Updated: October 8, 2026
"Do more with less" is the new expectation for go-to-market teams. It's a hard one to follow. That's why more teams are turning to signal-based selling.
Prospects are less responsive. According to Gartner, 67% of B2B buyers prefer a rep-free experience. A separate Gartner survey found that 73% of B2B buyers actively avoid suppliers who send irrelevant outreach.
That's exactly why relevance and precision matter more than ever. And both workforce contractions and technology stack contractions are limiting the pool of potential customers: The average company now runs 106 SaaS apps, down from 112 in 2023, according to BetterCloud.
Enter the signal-based GTM motion: the new standard for any team responsible for finding, closing, growing, or retaining revenue.
Capturing buying signals allows you to identify who's in-market (or who's about to be), prioritize accordingly, and take action with context. In short, it helps you prioritize the right people and accounts with the resources you already have.
But signals themselves aren't enough. You have to be thoughtful to deliver real results and do so efficiently.
So, without further ado, here's how to run a signal-based selling strategy, from selecting your signals to scaling what works. And don't forget to check out the recording above from our friends at RevGenius if you're more of a visual learner!
What Is a Signal-Based GTM Motion?
A signal-based GTM motion (also called signal-based selling) means using real buyer signals to trigger relevant, personalized outreach at the right moment. Those signals include job changes, website visits, product usage, and community and social activity.
Instead of sending the same generic message to a static list, you reach people when their behavior shows they're actually in-market. That makes outreach feel timely and useful rather than interruptive, and it puts your reps in front of the buyers most likely to respond.
Select the Right Signals (aka the What)
The most common question people have is: Where do I start?
The answer is: It depends (the worst answer, we know).
The most important thing to keep in mind is this: you have to maximize the overlap between your audience and your offer. Your audience is the signals generated by high-fit buyers and customers. Your offer is the relevance of your response to those signals.
This is what allows organizations to deliver on the core goal of go-to-market: right person, right message, right time.
Those signals can come from the channels you already rely on, from social and community to product, code collaboration, and CRM. The point isn't to chase more data; it's to turn the activity you already have into prioritized action.
The signals you choose will differ depending on your go-to-market motion. Here's a methodology every organization can use to zero in on the right ones:
Brainstorm Signal Options
First, list out all possible options based on your digital ecosystem (browse our signal guides).
Some common examples include:
- Customer or champion job changes
- Economic buyer activity
- Surges in product usage
- Social content engagement
- Questions in owned communities
- Pull requests in open-source repositories
Compare Signal Volume and Conversion Rates
Next, map out these signals based on volume and conversion rate.
You can do this using a simple spreadsheet:
- Column A: Signal
- Column B: Frequency of signal among your ideal customer profile (use historical data if possible)
- Column C: Baseline conversion rate of signal to pipeline
- Column D: Estimated pipeline impact of signal
- Column E: Level of difficulty in executing on signal (we'll come back to this one in a bit)
Then plot these signals on a graph.
Generally speaking, the higher the volume, the lower the conversion rate.
There's a good chance your organization already has automated processes in place for low-volume, high-converting signals (think demo requests on your website).
High-volume, low-converting signals are an area of opportunity. But they may require a lot of overhead in terms of capturing and executing on them (this is where column E comes in).
Kick things off by focusing on "easier" signals that strike the right balance between volume and conversion rate.
You want to start by validating signal efficacy. Choosing a handful of signals from this "golden zone" will help you balance effort and outcome.
It pays to be picky here. Across the hundreds of GTM conversations we have with teams each quarter, email reply rates hover around 1% and call connect rates sit around 2.5%. And according to Salesforce, reps spend 70% of their time on non-selling tasks like research and admin.
Picking the highest-value signals is what makes the effort pay off.
Group Similar Signals Together
Once you've got enough signals to work with, group them together based on channel or category.
This will help you determine which signals are easiest to track versus the ones that may require technical assistance or new tooling.
Plus, signals that fall within the same bucket will likely share similarities in terms of messaging patterns.
For example, outreach might call out a product trigger and share information about an inferred use case. That kind of messaging could apply to multiple signals related to product usage.
Match Messaging to Different Signals
Finally, craft compelling messaging based on the context of each signal.
Say the signal is someone visiting an integration page on your website. Your outreach may include a customer story that details how that integration is used.
Say the signal is product users hitting a usage threshold on their current plan. Your outreach may include an offer to walk users through different plan options before they lose access.
Say the signal is an economic buyer engaging with one of your competitors online. Your outreach may include a comparison of your two solutions, or user reviews that highlight the differences between your products.
Remember: The more overlap there is between the signal and the relevance of the messaging, the better your conversion rate will be.
Scale What Works (aka the How)
It's helpful to approach your signal-based selling plays with a crawl-walk-run framework in mind. This way you can test individual plays without a ton of overhead and scale the winners over time.
Crawl (Completely Manual)
The idea in this stage is to run a proof of concept so you can get a feel for what works. To quote Paul Graham: Do things that don't scale.
Here's a real-world example:
We found an influencer on LinkedIn who publishes content about problems our product can solve. We looked through the comments and reactions on one of their posts.
Next, we filtered out individuals who don't fit our ideal customer profile (ICP). Then we sent a DM to qualified individuals referencing the post and their interest in it.
Something like this is tedious, sure, but it's not terribly time-consuming and it doesn't require any extra tooling. It's something the average rep could do today without any help from other teams.
Walk (Last-Mile Human Touch)
The idea in this stage is to move forward with plays that generated positive results in the crawl phase. You can automate signal capture while still maintaining control over last-mile action.
Continuing with the example above, we automated the process of finding and segmenting people in our ICP who engage with relevant LinkedIn influencers.
We added people who interacted with certain posts (including their profile URLs, the actions they took, and so on) to a spreadsheet using Zapier. We then uploaded that sheet to Common Room, which automatically enriches identities and matches people to specific accounts.
Common Room automatically adds individuals who match our ICP to a dedicated segment for "socially engaged" prospects. This segment acts as a prioritized list for our reps. We refresh it daily so our sales team can add individuals to hyper-personalized Outreach sequences.
Common Room eliminates the heavy lifting of researching and prioritizing people and accounts, but there's still an element of human review.
Run (End-to-End Automation)
The idea in this stage is to turn qualified signals into timely action without manual handoffs. You can automate the end-to-end journey from signal to action with zero human input.
We haven't reached this stage with the example above (yet), but here's another real-world example:
We pump website pricing page activity directly into Common Room. Using our identity resolution and enrichment engine, Person360, we automatically filter out anyone who's not an economic buyer. We also cross-reference this activity with account ownership for different opportunities.
Using customizable automations (we call them workflows at Common Room), we add individuals who meet our criteria to Outreach sequences. These sequences are personalized based on their actions on the page, all without human intervention.
This is a play that allows us to go after low-hanging fruit and grow revenue on autopilot. And because the pieces are already connected, we can deploy new plays in hours, not weeks.
Start Stacking Signals
No matter the play, you'll eventually hit a ceiling on efficacy.
This doesn't mean you should stop running a play, but it does mean you should explore one of two options:
- Optimize your messaging to improve conversion rates (this is where you should start).
- Expand your aperture by creating new signal-based plays.
You can revisit the crawl-walk-run framework for each new play to test, optimize, and templatize.
Then, when that signal shows signs of reaching maximum potential, you can start to layer on more.
Lather, rinse, repeat.
Common Room Helps You Operationalize Your Signal-Based Selling Strategy
You don't need Common Room to take a signal-based selling approach to GTM.
But it helps. A lot.
Here's how.
Digital Signal Capture
We autocollect signals from hard-to-capture corners of the internet. We provide natively built and fully managed integrations with dozens of data sources: website, product, CRM, social, community, open-source, and more.
Unified Identity and Account Intelligence
We unify every signal into a single profile for every person and account. We build out these profiles by combining our proprietary 400M+ contact directory with your first-party data and real-world buyer signals. Our own AI-powered Person360 identity resolution resolves all of it to real people and accounts.
Most intent tools stop at the account level, flagging that "some company visited your site." Person360 resolves that activity to the specific person, so reps know exactly who to reach out to.
GTM teams get full visibility into the customer journey. They also get a 360-degree view of everyone associated with a given account (multithreading for the win!).
Actions and Automation
We help GTM teams act fast with user-friendly actions and automations. Improve speed to lead with real-time sales alerts, and streamline prospecting with automated segmentation. You can also take timely action on prioritized buyers with flexible workflows, and a whole lot more.
Best of all, we offer a free self-serve version you can test out for free.
Happy signal spotting.
Signal-Based GTM Motion FAQs
What Is a Signal-Based GTM Motion?
It's using real buyer signals, like job changes, website visits, product usage, and community activity, to trigger relevant, personalized outreach at the right moment. Instead of sending the same generic message to a static list, you reach people when their behavior shows they're in-market. That makes outreach feel timely and useful rather than interruptive.
How Is a Signal-Based GTM Motion Different From Traditional Outbound?
Traditional outbound works from static lists and generic messaging, whether or not a buyer is paying attention. A signal-based motion waits for real behavior, then matches the message to the context behind each signal. The result is outreach that lands when buyers are most likely to respond, so reps spend less effort for more pipeline.
How Is Signal-Based Selling Different From ABM?
ABM focuses on a predefined list of named accounts you've decided to pursue. A signal-based motion engages people and accounts showing real buying signals right now, whether or not they were ever on that list. The two can work together, but the signal-based approach follows intent instead of a fixed roster.
How Many Signals Should You Start With?
Start with a handful. Choose signals from the "golden zone" that balance volume and conversion rate, then validate that they actually drive pipeline. Once a play proves out, you can layer on more over time.
Does a Signal-Based GTM Motion Replace Outbound?
No. It makes outbound more effective by focusing your reps' effort on buyers who are showing real intent. You're still reaching out, you're just doing it with context and timing on your side.
Build a Better Signal-Based Selling Motion With Common Room
Request a demo or get in touch to see how Common Room helps you rapidly build, iterate, and automate a signal-based GTM motion.