How to Use Intent Data for Better Outbound Outreach

If you’ve ever launched an outbound campaign and wondered why only a handful of responses trickled in, intent data might be what you’re missing—or misusing.

Done right, it can help you stop sending “spray and pray” emails and start reaching out to the right people, at the right time, with the right message.

But like most tools in the sales stack, how you use it matters more than whether you have it.

Let’s break it down.

What Is Intent Data (and Why Most People Get It Wrong)?

Intent data is a signal. It's what tells you, “Hey, someone at Company X might be interested in what you offer.” This could come from a variety of sources—visiting your pricing page, reading multiple blogs, engaging with competitor comparisons, or downloading an industry report.

Tools like:

• Clearbit (for deanonymizing traffic)
• Leadfeeder (to track who’s visiting your site)
• Factors.ai (for journey mapping and page-level intent)
• RevSure/RB2B (for external buying signals)

...are all trying to do the same thing: help you identify buyer interest before they fill out a form.

Here’s the catch: most tools get it right only 20% to 50% of the time. That means for every 10 signals, 5 to 8 are noise.

So what do you do with that?

Define Your ICP First, Not After

Before diving into the data, nail your ICP (Ideal Customer Profile). Who is your best-fit customer in terms of:

• Company size
• Industry
• Tech stack
• Geography
• Role/title of buyer

Without this, you'll end up chasing false positives—companies showing some activity but that were never a real fit to begin with.

Once your ICP is tight, run your intent data through this filter. Yes, your list will shrink. But that’s exactly the point.

Fewer, better accounts > More, random accounts.

Segment Based on Intent Strength

Not all intent is equal. A company visiting your careers page once is different from one that:

• Spends 4 minutes on your pricing page
• Downloads a case study
• Comes back a second time to compare solutions

Segment your accounts into:

• High Intent: Pricing views, demo requests, repeat visits
• Mid Intent: Product pages, feature comparisons, blogs
• Low Intent: Homepage bounce, visiting careers or culture blog

Now match your messaging accordingly:

• High intent → Nudge to take action (short emails, assume familiarity)
• Mid intent → Connect the dots (why this solves their problem)
• Low intent → Educate (start at TOFU, build trust over time)

This makes sure your outreach respects where the buyer is in their journey.

Map the Whole Buying Committee

Intent data rarely tells you exactly who at the company is showing interest. It just tells you that someone is. Could be a user, a champion, a researcher—or someone just curious.

That’s why stopping at one contact is risky. Instead, you need to map the full buying committee:

• Who’s the decision-maker?
• Who will actually use the product?
• Who controls the budget?
• Who can block the deal?

A single high-intent signal (like a visit to the pricing page) should trigger deeper research into the account. Use tools like LinkedIn Sales Navigator or Apollo to build a list of relevant personas across departments.

Then personalize your outreach by role and function. A message to a Head of Ops will look very different from one to a Product Lead.

Intent gives you the door. Mapping the committee helps you walk through it—with the right message for each person on the other side.

How Human SDRs Can Use Intent Data

If you’re doing this manually as an SDR or AE:

1. Get alerts or exports from your intent platform.
2. Run those accounts through your ICP filters.
3. Manually check session journeys (especially if using tools like Factors.ai).
4. Find relevant contacts and enrich with LinkedIn, news, or recent company updates.
5. Build and send personalized messages tailored to intent level.

This works. But it’s slow. Done properly, it can take 30-45 minutes per account. And that adds up fast when you’re working with dozens—or hundreds—of accounts.

How AI SDRs Can Do This at Scale

AI SDRs (like Luru) are built for exactly this kind of task.

Here’s how a good AI SDR handles intent data:

• Connects to multiple intent sources: website visits, G2 activity, CRM behavior
• Filters based on your ICP: using firmographic and technographic criteria
• Scores and segments accounts: into high/mid/low intent buckets
• Sprawls the account: identifies all relevant stakeholders
• Writes messaging: tailored to role and stage of intent
• Launches smart sequences: across email, LinkedIn, and even WhatsApp/calls if needed

Even better, the human in the loop ensures the final messaging passes the “does this sound like a person wrote it?” test.

No robotic messages. No weird off-brand intros. Just consistent, human-quality outreach—at scale.

TL;DR

• Intent data is useful, but only when used with filters and thought.
• Your ICP is the first filter. Apply it ruthlessly.
• Segment accounts by intent strength and tailor your messaging accordingly.
• Don’t stop at one person—map the entire buying committee.
• AI SDRs can automate this whole process without losing the human touch.

Blind outreach is dead. Smart outreach—driven by intent and powered by AI—is how you break through.

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