, at the right time, without having to dig.

On the frontline, sales reps face hurdles in accessing relevant data and signals promptly. In some orgs, sales is siloed from key data, relying on an analytics team to provide context or marketing to drive signal-based interactions while they focus exclusively on generic high-volume playbooks. 

Some GTM teams might have access to signals, but it’s scattered across various tools, spreadsheets, and dashboards making it hard to synthesize insights and take action. Tedious processes that decrease a rep’s productivity become deprioritized and by the time they surface the information they need, the signals have become stale. This creates a reinforcement loop where the signals they may have been told to care about don’t drive impact and reps learn to see them not as helpful data but as a distraction.

How to implement signals, step-by-step

This step-by-step guide will walk you through the four key phases of signal implementation:

1. Understanding your key business pillars

2. Identifying your goals

3. Choosing your signals

4. Validating and launching your playbooks

Let’s get started building a more relevant, data-informed GTM strategy. 

Understand your key pillars

To implement a successful signal-based GTM strategy, you must understand your target market, ICP, and unique value prop. Here are some questions to ask yourself to help find the right strategy:

1. What is the main challenge or problem your product solves?

2. Who would benefit most from your solution? Who would value your solution most?

   • A simple way to tackle this question is to consider your best customers. What common attributes (size, industry, country, growth rate) do they have in common?

3. How do you solve their problem better than any other solution?

   • It’s also important to consider how and why your solution is better than the free and easy option of “just doing nothing.”

Identify your goals

Once you’ve identified the pillars of your strategy, consider your business goals. We can bucket most goals into one of five categories:

1. Assist: Get customers to value or Aha! moments as quickly as possible.

2. Conversion: Convert leads to paying customers or free/trial customers to paid customers.

3. Expand: Increase an existing paying customer’s spend, including adding more seats, moving into a higher plan tier, etc.

4. Consolidate: Move splintered accounts at the same company onto one contract.

5. Defend: Get customers to renew more proactively than typical churn prevention. 

Goals are heavily influenced by which GTM motion you use.

PLG companies are often most focused on assisting customers to value and converting customers from free to paid.

Sales-led brands are typically working to convert leads to customers, with some defensive goals around contract renewals.

Hybrid PLS models often have the widest set of goals with different parts of the GTM team focusing on all 5 of the above categories. For example, a PLS company may want marketing to drive free-to-paid conversion, rather than devote salespeople’s time to close deals that could convert on their own.

When you’ve picked the goal or goals that are most important to your team, you can begin to identify which signals ladder up to each goal and think about how best to action them.

Choosing your signals

There are a variety of signals that exist in modern go-to-market. But, the challenge is knowing which signals matter and require action. Signals primarily come in two different forms: 

• 1st Party Signals: This is data you own that was collected from a user engaging with your product or a prospect engaging with your brand. Examples include customer data from a CRM, product usage data from the data warehouse, marketing engagement data like content downloads or event attendees, community engagement, etc.

• 3rd Party Signals: This is data from a 3rd party provider, typically a data vendor like Clearbit, 6Sense, Bombora, and others. Some of these 3rd party vendors explicitly sell “intent” to help you understand where there is a buying signal within your target accounts. Other providers offer firmographic data, funding data, tech stack, etc., that could help you infer intent or buying signals.

With this plethora of data, it’s important to think about which signals matter most to you and will help you achieve your goals. Not sure where to get started?

Let’s look at a few signals.

• Pricing page visits: Visitors to your website are not always the best signal. Content downloads or blog page views are typically not strong enough signals that someone is actively evaluating your product. Pricing page visits, however, are more intent than the average website visitor. 

• Job switcher: When a product champion changes roles and switches to a new job within a target account, use this signal as an opportunity to break into the new account or strengthen an existing deal.

• Reverse job switcher: If you’re trying to break into a new target account, check to see if you have any current product champions who used to work there. If so, this is a great opportunity to ask for an intro to their former colleagues.

• Product feature usage spike: If you’re a PLG company, you won’t find a higher intent signal, especially when combined with other customer fit and marketing engagement data. Feature usage spikes typically indicate an account deepening its relationship with your product and may indicate readiness for a higher-tiered plan or cross-sell to a new product SKU.

Tracking multiple signals that boil up to the same goal can help you identify even stronger prospects.

For example, let’s say you’re selling a dev tool with a focus on targeting warm leads for conversion. You might look for signals like contacts mentioning relevant keywords in dev communities or on LinkedIn, job postings from target accounts that mention tools like yours, and alignment with a target account’s current tech stack. With these signals, you would have a much stronger pitch when reaching out to your target account — especially if you weave some of these signals directly into your outreach.

Validating and launching your playbooks

We define a playbook as a signal plus a corresponding action.

The action in this case can either be human-driven by a member of your team or something you automate. 

For example, let’s say your company-wide goal is account conversion. You might develop a Free-to-Paid playbook targeting SMBs with 3 or more active product users and at least one user approaching a paywall. Once these signals are identified for an account, you could trigger an automated marketing sequence to convert this account from free to paid. However, a similar playbook for Enterprise conversion opportunities might have higher signal thresholds and surface the account in a rep’s inbox so they can start a direct, data-informed conversation with a decision-maker.

Typically, we advise our customers to run multiple manual experiments before moving any playbook fully to automation to validate its effectiveness. Keep improving your signal-based playbooks as you get more data and refine your process until you have a proven winner.

Here are some real-life case studies on companies that have implemented a successful signal-based selling playbook using Pocus:

1. Loom

2. Miro

3. Clockwise

Wrapping up

The journey from traditional outbound tactics to signal-based selling is not just a shift in strategy; it's a fundamental reimagining of how sales, marketing, and analytics intersect.

Key takeaways from this paradigm shift include:

- Precision over volume: Rather than casting a wide net, focus on targeting high-intent prospects with personalized messaging tailored to where they are in the evaluation or buying process.

- Warm outreach beats cold outreach: Leverage signals to identify warm leads and engage with them in a timely and relevant manner. Rather than waste time on cold outreach, test automated or marketing-owned lead warming.

- Practice data-driven decision-making: Leave the “best guess” approach behind and let data guide your sales and marketing efforts. This strategy enables you to adapt and iterate based on real-time insights. You may uncover your next winning playbook by reviewing the information you already have!

It’s time to ditch spray-and-pray outbound and embrace a more nuanced, strategic approach to sales by harnessing the power of signals.

You’ll be rewarded with new growth, deeper customer relationships, and a leg up in an increasingly competitive marketplace!

Thank you, Alexa!

For more from Alexa, be sure to connect with her on LinkedIn and visit Pocus.

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