"We already have intent data. Why do we need buying signals?"
I hear this question constantly. It reveals a fundamental confusion in the market.
Intent data and buying signals are not the same thing. They measure different behaviors, operate on different timelines, and serve different purposes.
Let me explain.
What Intent Data Actually Measures
Intent data tracks content consumption patterns across the web.
When someone at Acme Corp reads articles about "CRM software comparison" or "best sales tools 2026," intent data providers detect that activity and flag Acme Corp as "showing intent" for CRM software.
How it works:
- Publishers install tracking pixels
- Visitors consume content (read articles, download guides)
- Provider aggregates activity by company (via IP matching)
- Companies with above-baseline activity get flagged
Major intent data providers:
- Bombora (Intent data co-op)
- G2 (Review site intent)
- TrustRadius (Review site intent)
- 6sense (Proprietary + aggregated)
What intent data tells you:
- Company is researching a topic
- Research intensity (surge vs. baseline)
- Topics being researched
- Sometimes: specific individuals researching
What Buying Signals Actually Measure
Buying signals track business events and changes that indicate purchasing likelihood.
When Acme Corp raises a Series B, hires a new VP of Sales, and posts 5 SDR roles, those are buying signals. They indicate the company is in a position to buy—regardless of what content they're consuming.
Types of buying signals:
- Funding events - New capital to spend
- Executive changes - New decision-makers
- Hiring patterns - Growth and priorities
- Tech stack changes - Active evaluation
- Organizational changes - M&A, restructuring
- Growth indicators - Revenue, expansion
What buying signals tell you:
- Company has budget (funding)
- Company has new priorities (leadership)
- Company is scaling (hiring)
- Company is actively changing (tech stack)
The Critical Difference
Here's the key distinction:
Intent data: Someone at the company is researching
Buying signals: The company is positioned to buy
Research doesn't equal purchase. Plenty of people research things they'll never buy:
- Competitors doing market research
- Analysts writing reports
- Students doing homework
- Employees with no buying authority
Buying signals indicate structural changes that create purchasing conditions:
- Budget (funding)
- Authority (new executives)
- Need (rapid growth, pain)
- Timeline (urgency from change)
When Intent Data Works Well
Intent data is valuable when:
1. You have a broad category If you sell "marketing software," intent data helps narrow the universe. Someone researching marketing automation is more relevant than someone researching unrelated topics.
2. You need volume Intent data can flag thousands of accounts. If your SDR team needs high volume, intent data provides it.
3. You're running advertising Intent data is excellent for ad targeting. Show ads to companies researching your category.
4. You want topic-level insights Intent data tells you what someone is researching. This helps with messaging and content strategy.
When Buying Signals Work Better
Buying signals are superior when:
1. You want quality over quantity Signal-verified accounts convert at 3-5x higher rates than intent-only accounts.
2. You're doing direct outreach Signals provide specific context for personalization. "Congrats on the Series B" beats "I noticed you're researching CRM software."
3. You have a defined ICP If you know exactly who buys your product, signals help you find them at the right moment.
4. You're competing on timing Signals decay fast. The team that reaches a new VP first wins. Intent data is often 2-4 weeks delayed.
The Ideal Stack
The best sales teams use both, but differently:
Intent data for:
- Advertising targeting
- Content recommendations
- Broad prioritization
- Market research
Buying signals for:
- Direct outreach prioritization
- Personalization context
- Account timing
- Sales team focus
Signal + Intent: The Triangulation Effect
The real magic happens when you combine them.
Intent only:
"Acme Corp is researching sales tools"
Could be anyone, for any reason. 60% noise.
Signal only:
"Acme Corp raised Series B and hired new VP Sales"
Clearly positioned to buy, but buy what? 70% relevant.
Signal + Intent:
"Acme Corp raised Series B, hired new VP Sales, AND is researching sales tools"
This is a qualified, in-market account. 90%+ relevant.
When a company has buying signals AND shows intent, you have near-certainty they're actively evaluating.
The Data Quality Problem
Both intent data and buying signals suffer from quality issues.
Intent data problems:
- IP-to-company matching is imprecise
- Can't identify individuals (usually)
- 2-4 week data lag
- High false positive rate
- Competitive research looks like buying intent
Buying signal problems:
- Not all signals are equally predictive
- Some signals are hard to detect
- Context matters (signal + situation)
- Single signals have noise
The solution for both: triangulation. Multiple signals + intent = high confidence.
Practical Recommendations
If you're just starting out: Start with buying signals. They're more actionable for direct sales and provide built-in personalization context.
If you have intent data already: Add buying signals to identify which intent accounts are actually positioned to buy. Use intent as a filter, not the primary signal.
If you have buying signals already: Add intent data to prioritize which signal-verified accounts are actively researching. The combination is powerful.
If you're resource-constrained: Focus on buying signals for outbound, intent data for inbound/marketing. Don't try to do everything.
The Bottom Line
Intent data tells you someone is looking.
Buying signals tell you someone is ready.
The best sales teams know both.
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