What Is B2B Intent Data and Why Does It Change Everything About Outbound

I see this every week - outbound teams reaching the right people at the wrong time.

You have a solid ICP. Your list is clean. Your emails are well-written. And still, you get a 1-2% reply rate because 98% of the people you contacted were not thinking about your solution when your email landed.

Intent data solves this problem.

B2B intent data is behavioral information that tells you which companies and buyers are actively researching a problem you solve - right now, not six months from now. Calling someone who just Googled "best CRM for SaaS" is a different conversation than cold-calling every SaaS company on a list and hoping one of them is in-market.

The results when teams get this right are not marginal improvements. Practitioners report reply rates jumping from the standard 1-2% range into the 6-25% range when outreach is triggered by strong intent signals. That's a 5-7x lift from one change in how you build your target list.

This guide covers what intent data is, where it comes from, which signals are producing results for outbound teams right now, and the honest limitations practitioners are running into.

The Core Definition I See Misrepresented Constantly

B2B intent data is a category of data.

It refers to any signal that suggests a business is actively in a buying journey for a product or service like yours. The signal can be behavioral, transactional, or situational. What matters is that something has changed at that company - a change that indicates they have a problem to solve or a decision to make.

Every company that could buy from you fits into one of three buckets.

• Not thinking about it. They don't have the problem, or they don't know they do.
• Aware but not moving. They know the problem exists but haven't started evaluating solutions.
• Actively looking. They're researching vendors, comparing features, and preparing to make a decision.

Only 15% of companies are in-market for any specific product at any given time. Intent data is how you find those 15% before your competitors do.

I see this every week - teams treating their entire addressable market as if everyone is equally likely to buy. They blast the full list. They burn contacts. And they wonder why their reply rates are dropping.

Intent data narrows your focus to the accounts where the timing is right. And timing, as it turns out, is most of the battle.

Why Timing Is the Entire Game

Gartner research shows that B2B buyers spend only 17% of their total buying time talking to suppliers. With an average of 8-12 people in a buying committee, any single vendor gets roughly 5-6% of the entire decision-making process. The other 94% happens invisibly - in Slack groups, on review sites, via AI search tools, and in conversations your sales team never sees.

By the time a buyer contacts a vendor, they've typically already shortlisted 2-3 options. If you're not on that list, you're not in the deal.

Intent data changes that equation. Instead of waiting for buyers to raise their hand, it reveals who's actively researching solutions in your category while they're still in the evaluation phase. That's the window where outreach converts.

One practitioner described it this way in a widely-shared post: a company consuming 15 articles about "sales intelligence" in a single week has clearly changed internally. Maybe they hired a new CRO. Maybe a contract is coming up for renewal. Maybe the board pushed for change after a bad quarter. You don't always know why. But you know now is the time to reach out.

Acting on a signal within 24 hours produces roughly 3x better results than acting within a week. The first vendor to reach out after a trigger event consistently wins the conversation.

The Three Types of B2B Intent Data

Intent data comes from three distinct sources, and understanding the difference matters because each one has different use cases, different costs, and different accuracy levels.

First-Party Intent Data

This is behavioral data collected from your own digital properties - website visits, content downloads, email link clicks, pricing page visits, demo requests, and time-on-page metrics.

First-party data is the highest quality signal you can get. A company visiting your pricing page twice in one week is almost certainly evaluating you. A prospect who read three case studies in your industry has already done significant research.

The limitation is coverage. Your website only captures people who already know you exist. It misses the 94% of the buying journey happening elsewhere.

If you haven't set up website visitor identification yet, that's the right starting point. One practitioner put it bluntly: buying a third-party intent platform before you can identify who's visiting your own website is like buying a telescope before you've opened your eyes.

Second-Party Intent Data

This is data shared directly from a partner platform where your prospects are already spending time. The most valuable example for B2B is review site data.

When a company is reading reviews of your competitor on G2, that's a strong signal they're in-market and actively comparing options. That's second-party data. The review platform owns it, and they share it with vendors whose categories are being researched.

Second-party data is particularly valuable for catching buyers during the vendor evaluation phase - when they're actively comparing solutions and are most likely to respond to outreach. Review site activity is a late-stage signal. These buyers are not just problem-aware. They're solution-shopping.

Third-Party Intent Data

This is behavioral data aggregated from networks of external publishers, content platforms, and B2B media properties. Bombora is the most well-known provider in this category.

Bombora draws its data from a publishing cooperative of more than 5,000 websites. For every company in their system, they establish a baseline of normal research activity on each topic. When a company's recent research spikes significantly above that baseline, it generates a Company Surge score. A score of 70 or higher is flagged as an active buying signal.

For example: a company that normally reads zero articles about "email deliverability" suddenly consuming content on that topic across dozens of B2B sites in a single week is showing intent. Something changed internally. The Surge score captures that change.

The limitation of third-party data is that it operates at the account level. You'll see that Acme Inc. is researching a relevant topic - but you won't know which specific person inside that company is doing the research or whether they're part of the buying group. You still need to find the right contacts yourself.

I see this across intent programs that have been running for a while - they end up combining all three. First-party data tells you who already knows you. Who's comparing options shows up in second-party. Third-party expands your coverage to in-market accounts you'd never find otherwise. Roughly 55% of companies using intent data combine first-party and third-party signals for this reason.

The Intent Signal Hierarchy - What Practitioners Are Using

Not all intent signals are equal. Based on what's resonating with outbound practitioners right now, signals can be organized into three tiers based on strength and reliability.

Tier 1 - Strongest Signals

These signals indicate a company is almost certainly evaluating a solution in your category. Act on these first.

• Job postings for roles you sell to. A company posting for a Head of Revenue Operations doesn't need that person to start yet - they have the problem right now. One practitioner with 60,000 followers built a whole outbound system around this insight: if a company is hiring for a specific role, they have the problem that role is meant to solve before that person even starts. The angle that works: "Saw you're hiring a [role]. Usually means the team needs [solution]."
• New leadership / role changes. Someone who just started a new job evaluates every tool in their stack in their first 90 days. That creates a buying window that closes fast. The angle: lead with context about their new role, not a pitch.
• Competitor engagement monitoring. One of the highest-performing intent signals among practitioners is tracking when ICP-fit prospects engage with competitor content on LinkedIn. Liking, commenting on, or sharing content from a rival tool is a clear buying signal. This tactic consistently generates the most engagement when practitioners discuss intent signals - and tracking competitor engagement on LinkedIn is not covered in mainstream intent data guides.
• Funding announcements and RFP publications. Fresh capital creates new budget. RFPs signal active vendor evaluation. Both indicate a company is in motion.
• Review site activity. A prospect reading your competitor's G2 reviews is comparison shopping. That's one of the clearest late-stage buying signals available.

Tier 2 - Strong Signals

These signals are worth acting on, especially when combined with Tier 1 signals.

• Tech stack changes (installing or removing tools you compete with or complement)
• Company growth indicators (headcount expansion, new office openings)
• Industry event attendance and conference registrations
• Bombora Company Surge scores above 70 for your core topics

Tier 3 - Moderate Signals

These signals alone are weak. Use them to support prioritization, not to trigger outreach on their own.

• General content consumption on your blog or industry publications
• Website visits without high-intent page visits (pricing, demo, comparison pages)
• Webinar registrations
• Social engagement with broad industry topics

A practitioner community consensus on this: a single signal is a hypothesis. Three signals from the same company is conviction. The strongest outbound plays stack multiple signals before pulling the trigger - especially when resources are limited.

The Number That Explains Why This Matters More Every Year

Cold email is getting harder at a measurable rate. The number of cold emails needed to generate a single positive reply has been rising steadily: in one widely-circulated analysis from an operator with 32,000 followers, the figure went from 120 emails per reply to 200 the following year, and then to 430.

When it takes 430 cold emails to get one reply from an undifferentiated list, intent data stops being a nice feature and becomes the primary efficiency lever.

The math is simple. If your reply rate is 0.2% on a cold list and 6% on an intent-triggered list, you need 30x fewer contacts to get the same number of conversations. That means lower send volume, better deliverability, less list cost, and more focused messaging. Every advantage compounds.

Only 25% of B2B businesses currently use intent data. But 99% of large enterprises use it in some form. Teams that build intent-driven outbound systems now will have significant advantages over those who don't - because the competition for in-market buyers will only get more intense.

How the Tech Stack Works in Practice

Practitioners are building signal-based outbound systems right now in the tools they're actively using.

Signal Detection Layer

This is where you identify that something has changed at a target account.

• Job change and hiring signals: LinkedIn Sales Navigator, Coresignal, Apollo
• Third-party behavioral intent: Bombora, 6sense, ZoomInfo Intent
• Review site signals: G2 Buyer Intent
• Website visitor identification: RB2B (for US-based visitors), Leadfeeder
• Competitor social engagement: Manual LinkedIn monitoring or tools like Trigify

Enrichment and Prioritization Layer

Once a signal fires, you need to find the right contact at that company and score the opportunity.

• Clay is the most commonly cited tool for this. It pulls from multiple data sources simultaneously, enriches the account with firmographic data, and scores leads based on rules you define.
• The output is a prioritized list of accounts with the right contacts already attached.

To find the right contacts at those companies at scale, Try ScraperCity free - you can search millions of verified B2B contacts by title, industry, location, and company size to match the right person at each signal-triggered account.

Verification Layer

Before any email goes out, contacts get verified. Bad data kills deliverability fast. Tools like MillionVerifier and BounceBan are what practitioners use before launching sequences.

Outreach Layer

Signal-triggered sequences go out through tools like Instantly, Smartlead (for email), and HeyReach (for LinkedIn outreach). The key difference from standard cold outreach: the message references the specific signal.

"Saw you're hiring a VP of RevOps - that usually means the team is building out the reporting infrastructure before that person starts. We help with that."

Signal detection. Enrichment. Verification. Then a message that proves you did your homework.

What the Reply Rate Data Shows

Let's be specific about the numbers practitioners are reporting, because there's a wide range and context matters.

Standard cold email to a static list: 1-2% reply rate. This is the floor. Multiple independent practitioner accounts confirm this as the baseline when there's no signal layer.

Signal-based outbound, general: 6-10% reply rates. This is the most common range cited by practitioners running intent-triggered sequences. It represents a 4-6x lift from baseline.

Specific signal types with documented outcomes:

• Hiring-signal triggered LinkedIn outreach: 13.8% reply rate (documented in a live case study from a practitioner with 125 likes on the post)
• Intent signal specialists (multiple signals stacked): 15-25% reply rate range

Industry benchmarks for signal-to-meeting conversion: 5-15% for topic-level intent, 15-30% for page-level intent (such as a prospect visiting your pricing page).

The important caveat: reply rate is not the only metric that changes. Sales cycle length shrinks because you're reaching buyers who are already in motion. Teams using intent data consistently report 30-40% shorter sales cycles. Conversion rates improve because you're having conversations with accounts that already have an active problem. Customer acquisition costs drop because you're not wasting outreach budget on 75% of the list that isn't in-market.

Honest Limitations

About 24% of practitioner-level conversations about intent signals include skepticism or caveats. That's a meaningful minority, and they raise legitimate points worth including here.

The most direct summary: "Intent data alone? Useless. But arming sales with why a prospect needs you right now? Real conversations start there."

Skeptics raise legitimate points.

Third-Party Intent Signals Are Often Late or Vague

By the time a Bombora Surge score fires, the company may have already made a decision. Buying cycles for mid-market deals can compress to 2-4 weeks from "actively researching" to "selected a vendor." A Bombora signal that's three weeks old might already be noise.

This is why practitioners increasingly favor event-based signals - job changes, funding rounds, tech stack changes - over content consumption signals. Event-based signals are precise in time. Someone accepted a new role on a specific date. That date is when the buying window opens, and you can act accordingly.

Account-Level Data Doesn't Tell You Who to Call

Both Bombora and 6sense show you that Acme Inc. is researching your topic. They don't tell you which person inside that company is driving the evaluation. Your outreach still needs to go to the right contact, which means you need a separate layer for contact-level data after the signal fires.

This is where teams that skip the enrichment step lose the benefit. Signal without the right contact is a phone number without an area code.

Signal Quality Degrades Without Clean Contact Data

One practitioner summarized it accurately: clean contact data matters. Hit them the same day the signal fires. The message has to match the trigger. Remove any one of those three and the results drop significantly. Intent data improves a functioning outbound operation. It doesn't substitute for one.

I see this constantly - ICP-fit accounts that still aren't in a buying window

Even with good intent data, AI lead scoring and signal filtering typically eliminate 60-70% of the accounts that look like good fits on paper. Filtering confirms that most of your addressable market isn't ready to buy right now, and stops you from wasting budget trying to reach them anyway.

Competitor Engagement Is a Buying Signal You Can Track for Free

Something that consistently generates strong practitioner engagement but gets zero coverage in mainstream intent data guides.

Monitoring LinkedIn engagement on competitor content is one of the most direct buying signals available - and it requires no enterprise software.

The workflow: identify your top 3-5 competitors. Follow their company pages and track which posts are getting significant engagement. When someone who fits your ICP likes, comments on, or shares competitor content, they have just revealed active interest in a solution category.

One operator described this directly: "Whenever someone who fits my ICP likes, comments on, or interacts with [competitor] content, it's a strong buying signal. I capture those profiles in real time."

This is third-party intent data you can collect yourself, for free, on a category your competitors are already educating for you. The prospect is raising their hand in public. All you have to do is see it.

The outreach angle that works: don't mention that you saw them engage with a competitor. Instead, lead with the topic they were engaging with. "Saw some conversation in the space about [topic]. We've been getting a lot of questions about [specific angle]. Here's how we approach it differently..."

You're reaching them at the moment of highest interest. That's what intent data is supposed to do - this tactic just does it without a $50,000 platform contract.

The Tool Installation Signal - A Practitioner Workflow

One of the most underutilized intent signals is tech stack data. Specifically: identifying companies that have just installed a tool that indicates they're in-market for what you sell.

The workflow works like this. Map your buyers to the tools they install when they're actively building the kind of operation that needs your product.

• eCommerce brands building out customer support infrastructure install Gorgias.
• Podcast-based content brands use Podchaser.
• Course creators on specific platforms install Teachable.
• HelpCrunch gets deployed when the support load gets serious.

Each of these tool installations is a behavioral signal. A company that just added Gorgias is scaling their support operation. If you sell to eCommerce brands, that company just became a high-intent target - not because of anything they searched, but because of a tool they installed.

PublicWWW searches the raw source code of websites, which means it can surface thousands of domains using a specific tool that wouldn't show up anywhere else. Search a tool name on PublicWWW, export the domain list, then enrich for contacts. The entire workflow takes under an hour and costs close to nothing.

You're finding companies that have already done something that proves they have the problem you solve.

How to Start Without a Big Platform Contract

The entry point for intent-based outbound doesn't require a six-figure tech stack. Here's a practical starting sequence for teams that are new to this.

Step 1 - Set Up First-Party Visitor Identification

Before anything else, know who is visiting your website. Tools like RB2B (US-focused), Leadfeeder, and Clearbit Reveal will identify the companies behind anonymous website sessions. A prospect visiting your pricing page three times is a hotter lead than any Bombora Surge score.

Step 2 - Pick Two Event-Based Signals to Activate

Don't try to monitor everything at once. Pick two high-quality event signals that match your ICP.

In B2B SaaS, the starting pair I come back to is:

1. Job postings for roles that indicate your problem (hiring signals)
2. Job changes (new leaders evaluating their inherited stack)

Both are free to monitor via LinkedIn. Both are time-specific. Both give you a reason to reach out that you can reference in your message.

Step 3 - Build the Message Around the Signal

Your message should prove you know why you're reaching out. The template pattern that works:

• Acknowledge the specific signal without being creepy about it. "Saw [company] is hiring a [role]" is specific. "I noticed some changes at your company" is vague and suspicious.
• Connect the signal to a problem you solve. "Usually means the team needs [outcome] before that person even starts."
• Keep the ask simple. Not a 30-minute call. A single question they can answer in one sentence.

Step 4 - Add Verification Before Sending

Signal-based lists tend to be smaller and more targeted than cold lists. That makes verification even more important because your reply rates will be higher and deliverability matters more. Verify every address before it goes into a sequence.

Step 5 - Measure Signal-to-Meeting Rate

Track what percentage of intent-triggered outreach results in a booked meeting within 14 days. That's your north star metric. If that number is below 5% for strong Tier 1 signals, your message isn't matching the trigger. If it's above 15%, you've found a signal-message combination worth scaling.

Intent Data and ABM - How the Two Connect

Intent data and ABM work together as strategy and input.

ABM is a strategy: focus your marketing and sales resources on a specific set of high-value accounts. Intent data is the input that tells you which accounts to focus on and when to activate.

Without intent data, ABM programs often run on static account lists built from firmographic criteria. You pick 200 companies that look like good fits and spend a year marketing to all of them at the same intensity. The result is wasted spend on the 85% of those accounts that aren't in-market at any given moment.

With intent data layered in, ABM becomes dynamic. The same 200 target accounts get different treatment based on their current buying stage. An account surging on your core topics gets immediate sales outreach and targeted ads. An account with no signals stays in a low-touch nurture until something changes.

Organizations with strong intent-ABM alignment report 36% higher customer retention and 38% higher sales win rates compared to teams without that alignment. The conversion rate improvement when sales and marketing teams have shared visibility into intent signals averages 48% compared to siloed approaches.

The Speed Problem - Why Your Signal Ages Fast

Intent data has a shelf life. A buying signal from three weeks ago is often noise by the time you act on it.

Mid-market B2B buying cycles can compress to 2-4 weeks from active research to vendor selection. That means a Bombora Surge score that's three weeks old may represent a decision that's already been made.

This is why teams that act on signals within 24 hours report roughly 3x better results than teams acting within a week. The first vendor to reach out after a trigger event consistently wins the initial conversation - and initial conversations are where pipeline is built.

The practical fix: set up automated alerts or daily signal reports rather than weekly reviews. For event-based signals like job changes and funding rounds, the trigger date is when your outreach should fire - not three days later when the sales rep happens to check the dashboard.

Real Case Examples - What the Numbers Look Like in Practice

Snowflake implemented an intent-driven ABM program and reported a 215% increase in qualified opportunities alongside a 67% reduction in sales cycles. Reach the right accounts at the moment they're in motion.

ServiceNow used 6sense intent data with a combined first-party and third-party approach and achieved an 89% engagement rate with targeted accounts while reducing content production costs by 45%.

At the practitioner level, one operator documented pulling 2,000 targeted leads in a single session and booking 4 meetings that week - not from volume, but from targeting companies showing the right signals and verifying the data before sending.

The pattern across every example is the same. Intent data produces better conversations because you're reaching people who have an active problem. The message still needs to be good. The follow-up still needs to happen. The signal just makes sure you're putting that effort where it can convert.

Intent Data vs. Predictive Analytics - The Difference

These two terms get used interchangeably but they describe different things.

Intent data tells you what's happening right now - a company is researching your category today. It's behavioral.

Predictive analytics uses past data to forecast which accounts are most likely to buy. It tells you what's likely to happen based on historical patterns.

Both are useful. The most effective programs use both together. Intent data surfaces the accounts that are actively in-market. When you have those accounts, predictive scoring helps you decide which ones to contact first based on fit and historical conversion patterns.

6sense, for example, combines third-party intent data from its B2B publisher network with first-party engagement data and historical deal data to place accounts in predicted buying stages. That's intent data plus predictive analytics working together.

When I work with teams starting out, intent data is the more immediately actionable layer. You don't need a year of historical data to start using it. A job posting or a funding announcement is a usable signal today.

Privacy and Compliance - What You Need to Know

One of the most common questions about third-party intent data is whether it's legal. The short answer: it depends on how it's collected.

Reputable providers focus on account-level tracking using company IP addresses rather than personal information. When personal data is involved, it is either anonymized and aggregated or collected only after explicit consent.

GDPR compliance is a meaningful concern for teams targeting European accounts. Intent data collected through B2B publisher networks where users have consented to data sharing is generally considered compliant. Intent data collected through bidstream advertising data - a less transparent method - carries more compliance risk.

The practical rule: press your intent data vendor on exactly how they source data and how they handle GDPR and CCPA compliance. Transparent providers explain their methodology without hesitation. If the answer is vague, that's a signal.

For first-party data, you're on solid ground as long as your cookie consent and privacy policy are in order. For second-party data from review sites, the platforms handle compliance on their end. Third-party data requires the most diligence.

What to Look for in an Intent Data Provider

If you're evaluating a paid intent data platform, here are the questions that matter.

• What is the data source? Content consumption from a publisher cooperative (Bombora's model) is a stronger signal than bidstream data. Ask specifically.
• Is it account-level or contact-level? Account-level is what most platforms deliver. You'll know the company is researching, but you'll still need to find the right person.
• How is the baseline calculated? Bombora, for example, compares recent activity to a 12-week baseline. A spike relative to that company's own normal behavior is more meaningful than a raw content consumption count.
• How fresh is the data? Bombora delivers weekly surge data. For time-sensitive signals, that weekly lag may be acceptable for topic-level intent but not for event-based triggers like job changes, which need to be real-time.
• What are the CRM integrations? Intent data that doesn't flow automatically into your sales team's workflow is intent data that won't get used. Native integrations with Salesforce, HubSpot, and your sequencing tool are non-negotiable.
• Can you pilot it? ROI typically starts showing up within 60-90 days for first-party signals and 90-180 days for full multi-source implementations. Any reputable provider should be willing to support a pilot before a full commitment.

On pricing: enterprise intent platforms can run from a few hundred dollars per month to tens of thousands annually. One practitioner who evaluated a well-known provider described being pressured into a $15,000 annual contract on a demo call with pricing framed as disappearing if they didn't commit immediately. That's a red flag regardless of data quality. Pilots, transparent pricing, and monthly options exist in the market.

Building a Signal-Based System That Scales

The teams getting the best results from intent data are not using it as a one-off tactic. They've built it into their operational rhythm.

Every Monday, their team pulls a list of accounts that surged on core topics in the past week. They cross-reference against ICP criteria. Only the accounts matching both filters go to the top of the sequence queue - the overlap of signal and fit, nothing else.

New job change signals fire automatically through their enrichment layer. The relevant contact at that company gets a signal-specific email sequence within 24 hours of the trigger date. The message references the specific change.

Hiring signals get checked every 48 hours. When a target account posts a role that indicates their problem, the rep gets an alert and a pre-built email template that references the specific job title and connects it to the problem they solve.

Over time, the team tracks which signal types convert to meetings at the highest rate and doubles down on those. Which signals generate reply rates above 10%? Which generate below 3%? The feedback loop improves the system continuously.

That's intent data done right. A systematic approach to finding the right people at the right moment and having a message ready when that moment arrives.

The One-Sentence Version

B2B intent data tells you which companies are actively looking to buy something you sell - so you can reach them before they've already chosen someone else.

Frequently Asked Questions

What is B2B intent data in simple terms?

B2B intent data is behavioral information showing that a company is actively researching a problem you solve. It could be content they're reading, tools they're installing, roles they're hiring for, or changes happening inside the company. It tells you who is in a buying window right now - not who fits your ICP on paper.

What's the difference between first-party and third-party intent data?

First-party intent data comes from your own website and marketing assets - visitors to your pricing page, email link clicks, demo requests. Third-party intent data is aggregated from external publisher networks and tells you which companies are researching relevant topics across the broader internet, even before they've ever visited your website. First-party data is higher quality but has limited coverage. Third-party data has broader coverage but requires more filtering to be useful.

How much does B2B intent data cost?

Costs vary widely. Enterprise platforms like 6sense and Demandbase start at several thousand dollars per month and scale up significantly. Bombora can be purchased as a standalone data feed. Review site intent (G2 Buyer Intent) is sold separately. Many event-based signals - job postings, funding announcements, competitor social engagement - can be monitored for free with manual workflows. For most teams, the right starting point is free event-based signals plus a contact enrichment tool before committing to a full intent platform.

Does intent data improve reply rates?

Practitioners consistently report reply rates of 6-25% from intent-triggered outreach versus 1-2% from cold lists with no signal layer. It depends on three things: the quality of the signal, the speed of outreach after the signal fires, and a message that directly references the trigger. Intent data without any of those three elements produces marginal improvement. Without all three, you're leaving most of the gain on the table.

What are the most reliable intent signals for cold email?

Based on practitioner results, the two strongest signals for cold outbound are hiring signals (companies posting for roles that indicate their problem) and job changes (new leaders evaluating their inherited tech stack). Both are time-specific, free to monitor, and give you a natural reason to reach out that you can reference directly in your message.

Is B2B intent data GDPR compliant?

It depends on how the data is collected. Account-level intent data based on company IP addresses and aggregate content consumption is generally considered GDPR compliant, especially when collected through publisher cooperatives where users have consented. Contact-level data and bidstream-based intent data carry more compliance risk for European audiences. Always verify with your specific provider how they handle GDPR and CCPA compliance before activating for EU accounts.

Can small teams use intent data without enterprise tools?

Yes. The most effective starting point for small teams is two free signals: job postings (hiring signals) and new role announcements (job change signals). Monitor these manually through LinkedIn or set up alerts through free tools. When a target account posts the right role or a new exec joins, send a signal-specific message within 24 hours. Add website visitor identification via a freemium tool to capture first-party intent from your own site. That combination costs close to nothing and produces meaningful reply rate improvements before you need to invest in a full intent platform.