Signals vs Intent Data

How can your sales, marketing, or RevOps team know who’s ready to buy before competitors do? The answer lies in harnessing the right data at the right time. In B2B go-to-market (GTM) strategy, two data types dominate the conversation: traditional intent data and real-time signals. Both offer insight into buyer interest, but they aren’t the same. In fact, a staggering 75% of B2B sales engagements in 2025 are forecasted to originate from signal-based triggers (e.g. leadership changes, funding rounds) – a fundamental shift in how teams target prospects. This post will unpack the differences between signals and intent data, illustrate use cases for each, and show how combining them can empower your GTM team to engage buyers at the perfect moment.

Why Signals Matter for Modern GTM Teams

Today’s B2B buyers are more elusive than ever. Studies show buyers conduct 80% of their interactions through digital channels and complete 60–90% of their decision-making process before contacting any vendor. This means the majority of the buyer’s journey happens “invisibly,” without your sales team’s knowledge. If you’re only relying on inbound inquiries or gut instinct, you’re missing huge chunks of this journey.

Intent data emerged to solve part of this problem by illuminating what target accounts are researching online. But intent signals alone aren’t enough. They primarily reflect content consumption habits – for example, an increase in reading whitepapers about cybersecurity might indicate a company’s interest in security solutions. Buying signals, on the other hand, are real-world events and organizational changes (like funding news or hiring sprees) that often create immediate needs. These signals can tip you off that an account is primed for engagement even before they start consuming content related to your product.

The competitive advantage is clear: companies that act on real-time signals consistently engage prospects earlier. Forward-thinking sales organizations using trigger events see conversion rates 4× higher than generic cold outreach. In other words, by the time a competitor waits to see “intent” surging for an account, a signal-driven team may have already started a conversation and framed the deal.

Understanding Intent Data (Traditional “Intent” Signals)

Intent data refers to behavioral clues that a prospect is actively interested in a topic or solution. Typically, this data comes from online content engagement such as:

• Web activity on third-party sites: e.g. reading comparison articles, visiting review platforms, downloading ebooks.
  
  
• First-party website behavior: visits to your pricing page, repeated site visits, webinar sign-ups.
  
  
• Content consumption patterns: attending relevant webinars, listening to podcasts, or searching certain keywords.

Why does intent data matter? Because it sheds light on that hidden buyer research phase. Teams using intent data report overwhelmingly positive results. 96% of B2B marketers say they have seen success in achieving their goals with intent data, and 98% consider intent data an essential component of demand generation. By monitoring what prospects are reading and researching, GTM teams can:

• Prioritize in-market accounts: Focus on companies showing interest in your solution area, rather than guessing or relying solely on demographics.
  
  
• Personalize outreach: Tailor marketing messages or sales pitches to the topics a prospect cares about (yielding much higher engagement – intent-driven ads see 220% higher click-through rates compared to generic ads).
  
  
• Align sales and marketing: Use data to agree on which leads are “warm.” In fact, 53% of B2B marketers use intent data specifically to improve sales-marketing alignment by defining objective triggers for outreach.

Imagine your marketing team sees that a target account has spiked in consuming content about CRM software integration. This third-party intent signal suggests they may be considering a new CRM or add-ons. Marketing can add them to a targeted campaign with content about your integration-friendly features, while sales might prioritize them for outreach. According to research, such intent-informed campaigns can yield dramatic results – companies have observed 93% higher conversion rates when leveraging intent data and significantly faster sales cycles as reps engage buyers who are already in research mode.

However, intent data is not without challenges. It often comes with noise – not every content view is a genuine purchase intent (someone could be casually browsing or an intern doing research). And while 99% of large enterprises use intent data in some way, only about 25% of all B2B businesses currently leverage these tools, largely because smaller companies struggle with perceived complexity or costs. The good news: most hurdles (data integration, interpretation) are surmountable – 92% of teams have successfully integrated intent data into their tech stack, and 61% see ROI from intent programs within 6 months once they get started.

What Are Real-Time Signals (Buying Signals)?

While intent data looks at interest, signals focus on readiness. Signals (often called trigger events or buying signals) are real-time indicators that a target account is undergoing a change that could drive a purchase. These typically include:

• Hiring Signals: e.g. rapid hiring growth, new executive appointments, or key leadership changes. (A new C-suite executive is 68% more likely to review existing vendors within 90 days, making it a prime opportunity to pitch a solution aligned with their new agenda.)
  
  
• Funding Signals: e.g. a company announcing a fresh funding round or increased revenue. (Companies with new funding spend 22% more on tools within 6 months ; moreover, 71% of funded companies finalize new vendor contracts within 90 days when approached early. Move fast – vendors who reach out to a newly funded company within 48 hours enjoy 4× higher conversion rates than those who delay.)
  
  
• Technographic Signals: e.g. adopting or replacing a technology in their stack. (If you see a target account just installed a complementary tool to yours, or their current solution is reaching end-of-life, they might need your product next.)
  
  
• Expansion Signals: e.g. opening a new office, entering a new market, or merging with another company. (These often create immediate needs – 58% of acquired companies replace major systems within 12 months post-merger, representing big openings for new vendors.)
  
  
• “Warming” Signals (Early Interest): subtle signs of early research or curiosity in your category that precede formal intent. For instance, increased engagement with your thought leadership content or social media could indicate an account is starting to explore solutions (even if third-party intent providers haven’t flagged them yet).

In short, signals are the contextual events that often spark buying initiatives. They answer questions like: Has this company hit a growth spurt (and thus needs new software)? Did they just hire a VP of Sales (who might consider new sales enablement tools)? Did they announce an expansion (indicating new infrastructure needs)? These real-world changes often create urgency that pure intent data might miss.

Consider a few concrete examples of signals in action:

• Leadership Change: A new CFO is hired at a mid-market tech company. This is a strong signal – new executives often reevaluate tech and vendor choices. Knowing this, a savvy sales rep reaches out within days, congratulating the CFO and highlighting how their solution can drive quick wins. That rep isn’t guessing; they’re timing outreach based on a data-backed trigger. (Outreach tied to leadership changes gets a 14% response rate versus just 1.2% from cold calls, because the message is timely and relevant.)
  
  
• Funding Event: A startup in your target list just raised a Series B round. With fresh capital, they’ll be investing in scaling – possibly including your product category. Marketing could fast-track this account for an ABM campaign, while your SDR emails them referencing their growth plans. Given that the majority of funded companies lock in new vendors within ~3 months, being first to engage is critical.
  
  
• Product Expansion: Your ICP (Ideal Customer Profile) includes retailers, and you see news that a regional retail chain is expanding to e-commerce nationwide. This expansion signal suggests they’ll need better e-commerce analytics and supply chain tools. If you offer one of those, this is your moment to reach out with a tailored message about handling growth – before they even start Googling solutions.

It’s no surprise that industry research predicts signal-driven prospecting will soon overtake traditional methods. Companies systematically tracking these signals are transforming their prospecting from a volume game into a precise, timing-driven strategy.

Using Signals vs. Intent Data in Practice (Use Cases)

Leading GTM teams don’t view signals and intent as abstract concepts — they build them into daily playbooks. Here’s how sales, marketing, and RevOps practitioners apply each:

Sales Prospecting with Signals: Sales development reps (SDRs) and account executives leverage real-time signals to prioritize outreach. For example, an SDR might start each morning by reviewing alerts for any target accounts with fresh signals: new funding, big hire, expansion news, etc. Those accounts get top priority for calls or personalized emails that day. The messaging directly references the trigger (“Congrats on the funding… many companies in growth mode use our solution to scale hiring – have you considered X?”). This approach transforms cold outreach into warm relevance. It’s proven to boost outcomes – **teams that monitor trigger signals achieve 400% higher conversion rates on average versus generic cold calling. Reps also use signals to time their follow-ups: if a deal went dark but then the prospect announces a major partnership (expansion signal), that’s a cue to re-engage with a new angle.

Marketing Campaigns with Intent Data: B2B marketers frequently use intent data to refine targeting and personalize content. One common use case is Account-Based Marketing: say you have a list of 100 target accounts, and intent data reveals 15 of them are “surging” on keywords related to your product. Marketing can focus ad budget on those 15, craft ad copy or emails that speak to the specific topics they’re researching, and even create content (whitepapers, case studies) that match those interests. The impact can be dramatic – ads aligned to intent signals see click-through rates more than double (2.2×) the industry average, because you’re speaking to an active need. Similarly, intent data helps prioritize which accounts get fast-tracked to sales; many companies set up alerts or lead-scoring rules so that if an account hits a high intent threshold (e.g. reading 10+ relevant articles in a week), sales is notified to reach out immediately.

Combining Both in Account Strategy: The most sophisticated GTM teams layer signals and intent together for an “all-angle” view. For instance, imagine your RevOps team uses a scoring model for accounts: they might assign points for fit (industry, firmographics), points for intent (content engagement level), and points for signals (recent trigger events). An account that just had a strong intent surge and a big buying signal (e.g. new CIO hired + researching “data integration”) would score off the charts – a must-contact-now account. On the flip side, an account with a buying signal but no detected intent might still be worth outreach (they may not have started public research yet, giving you a chance to shape their thinking early). RevOps also feeds both data types into routing and segmentation. It’s common to route high-intent leads straight to experienced reps or to create separate nurture tracks for “signal-only” leads vs “intent-active” leads, since their timelines might differ. Can you combine signals with intent data? Absolutely – and it often yields the best results.

Use Case – Trade Show Follow-Up: Here’s a tactical example integrating both: Suppose your company is attending a big industry trade show. Marketing captures first-party intent by noting which booth visitors showed interest (scanned badges, attended your session – that’s intent data showing they’re curious). Post-event, you enrich this with third-party intent (did those accounts then visit review sites or download related content?) to gauge continued interest. Meanwhile, you watch for signals like press releases from those accounts post-show (did they announce a new initiative in the space?). If, say, one of those prospects also just announced an expansion into a market that your product supports, sales should reach out referencing both the trade show conversation and that expansion signal. This multi-pronged insight paints a fuller picture and often impresses the prospect (“Wow, they really understand what’s happening with my business”).

Precision in Timing vs Personalization: In practice, signals often dictate when to reach out, while intent guides how to craft the message. A sales rep might decide to contact a prospect this week because of a signal (e.g. “I saw you were hiring 50 new engineers – usually that’s when companies look at scaling their DevOps tools, which we can help with”). In that outreach, the rep will also use any intent data available to personalize the pitch (“…and I noticed your team has been exploring Kubernetes optimization – here’s a case study on that.”). The combination makes the outreach both timely and relevant.

Pros and Cons Summary

To recap, here are the high-level pros and cons of signals vs. intent data for GTM teams:

Signals – Pros:

• Timely and actionable: They alert you to strike at the right moment (when a prospect’s situation is changing). This timing can dramatically improve response rates and conversion.
  
  
• High relevance: Each signal provides a natural conversation opener (you can immediately address the context: new role, new funding, etc.), which helps you cut through the noise with prospects.
  
  
• Strategic insight: Signals often reveal strategic shifts at a company (e.g. expansion, re-org). This helps you tailor not just your messaging but your overall account strategy (maybe focusing on certain product lines or proposing solutions fitting their growth mode).
  
  
• Less guesswork: A trigger event is a concrete reason to believe an account could need something. Reps gain confidence in their outreach prioritization, leading to better productivity.
  

Signals – Cons:

• Sporadic coverage: Not all accounts emit frequent signals. If you focus only on triggers, you might overlook accounts that are quietly researching solutions without any big public moves.
  
  
• Public visibility: Many signals (funding announcements, etc.) are public info – meaning your competitors see them too. Acting quickly is key, but there’s no exclusivity to knowing a company got funded.
  
  
• Context needed: A signal tells you something changed, but not necessarily what solution the prospect will choose. You still need to do discovery. For example, a new CTO hire is a buying signal, but you must investigate what that CTO’s priorities are (intent data or initial conversations can help there).
  

Intent Data – Pros:

• Broadly surfaces interest: It casts a wide net to catch any account showing buying research behavior, even without public events. Great for uncovering “hidden” prospects who might otherwise stay under radar.
  
  
• Topic specificity: Intent data often reveals what the prospect cares about. This is gold for crafting effective marketing content and sales pitches that resonate with their specific pain points.
  
  
• Proven impact on funnel: Using intent data has been linked to improved funnel metrics across the board. Companies see higher email engagement, 82% faster lead conversion on intent-qualified leads, and even higher win rates when sales and marketing align around intent signals.
  
  
• Scalability: Once integrated, intent data can be automated through your systems (e.g. auto-alerting reps or dynamically personalizing web content for visitors from an in-market account). It continuously feeds your GTM engine with insights without heavy manual effort.
  

Intent Data – Cons:

• Noise & interpretation: It requires careful tuning. Teams must figure out which intent signals truly indicate buyer readiness versus curiosity. This can mean trial and error with thresholds or buying from quality providers to reduce noise.
  
  
• Delayed or opaque data: Some third-party intent sources won’t tell you exactly who was interested (only that someone at Company X is reading about Y). And data might come on a lag (weekly reports of surges). This is improving with technology, but it’s not always “instant.”
  
  
• Integration & skills: Smaller companies may find the ecosystem confusing at first – there are dozens of providers and figuring out how to plug intent into your CRM/marketing automation takes planning. However, as noted earlier, concerns about complexity are often overstated – nearly 92% of teams succeed in integrating intent data, especially when using platforms or partners to help.
  
  
• Privacy changes: As mentioned, reliance on cookies and third-party tracking means the industry is adapting. Solutions like publisher cooperatives, IP matching, and contextual intent are emerging to keep intent data flowing in a privacy-compliant way.

The bottom line: Signals and intent data are complementary. Each mitigates the other’s weaknesses. Signals give you confident triggers to act on; intent data ensures you’re not missing the quieter indicators of interest and helps refine your approach.

Combining Signals with Intent for Maximum GTM Impact

Given their complementary nature, the best GTM teams use signals and intent data together to supercharge their pipeline. Here are some best practices for combining them:

• Layer intent on top of signals for prioritization: Suppose you have a batch of accounts showing recent signals (maybe 50 accounts that got funded this month). If any of those also show a surge in intent on your solution area – those are your hottest opportunities. Focus sales efforts there first. The signal indicates timing, and the intent indicates interest, together signaling a high likelihood of a deal if you engage effectively.
  
  
• Use signals to validate and filter intent leads: Not every intent spike is worth sales time. But if an account surging on intent also has a known pain point or trigger event, it’s more likely to convert. For example, two companies both show intent for “ERP software”; one of them just announced an acquisition (signal), the other hasn’t. The one with the M&A signal likely has an urgent integration need – a stronger bet for your sales outreach.
  
  
• Craft multi-touch campaigns mixing both angles: Marketing can run integrated plays such as an email sequence that starts by referencing a company’s specific signal (e.g. “We saw you’re expanding to APAC – congrats! Here are resources on scaling globally”) and then follows up with content aligning to their intent topics (e.g. “Since you’re researching cloud infrastructure, here’s a guide on optimizing cloud costs for new regions”). This one-two punch shows the prospect you understand both their situation and their interests.
  
  
• Leverage technology to unify insights: Modern platforms (like Landbase’s own GTM intelligence platform) increasingly bring together thousands of signal data points with intent data in one view. For instance, Landbase monitors 10+ million real-time signals across web, email, and other channels to identify when prospects are “in-market” or experiencing a change. AI can then analyze these combined signals to score and recommend next actions. By using such tools, GTM teams can ensure no important signal or surge is missed and that all data is feeding a cohesive strategy.
  
  
• Align team roles around data: Often marketing may “own” third-party intent data (for top-of-funnel targeting), while sales teams leverage more of the trigger events intel. To avoid silos, have regular meetings or shared dashboards that show both types of insights for target accounts. Some organizations form a “Revenue Operations” function that centralizes these data feeds and disseminates a unified view to sales & marketing, ensuring everyone is on the same page regarding who to go after and why.

Remember that speed is crucial, especially with signals. If you get an alert that a target account had a major trigger (say, big funding), have a process so the relevant sales rep is on it within 24–48 hours. Intent data might tell you an account is warm for a few weeks, but a buying signal’s value decays fast – being the first vendor to reach out with a tailored message can be the difference between winning the deal or never getting a response.

Turn Signals into Your GTM Advantage

In an era where buyers have more control over the journey, staying proactive is everything. Traditional intent data gives you a window into what prospects care about, and it’s become an indispensable tool – nearly 98% of marketers say intent data is fundamental for their demand gen efforts, and using it has been linked to 99% of businesses seeing increased sales/ROI post-implementation. Real-time signals, meanwhile, are the emerging secret weapon that let you engage at the right moment; they focus your efforts where there’s real buying energy (think of them as early warning alarms for deal opportunities). The companies that master both are essentially illuminating the buyer’s path from two sides – understanding who is interested and when/why they’re ready to buy.

Your GTM team can start small: perhaps begin tracking a few high-impact signals (like funding announcements in your target industry) while also tapping an intent data source for your top accounts. Experiment with tailored outreach using these insights, and measure the lift in engagement versus your usual efforts. The data strongly suggests you’ll see faster conversions and fuller pipelines. As one study succinctly put it: early adopters gain a compound advantage by engaging prospects when competitors remain in the dark. In practical terms, that means more wins, bigger wins, and less time lost on prospects that aren’t ready.