Intent signals are the difference between guessing and knowing who's ready to buy
Most outbound teams are spray-and-pray. They pull a list from Apollo, add titles, and hit send. Then they wonder why reply rates hover at 4–6%.
Account-Based Marketing changes that math — but only when your list is built on real buying intent. If you're targeting accounts because they match a firmographic profile, you're guessing. If you're targeting them because they're actively researching your category on G2, engaging with competitor content on LinkedIn, and just raised a Series B, you're operating on signal.
This guide shows you exactly how to build an ABM list using intent signals from G2, LinkedIn, and funding data — the same framework B2B Leads uses to generate 15–24% outbound reply rates for SaaS companies.
The problem isn't ABM as a strategy. The problem is that most teams build ABM lists the wrong way.
They start with ICP firmographics — company size, industry, revenue range. That's necessary. But it's not sufficient.
Firmographics tell you who could buy.
Intent signals tell you who's ready to buy.
The gap between those two groups is where pipeline gets wasted.
Stat: A 2024 Demand Gen Report found that 68% of B2B buyers complete more than half their research before talking to a vendor. By the time they fill out a form, they've already shortlisted 2–3 options.
Intent-based ABM lets you intercept accounts before that shortlist closes.
Not all intent data is equal. The most effective ABM programs layer three types of signals:
Accounts actively viewing competitor profiles, reading reviews in your category, or comparing solutions on G2.
Decision-makers engaging with your content, following your competitors, or posting about pain points your product solves.
Companies that just raised capital — especially Series A/B/C rounds — are in buying mode. New budgets, new initiatives, aggressive hiring.
Each layer adds precision. Together, they create a list of accounts that are firmographically qualified AND behaviorally active.
G2 Buyer Intent is one of the most underused signals in B2B SaaS. It tracks which companies are visiting your G2 profile, your competitors' profiles, and category pages.
If you're on G2's paid tiers (Essentials or above), you get access to Buyer Intent data in your G2 dashboard. You'll see:
The highest-priority segment: Accounts viewing 2+ competitors in your category within a 30-day window. That's active evaluation behavior.
Raw G2 data gives you company names and domains. You still need to:
Tools like Clay, Apollo, or Clearbit work well for enrichment. Export from G2, push to Clay, enrich with LinkedIn profile data and email, then route to your outbound sequence.
Stat: G2 reports that accounts with active buyer intent signals convert at 2–5x the rate of cold accounts with no intent layer.
LinkedIn intent is less structured than G2, but often more contextual. You're identifying behavioral patterns — not just company-level traffic.
Anyone who liked, commented, or shared your LinkedIn posts in the last 30–60 days is warm. Export this from LinkedIn analytics or use tools like Shield or Taplio.
Use Sales Navigator to find people who follow your direct competitors. This is a strong signal — they're already invested in the category.
A company posting for a "Demand Gen Manager" or "RevOps Lead" is building out a function — and likely buying tools to support it. LinkedIn's job search API or tools like Theirstack surface this.
Decision-makers posting about challenges your product solves (e.g., "our outbound is broken, open to suggestions") are practically raising their hand.
Use Sales Navigator's Account and Lead filters together:
Account filters:
Industry, headcount, revenue, technology used
Lead filters:
Title (CMO, VP Sales, Head of Demand Gen), seniority (Director+), posted on LinkedIn in last 30 days
Pro tip: Save these as alerts. Sales Navigator will notify you when new accounts match — meaning your list stays fresh without manual refreshes.
Funding events are one of the cleanest buying signals in B2B. A company that just raised $15M Series B has budget to deploy, a board expecting growth, and a team under pressure to execute.
| Source | Data Available | Cost |
|---|---|---|
| Crunchbase | Funding rounds, investors, founding date | Paid ($49–$299/mo) |
| PitchBook | Deep funding + investor data | Enterprise |
| Dealroom | EU-focused, good for EMEA lists | Paid |
| Company updates (funding announcements) | Free / Sales Nav | |
| Tracxn | Global, strong in APAC | Paid |
For most SaaS teams: Crunchbase + LinkedIn covers 80% of use cases.
Not all funded companies are relevant. Apply these filters:
Round type:
Prioritize Series A, B, C (enough budget, not too early-stage)
Raised in last 90 days:
Urgency matters — budgets get allocated fast
Headcount:
Match to your ICP (e.g., 50–500 employees)
Category:
Filter by industry vertical and tech category
Example: A $10M Series B SaaS company in the martech space that just hired a VP of Marketing is a near-perfect ABM target for a demand gen agency.
| Dimension | Old ABM Approach | Intent-Driven ABM |
|---|---|---|
| List Source | Firmographic filters only | Firmographics + G2 + LinkedIn + Funding |
| Account Prioritization | Random or by revenue | By active buying behavior |
| Personalization | Industry-level | Signal-specific (e.g., "saw you on G2...") |
| Refresh Cycle | Quarterly | Weekly or real-time |
| Avg. Reply Rate | 4–6% | 15–24% (B2B Leads benchmark) |
| Time to First Meeting | 60–90 days | 2–4 weeks |
The difference isn't just efficiency. It's the quality of conversations. When you reach out because you know a prospect is actively evaluating your category, you're not a cold email — you're a timely intervention.
Building the list is step one. Prioritization is where revenue happens.
Use a simple scoring model with weighted signals:
Scoring threshold: Scores above 70 go to Tier 1. Scores 40–70 go to Tier 2. Everything else gets a nurture sequence.
A great list with generic outreach is still a bad campaign. Personalization has to match the signal.
Segment by signal type
G2 accounts get different messaging than funding-triggered accounts
Write signal-specific openers
"Noticed you've been comparing [competitor] on G2..." is 3x more likely to get a reply than a generic hook
Sequence structure
Day 1 (email) → Day 3 (LinkedIn connect) → Day 6 (email follow-up) → Day 10 (LinkedIn message) → Day 14 (breakup email)
Match CTA to buying stage
Tier 1 accounts get "15-min call this week." Tier 3 gets a content asset.
Track signal decay
If a Tier 1 account doesn't respond in 21 days, reassess their intent score and adjust cadence
One rule: Never send the same sequence to Tier 1 and Tier 3. Wasting a hot signal on a generic email is the most expensive mistake in outbound.
Building an ABM list using intent signals isn't a new concept — it's just not done well by most teams. They either skip the signals entirely or use a single data source and call it "intent-based."
The teams consistently generating 15–24% reply rates (vs. the 4–6% industry average) are layering G2 buyer behavior, LinkedIn activity, and funding triggers into a scored, prioritized list — and then activating it with signal-specific messaging.
If you want to run this playbook for your pipeline — without spending months figuring it out yourself — B2B Leads builds and activates intent-driven ABM programs for B2B SaaS companies.
We've helped 25+ SaaS clients book 60+ qualified meetings in 90 days and reduce CAC by an average of 38% — using exactly the framework outlined here.
Visit tryb2bleads.in to get started