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What Is Intent Data?

Intent data reveals which companies are actively researching solutions like yours. It includes:

First-party intent signals:

• Website visits and page views
• Content downloads and form fills
• Pricing page engagement
• Product demo requests
• Email opens and clicks

Third-party intent signals:

• Industry publication reading patterns
• Competitor research activity
• Review site visits
• Technology adoption patterns
• Job posting changes

Buying signals:

• Funding announcements
• Leadership changes
• Hiring surges in relevant departments
• Technology stack changes
• Company expansion news

The problem: Most teams have intent data but lack the automation to act on it quickly. By the time you manually research and reach out, the buying window closes.

Why AI + Intent Data Works

Traditional prospecting operates on static lists. You identify 1,000 companies that fit your ICP and blast outreach to all of them simultaneously. Result: 1-3% response rates because only 5-10% are actually in-market.

AI + intent data changes the equation:

Speed: AI processes intent signals in real-time and triggers outreach within hours, not days
Personalization: AI crafts messages referencing the specific signals that indicate buying intent
Prioritization: AI scores prospects based on signal strength, focusing your team on hottest opportunities
Timing: AI reaches out when buying intent peaks, not on arbitrary campaign schedules

Real-world impact: Teams using AI to act on intent data report 15-30% reply rates versus 1-3% for blind outreach. That's 10x improvement from better timing and relevance.

The 5-Step Framework

Step 1: Identify Your Intent Signals

Not all signals matter equally. Map which behaviors actually correlate with buying:

High-intent signals (act within 24 hours):

• Pricing page visits
• Demo requests
• Multiple team members visiting your site
• Competitor comparison research
• Product-specific content downloads

Medium-intent signals (act within 1 week):

• Blog content consumption
• Industry report downloads
• LinkedIn profile views of your team
• Job postings for relevant roles
• Technology evaluation activity

Low-intent signals (nurture for later):

• Single website visits
• Social media follows
• General industry content reading
• Conference attendance

Action: Use your CRM data to validate which signals actually convert. Look at closed-won deals and work backward to identify the signals that appeared 30-90 days before purchase.

Step 2: Choose Your Intent Data Sources

You need both first-party and third-party data:

First-party tools:

• Website tracking (Google Analytics, Segment, Heap)
• Email engagement (HubSpot, Salesforce)
• Product usage data (for PLG companies)
• CRM interaction history

Third-party intent providers:

• Lusha (contact data + basic intent)
• Persana AI (real-time enrichment + signals)
• Amplemarket (buying intent + technographic data)
• ZoomInfo, 6sense, Bombora (enterprise intent platforms)

Integrated platforms:

• Eve by Cykel (combines prospecting, intent detection, and automation in one platform)

Pro tip: Start with first-party signals you already capture. Add third-party data once you've proven ROI on owned signals.

Step 3: Connect AI Automation to Intent Triggers

This is where most teams fail. They collect intent data but don't automate the response. Here's how to connect them:

Option A: Build custom workflows

Use platforms like Zapier or Make to connect intent sources to outreach tools:

• Website visitor identified → Enrich in Apollo → Add to Instantly sequence
• LinkedIn profile view detected → Research in Clay → Send personalized message via Expandi

Downside: Requires 5+ tools, complex integrations, constant maintenance.

Option B: Use integrated AI SDR platforms

Platforms like Eve by Cykel detect intent signals and trigger outreach automatically:

• Company posts job for Head of Sales → Eve identifies buying signal → Creates targeted sequence → Books meeting

Advantage: Intent detection, research, and outreach happen in one system. No integration required.

Step 4: Personalize Outreach Based on Intent

Generic messages kill conversion, even with perfect timing. AI should reference the specific signal:

Bad (ignoring intent):
"Hi John, I noticed you work at Acme Corp. We help companies like yours with sales automation."

Good (referencing intent):
"Hi John, noticed you checked out our pricing page yesterday and spent time on our LinkedIn automation features. Most teams exploring that combination are trying to scale outbound without adding headcount. Is that what you're solving for?"

Better (multiple signals):
"Hi John, saw Acme just posted for 2 SDR roles and your team visited our site 3 times this week, including pricing and integration pages. Looks like you're scaling outbound. We help companies at your stage go from 5 meetings/week to 25+ without hiring. Worth a 15-min conversation?"

AI platforms like Eve automatically generate these personalized messages by analyzing which signals fired and crafting contextual outreach.

Step 5: Prioritize and Route Based on Signal Strength

Not every signal deserves immediate action. Use AI to score and route:

Hot leads (score 80-100):
Multiple high-intent signals within 7 days → Immediate personal outreach from AE

Warm leads (score 50-79):
Medium-intent signals or single high-intent signal → AI-powered sequence with human review

Cold leads (score 0-49):
Low-intent signals only → Nurture campaign, revisit when score increases

Prospects scoring 70+ get immediate personalized outreach. Below 50 goes into nurture.

Common Mistakes to Avoid

Mistake 1: Collecting intent data but not acting fast
Intent signals decay rapidly. A pricing page visit is hot for 24-48 hours, not 2 weeks. Use AI to respond within hours.

Mistake 2: Treating all signals equally
A LinkedIn profile view doesn't equal a pricing page visit. Score signals based on actual conversion data.

Mistake 3: Over-automating without personalization
Generic "I saw you visited our site" messages feel creepy and convert poorly. Reference specific behaviors and add value.

Mistake 4: Ignoring negative signals
If a prospect unsubscribes, visits your careers page (they want a job, not your product), or engages with competitor content, suppress them. AI should respect these signals.

Tools That Combine AI + Intent

All-in-one platforms:

• Eve by Cykel (prospecting, intent signals, automation unified)
• Amplemarket (data + intent + sequences)

Intent data providers:

• Lusha, Persana AI, ZoomInfo, 6sense

AI automation tools:

• AiSDR, Reply, Instantly

Best approach for most teams: Start with an integrated platform like Eve that handles intent detection and automation together. Add specialized intent providers once you've proven ROI.

Getting Started

Week 1: Identify which intent signals correlate with your closed-won deals
Week 2: Set up tracking for those signals (first-party + one third-party source)
Week 3: Connect AI automation to trigger on high-intent signals
Week 4: Test messaging variations and measure reply rates

The combination of AI automation and intent data isn't optional anymore. It's how modern sales teams prospect. The question is whether you'll implement it before your competitors do.

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