Signal-based selling in practice
AI sales signals are data-driven indicators derived from CRM activity, intent data, job changes, funding events, and external news that AI systems detect and score to identify which prospects are most likely to buy. The best signal-based selling teams don't wait for buyers to raise their hands. They act on signals that most reps never see, because they're buried in unstructured data, scattered across news feeds, or locked inside earnings call transcripts that nobody has time to read.
Two practitioners who have built their entire outbound motions around this approach are Tom Slocum, founder of sales consultancy The SD Lab, and Eric Nowoslawski, founder of outbound agency Growth Engine X. Their frameworks for reading and acting on signals are at the center of this article.
The productivity case for signal-based selling is real and sourced. Seismic saved 11.5 hours weekly per rep and saw a 54% productivity gain after deploying GTM Workspace. That's not time saved on dashboards. That's selling time recovered.
What are AI sales signals (and why humans keep missing them)
AI sales signals are the output of systems that continuously monitor accounts for behavioral, operational, and external changes, then score those changes by urgency and fit to surface the accounts most likely to convert right now. They go far beyond basic intent data. Where intent data tells you someone is researching, AI sales signals tell you why, who, and when to reach out.
There are four categories of signals that well-designed AI systems monitor:
Stakeholder Signals: Personnel changes and new decision-maker engagement. Examples: a new VP of Sales joins a target account, a champion from a closed-lost deal moves to a new company, an org restructure puts a new budget owner in place.
Operational Signals: Budget approvals, tech-stack changes, and calendar spikes. Examples: a company purchases a new CRM, fiscal year planning activity spikes, a new software contract shows up in technographic data.
External Signals: Competitor launches, regulatory shifts, and industry news. Examples: a competitor announces a product that directly competes with your prospect's current stack, a regulatory change creates compliance urgency, an earnings call discloses a strategic priority shift.
Intent Signals: Anonymous web behavior and content consumption patterns. This is where data signals marketing and sales intersect: anonymous visits to pricing pages, whitepaper downloads, and competitor comparison searches are marketing-originated behavioral signals that sales teams now act on directly.
The reason humans miss so many of these signals comes down to three systemic problems, not personal failures. First, cognitive overload: a rep managing 300 to 500+ accounts simultaneously cannot monitor all of them for signal events. They default to the accounts they already know. Second, unstructured data scatter: External and Operational signals live in news feeds, job boards, and call transcripts that CRMs do not natively ingest. There is no alert, no flag, no notification. Third, temporal latency: by the time a human notices a funding announcement or a competitor product launch, the buying window may have already opened and closed. AI systems operating continuously don't have this problem.
Funding signals: reading between the lines
Funding rounds are among the strongest signals for both sales and marketing teams. New funding suggests ongoing product development, imminent growth, and investor confidence.
But according to Tom Slocum, founder of sales consultancy The SD Lab, it's not enough for frontline salespeople to merely identify companies that have successfully raised new funding. There still has to be a compelling value proposition.
"We don't want to be the typical reps who say, 'Hey, just got funding, how are you?' But it is an indication that the timing is good," he says. "They want to either build a sales playbook and refine their sales motion, because they're about to double in size, or they hired 50 people and lost 20, because their onboarding wasn't there."
Most go-to-market teams understandably focus on new funding rounds as a signal when prospecting. But Slocum and his team at The SD Lab have been using ZoomInfo's GTM Workspace to identify adjacent signals that indicate potential opportunity.
"What I love about Copilot is that it shows companies decreasing in funding. That's a good signal for us. Why? Because that means it's hurting. Something's not working. They can't get the sales, the pipeline isn't moving. Our revenue accelerator and our lead gen can boost those results for them or come in and support them." [Note: ZoomInfo Copilot has since evolved into GTM Workspace.]
Eric Nowoslawski, founder of outbound agency Growth Engine X, agrees that funding can be a valuable signal for sales teams. Although Nowoslawski and his team look for funding round signals, they typically don't mention the event as a reason.
"I don't want to start every email with, 'Hey, congrats on your latest funding round,' because then you're just the same as everybody else. So we'll pick another relevant data point to bring up about the company, but use the funding round signal to build the overall list," Nowoslawski says.
Product launches: getting ahead of the problem
Nowoslawski and his team typically use product launch signals as a starting point for further research, especially opportunities to preemptively solve problems common when bringing new products to market.
"Usually, we see product launches as an opportunity to say, 'Hey, with this product launch, there could be problems you may not be sure how to solve. Let's talk about how we can take care of that,'" he says.
However, with hundreds of thousands of software products alone released every year, researching or responding to most of them manually simply isn't feasible. To solve this, Nowoslawski and his team use AI-assisted prospecting tools, including GTM Workspace, to scale their outreach motions while leaning on their expertise to personalize specific interactions.
"A lot of times, the messaging we create that goes along with product launch announcements is basically using AI to talk about the product launch, but then also saying, 'In our experience, these are the problems that often come with this type of launch,'" he says.
Product launches are a textbook example of External Signals: AI can detect them from news feeds and press releases at scale across thousands of accounts simultaneously, surfacing the ones that match your ICP before a human monitoring manually would ever notice them.
Account-fit score: start with clean data
With AI-driven account scoring in tools like GTM Workspace becoming standard practice for top-performing sellers, data accuracy has never mattered more. The old adage of "garbage in, garbage out" has never been more relevant, and sales leaders are quickly discovering that feeding poor-quality data to even the most sophisticated AI is a fast-track to failure.
The same principle applies to account-fit score, especially in increasingly automated sales workflows.
"First, you need to make sure your CRM is clean," Slocum says. "You have your customers outlined. You have the right titles for the people that you're closing deals with. I've worked at companies where we thought the ICP was one thing, and when we started closing deals and looked at the signatures, it's a title we weren't even targeting."
ZoomInfo, an all-in-one AI GTM Platform, provides the data foundation The SD Lab relies on to avoid these costly mistakes. They've already seen promising results from GTM Workspace's Account-Fit Score, using it to identify similar companies to existing clients as a starting point for further prospecting.
"ZoomInfo will start feeding you things that fit the most potential," Slocum says. "You want this title, this company size, this industry, and then Copilot will map everything that's currently in your CRM and say, 'Hey, this company actually looks like a really great fit for what you're doing.'" [Note: ZoomInfo Copilot has since evolved into GTM Workspace.]
After identifying strong account-fit matches using ZoomInfo's GTM Workspace, Slocum's reps surface companies in the same industry of similar size, revenue, and growth potential to clients they've already worked with. From there, they identify potential brand champions that can advocate for them internally, and refine their results using hiring plans, funding rounds, and other signals.
How ZoomInfo's GTM Workspace turns signals into pipeline
ZoomInfo's approach to AI sales signals rests on three interconnected capabilities: the depth and accuracy of its underlying data, the GTM Context Graph's ability to reason across that data, and the way GTM Workspace delivers actionable intelligence directly to sellers in the tools they already use.
The data foundation matters because signals are only as good as the data behind them. ZoomInfo's platform covers 500M contacts, 135M+ verified phone numbers, 200M+ verified business emails, and processes 1.5B+ data points daily. For reps dealing with bounced emails and wrong numbers (the daily friction that AE_PP_01 and AE_PP_08 describe so precisely), this isn't a spec sheet item. It's the difference between a signal that fires on a real decision-maker and one that routes to someone who left the company two years ago.
The GTM Context Graph is what separates signal detection from signal intelligence. It processes 1.5B+ data points daily, fusing ZoomInfo's B2B data with customer CRM records, conversation intelligence from Chorus, and behavioral signals into a unified reasoning layer. The result isn't a list of accounts that tripped a keyword threshold. It's a ranked, contextualized view of which accounts are most likely to convert and why. Thomson Reuters hit 115% quota attainment and saw a 40% increase in closed-won deals after deploying signal-driven selling with GTM Workspace, the kind of outcome that comes from acting on the right signals at the right time, not just having access to more data.
GTM Workspace delivers all of this to sellers without requiring them to leave their existing workflow. Account-Fit Score, Earnings Scoops, and buying group alerts surface natively so reps spend time acting on signals, not hunting for them across five different tabs.
Ready to see AI sales signals in action? Request a demo of GTM Workspace.
Pain points: relevance over personalization
Businesses don't invest in new products or services for its own sake. They do so to solve specific problems that are hindering growth. This makes pain points among the most valuable signals for frontline GTM teams, as they reveal the most urgent challenges facing a business and provide salespeople with a strong opening.
Most salespeople know that, when leveraging pain points in sales conversations, demonstrating a keen understanding of the prospect's problem and offering a relevant solution is crucial. However, according to Slocum, many salespeople miss valuable opportunities simply by approaching conversations the wrong way.
"Everybody talks about personalization," he says. "It's important, but it's not about your dog, your college, or anything like that. With pain points, it's about relevancy. How do we tie that into the prospects' world? It's about the cost of inaction."
Slocum recommends leaning into competitor research when leveraging pain points. Asking informed questions about specific challenges is an excellent way to demonstrate the in-depth industry knowledge the best reps should have. It also allows reps to adopt a more consultative role that can establish and build credibility and trust.
"If your solution can tie into that cost of inaction, then you have the opportunity to say, 'Hey, your revenue has decreased for the past six months and your headcount's going down with it,'" Slocum says. "'What are you doing to address that? Here's what we do to help companies that have been in this situation before, and here's what they got out of it once we were through that pain challenge.'"
However, according to Nowoslawski, it's crucial that salespeople think carefully (and act judiciously) when evaluating pain points as a signal.
"It's kind of creepy if you were to email somebody and say, 'Hey, the reason I'm reaching out is because my software told me you were searching for tech-stack consolidation. We don't call out that we built our list via intent data, but we do match the pain point with that intent data."
Part of the challenge when using pain points as a signal, especially for cold outreach, is knowing how to focus your messaging. Some prospects may have multiple pain points, and therefore be receptive to multiple messages, but casting too wide a net may result in lost opportunities.
"When you're sending a cold email, you don't quite know what you're walking into," Nowoslawski says. "Are they going to resonate with the fact that you can help them save money? Are they going to resonate with the consolidation play? Are they going to resonate with ease of use?"
His approach? Focusing the entire motion on a single pain point, to be sure the prospects are responding to a need that sellers are ready to address.
Earnings calls: AI surfaces what reps used to skip
Earnings call transcripts, as well as 10-K and other regulatory filings, can be an invaluable source of information for motivated sales reps, which makes their publication a valuable signal that reps should be quick to act upon.
However, these materials are often dense, complex documents, and even the most motivated salespeople only have so much time. Not so long ago, this was a considerable disadvantage.
"I used to have to fight with my AEs as a manager because my AEs would want my SDRs to do that admin work. 'Go read this report. Go watch this call,'" Slocum says. "And it's like, where do I have that time, I have to be prospecting?"
Today, AI-assisted sales makes accessing the insights contained within these materials easier than ever. Tools such as ZoomInfo's Earnings Scoops, available within GTM Workspace, can surface a wealth of information in seconds, giving salespeople a vital competitive edge.
Best of all, these insights can be identified virtually as soon as an earnings call transcript or regulatory filing is available, meaning frontline reps can make the pain points and growth goals surfaced from earnings calls the central focus of their outreach.
Earnings call transcripts are a prime example of External Signals: high-value intelligence buried in unstructured data that AI can surface in seconds.
Turning AI sales signals into sent messages: a repeatable workflow
Most platforms marketed as "AI sales agents" are functionally templated email senders. They take a trigger event, slot it into a pre-written sequence, and call it personalization. True AI signal capability requires a full six-step pipeline from detection to delivery. Here's what that looks like in practice for teams using GTM Workspace.
Continuous account monitoring: AI watches all accounts simultaneously for signal events across all four categories. This includes data signals marketing teams generate on the behavioral side, specifically Intent Signals like anonymous web visits and content downloads, that sales reps can now act on directly.
Signal detection and classification: When a signal fires, AI identifies which category it belongs to and scores it against the account's ICP fit. AI deal signals at the in-deal stage, such as a new stakeholder joining the buying committee mid-cycle, get classified differently from early-stage Operational Signals like a new software purchase.
Relevance scoring: Not every signal is worth acting on immediately. GTM Workspace's Account-Fit Score ranks signals by urgency and fit, so reps see the highest-probability accounts first rather than a flat list of everything that moved.
Intelligence synthesis: The GTM Context Graph fuses the detected signal with CRM history, conversation intelligence from Chorus, and behavioral data to surface a clear answer to "why this account, why now." This is the step that separates a useful alert from a noise notification.
Personalized message generation: AI drafts outreach anchored to the specific signal detected, not a generic template. The message references what actually changed at the account. Seismic's reps saw a 54% productivity gain and saved 11.5 hours per week once this step was automated inside GTM Workspace.
Rep review and send: The human reviews the drafted message, refines the framing, and sends. Steps 1 through 4 are where AI delivers the most leverage. The rep remains in the loop at steps 5 and 6 to ensure the message reflects judgment that no model can fully replicate.
The distinction matters operationally: if your "AI sales agent" only executes step 5, you're automating the last mile while leaving the most valuable work, signal detection, scoring, and synthesis, entirely manual.
CRM integration: making signals actionable inside Salesforce and HubSpot
The most accurate signal in the world doesn't move pipeline if it never reaches the rep. That's the operational failure mode AE_PP_02 describes precisely: intent signals exist in the system, but a configuration gap silently prevents them from surfacing to the field. The program looks functional from a management view. The reps get nothing.
GTM Workspace is built to close this gap. Signals surface natively inside Salesforce and HubSpot workflows so reps see Account-Fit Score updates, buying group alerts, and Earnings Scoops without leaving their CRM. No separate login, no manual export, no "check the other platform" friction.
For teams with non-standard buying motions, GTM Workspace also supports custom signal configuration. You define your own ICP-specific trigger events, and the system monitors for them. This is where data signals marketing teams have already collected, such as web behavior and content consumption patterns, become actionable for sales: those behavioral signals can be configured as custom CRM triggers so reps receive an alert when a target account crosses a threshold your team defined.
Spekit qualified pipeline 58% faster and saw 43% more leads turn into qualified pipeline after deploying GTM Workspace's signal-driven qualification workflows. That outcome starts with signals reaching reps in the tools they already use.
A practical three-step setup for any team starting from scratch:
Map your ICP trigger events: which signal categories matter most for your motion (funding, hiring, intent, stakeholder changes)?
Configure signal rules in your CRM or signal platform: define the thresholds and account criteria that should fire an alert.
Set rep notification thresholds: not every signal warrants immediate action. Calibrate alert volume so reps get actionable signals, not noise.
Hiring plans: what the job description really says
At first glance, hiring plans may appear to be among the most straightforward signals for GTM teams. Plans to increase headcount are understandably seen as a positive indicator of future growth, whereas reductions in headcount are typically seen as a reactionary measure to cut costs or in response to declining demand.
Although this is generally true, there is a great deal more information to be learned from prospects' hiring plans if you know how and where to look.
For Slocum and his team at The SD Lab, which specializes in helping early stage founders build bespoke, scalable outbound sales motions, hiring plans are among the most valuable signals because they indicate underlying pain points that are hindering growth.
"I love looking at an application portal and seeing that a prospect has had 150 applicants but that posting has been up for nine months," Slocum says. "Something's going on. You're not finding the right person. If I'm a sales leader, I want my team looking at hiring plans because if our product can support that new role, great, let's get in there, maybe it can even replace that role."
According to Nowoslawski, hiring plans can be an indicator of several additional positive signals, including heightened demand, greater investment in research and development, or anticipated growth.
In today's markets, however, it's no longer enough for frontline GTM professionals to use hiring plans as a simplistic one-to-one indicator. Instead, Nowoslawski recommends avoiding assumptions about hiring intentions and focusing on supporting the prospect through the challenges that often come with increased headcount.
"I used to be a job-board maximalist," Nowoslawski says. "But we've actually found that targeting people by job boards just doesn't matter. A lot of times, reps are like, 'They're hiring for graphic designers, they should totally use our graphic design software.' But that's not actually the right bridge, they might be hiring a graphic designer because they need new creative ideas, not new tools."
To identify solid opportunities for cold outreach, Nowoslawski and his team often use vacancy listings as a source of data on the challenges facing would-be clients, using AI to analyze thousands of job descriptions and surface potential talking points.
"We'll pull the actual listing of what they're hiring for and mine the job description for keywords using AI," Nowoslawski says. "Instead of saying, 'Hey, I saw you're hiring for SDRs, you should buy ZoomInfo or hire Growth Engine X,' we'll say, 'Hey, I noticed that you're hiring for an SDR. I checked out the job description and it said that they're going to be making outbound calls. Where are you currently sourcing your mobile numbers from? ZoomInfo has the best mobile numbers in the market.'"
Hiring plan analysis is a core Operational Signal use case: GTM Workspace can surface AI deal signals from job description patterns across thousands of accounts simultaneously, giving reps the talking points Nowoslawski describes without the manual research overhead.
Layoffs: a signal that something is broken
The past several years have seen some of the most turbulent economic conditions in recent memory. The tech sector, in particular, saw unprecedented layoffs in 2023 as businesses sought to recalibrate in the wake of the pandemic and the "new normal" that followed.
According to Slocum, layoffs represent an opportunity to revisit previous conversations, with the necessary tact and diplomacy, of course.
"Layoffs let you know that the cost of inaction happened. Something is broken. So if you've got a marketing strategy, solution, or service, go in and talk about that. Be more consultative. 'Hey, I see your layoff. Something's going on. We can help.'"
As a signal, layoffs can be indicative of more than simple overscaling. Heightened competition, poor product-market fit, and M&A activity can all result in broad reductions in headcount, all of which are valuable data points for frontline reps seeking to better understand their prospects.
Buying groups: track the committee, not just the champion
With investments in technology under greater scrutiny than ever before, it's little wonder that today's buying groups are bigger than they've ever been.
Data from sales consultancy Challenger indicates that the average B2B buying group has expanded from around five individuals in 2009 to upward of 10 as of 2019. In the enterprise, buying groups can be even larger, with IDG's Foundry reporting buying groups of almost 30 people in 2024.
These committees are also constantly changing as job roles and company priorities shift. Staying on top of the composition of your buying groups is doubly powerful, allowing sellers to connect with new decision-makers and track the moves of past buyers to new roles or companies.
"Buying groups is one of my favorite signals, I get Slack alerts on that all day long, and it is fantastic," Slocum says. "Buying group changes can be your best friend, because now you have a real pulse on when people are moving, where they're going, and you have a way to support that motion with them as they navigate the job changes."
GTM Workspace's buying group alert capability is what makes the Slack-alert workflow Slocum describes possible at scale: the system monitors committee composition changes automatically so reps don't have to.
Finding the signal in the noise
Not too long ago, salespeople had limited visibility into their prospects and markets. Today, the opposite is true, and discerning the signal from the noise is becoming increasingly difficult.
The four-category signal taxonomy in this article maps directly to what the best practitioners are already doing intuitively. AI sales signals help reps find the right person through Stakeholder Signals, the right timing through Operational and External Signals, and the right message through Intent Signals and GTM Context Graph synthesis. The taxonomy gives that intuition a repeatable structure.
Nowoslawski and Slocum say that adopting signal-based selling is not simply a new set of templates or workflows to follow. Instead, frontline teams should cultivate cultures of ongoing experimentation with the understanding that not every signal or strategy will be effective.
"You're always trying to reach out to the right person, with the right timing, with the right message, the three R's," Slocum says. "That trinity coming together gets you that meeting, and signals help you find that right person, that right timing, and that right messaging all in one."
Frequently asked questions
What are AI sales signals?
AI sales signals are data-driven indicators derived from CRM activity, intent data, job changes, funding events, and external news that AI systems detect and score to identify which prospects are most likely to buy, churn, or expand. They replace manual account monitoring with automated, real-time intelligence across four categories: Stakeholder, Operational, External, and Intent signals. Where buying signals capture a single dimension of buyer behavior, AI sales signals fuse multiple data streams into a ranked, actionable view of which accounts to prioritize right now.
How do AI sales agents use buying signals?
AI sales agents monitor accounts continuously for buying signals including job changes, funding rounds, tech-stack shifts, and competitor mentions, then synthesize that intelligence into personalized outreach drafted within minutes of signal detection. The key distinction is that true AI signal capability requires a full detection-to-synthesis-to-generation workflow, not just templated email automation. The GTM Context Graph is the reasoning layer that makes synthesis possible: it fuses signals with CRM history and conversation intelligence to surface why an account is worth reaching out to, not just that something changed. Tools like GTM Workspace execute this end-to-end.
What types of sales signals should AI monitor?
AI should monitor four signal categories: Stakeholder Signals (personnel changes, new decision-maker engagement), Operational Signals (budget approvals, tech-stack changes), External Signals (competitor launches, regulatory shifts, industry news), and Intent Signals (anonymous web behavior, content consumption). External and Operational signals are the most commonly missed by human reps because they exist in unstructured data sources that CRMs do not natively ingest. AI sales signals systems solve this by continuously scanning news feeds, job boards, and earnings transcripts across every account in a rep's territory simultaneously.
How do AI sales signals integrate with Salesforce and HubSpot?
AI sales signal platforms like GTM Workspace surface signals natively inside Salesforce and HubSpot so reps see Account-Fit Score updates, buying group alerts, and Earnings Scoops without leaving their CRM. Custom signal configuration lets teams define their own ICP-specific trigger events, including marketing-originated behavioral signals like web visits and content downloads. The key setup steps: map your ICP trigger events, configure signal rules in your CRM or signal platform, and set rep notification thresholds. Spekit qualified pipeline 58% faster after deploying signal-driven qualification workflows inside their CRM.
What is the difference between intent data and AI sales signals?
Intent data is one input into AI sales signals, specifically the Intent Signal category covering anonymous web behavior and content consumption patterns. AI sales signals are broader: they encompass Stakeholder, Operational, External, and Intent signals, fused and scored by AI to surface the accounts most likely to convert right now. Intent data tells you someone is researching. AI sales signals tell you why, who, and when to reach out. For a deeper look at basic intent data and how it fits into a broader signal strategy, the buying signals article covers the foundation.
Which buying signals should SDRs prioritize?
SDRs should prioritize signals with the highest urgency and ICP fit: funding rounds (indicates growth investment), hiring plans (reveals operational pain points), job changes in the buying committee (new decision-makers are more receptive to new vendors), and earnings call disclosures (surfaces stated priorities and pain points directly from leadership). GTM Workspace's Account-Fit Score automatically ranks these signals by relevance to your ICP so reps focus on the highest-probability accounts first. Thomson Reuters hit 115% quota attainment and saw a 40% increase in closed-won deals using this signal-prioritized approach.