Using Product Intent for Lead Scoring: Enhancing Lead Qualification | SMRTMR

For years, marketing teams relied on demographic + activity-based lead scoring to decide who was “sales-ready.” Job title? +10. Company size? +5. Webinar attended? +15.

It worked - until it didn’t.

In today’s buying environment, buyers research silently, engage non-linearly, and signal intent long before they ever fill out a form. If your lead scoring model still treats email opens and whitepaper downloads as primary buying signals, you’re not qualifying demand - you’re guessing.

This is where product intent fundamentally changes the game.

Product intent moves lead scoring from engagement-based assumptions to behavior-backed buying signals. It tells you who is actively evaluating your product, what they care about, and how close they are to a decision.

And when implemented correctly, it dramatically improves MQL quality, sales trust, and pipeline efficiency.

What Is Product Intent (And What It Is Not)

Let’s be very clear.

Product intent is not just “interest.”
It is observable behavior that indicates evaluation, comparison, or readiness related to a specific product or capability.

True Product Intent Signals Include:

• Repeated visits to product, pricing, or comparison pages

• Engagement with feature-specific content

• Trial sign-ups or sandbox usage

• API documentation views

• Integration-related content consumption

• High-frequency, short-interval site visits tied to the same account or individual

• Return behavior after sales outreach

What Product Intent Is NOT:

• One-time blog reads

• Generic TOFU content engagement

• Vanity metrics like impressions or single clicks

• Blind third-party intent without internal validation

Intent without context is noise.
Intent aligned with product capability is signal.

Why Product Intent Belongs at the Core of Lead Scoring

Traditional lead scoring answers one question:

“Is this lead engaged?”

Product intent answers a far more important one:

“Is this lead evaluating our product right now?”

When product intent is layered into lead scoring:

• MQLs drop in volume - but rise sharply in quality

• Sales stops questioning marketing-sourced leads

• Conversion rates improve across every downstream stage

• Pipeline velocity increases

• Attribution becomes defensible, not emotional

In short:
Product intent aligns marketing scoring with how buyers actually buy.

How I Approach Product Intent–Driven Lead Scoring (Marketo-First)

After designing and rebuilding multiple lead scoring frameworks across enterprise environments, I follow one principle:

Scoring should reflect buying motion, not marketing activity.

Here’s how I structure it.

1. Separate Engagement Scoring from Intent Scoring

The biggest mistake I see teams make is blending everything into one score.

Instead:

• Engagement Score = email, events, content, awareness

• Product Intent Score = product-facing, capability-specific behavior

Only product intent should meaningfully influence MQL readiness.

Engagement warms leads.
Intent qualifies them.

2. Weight Product Intent Higher Than All Other Behaviors

If someone:

• Visits pricing multiple times

• Reads feature documentation

• Compares integrations

• Returns within 48 hours

That behavior should outweigh three webinars and ten email clicks combined.

In my scoring models:

• Product intent contributes 50–70% of MQL qualification weight

• Demographics validate fit, not readiness

• Engagement confirms awareness, not urgency

3. Apply Time Decay Aggressively

Intent is time-sensitive.

A pricing page visit from six months ago means nothing.
Five product page visits in three days means everything.

I always:

• Apply recency-based decay

• Spike scores for compressed behavior windows

• Reset intent scores if signals go cold

Intent without recency is just historical interest.

4. Score at Both Lead and Account Level

In B2B, deals are rarely single-threaded.

One individual may show intent - but buying happens at the account level.

Best practice:

• Individual intent contributes to lead score

• Aggregated intent contributes to account qualification

• Account-level intent can pull in otherwise cold contacts

This is especially critical for CXO and buying committee modeling.

Real-World Case Study: Turning Noisy Leads into Revenue Signals

The Problem

In one enterprise environment I worked with:

• Marketing was generating high MQL volume

• Sales acceptance was low

• AEs claimed leads were “not serious”

• Conversion from MQL → SQL was underperforming

Classic symptoms of engagement-heavy scoring.

The Shift

We redesigned lead scoring around product intent, not campaigns.

Key changes:

• Introduced product capability scoring

• Weighted pricing, integration, and comparison behavior heavily

• Applied strict recency rules

• Introduced account-level intent rollups

• Reduced demographic inflation

The Outcome

Within one quarter:

• MQL volume dropped by ~30%

• Sales acceptance increased significantly

• MQL → SQL conversion improved materially

• Pipeline influenced by marketing became defensible

• Sales trust in scoring logic improved (this matters more than dashboards)

The biggest win?
Sales stopped asking “Why is this an MQL?”
They started asking “Do you have more like this?”

That’s when you know scoring is working.

Common Mistakes to Avoid

Let me be blunt - most intent implementations fail because of these mistakes:

• Treating intent as just another score field

• Over-scoring third-party intent without validation

• Ignoring recency

• Mixing awareness and evaluation behaviors

• Letting scoring logic become politically driven

• Optimizing for volume instead of conversion

Lead scoring is not a popularity contest.
It is a qualification system.

The Bigger Picture: Product Intent as a Revenue Language

When product intent is embedded correctly:

• Marketing speaks the same language as sales

• Reporting shifts from “leads generated” to “demand identified”

• Attribution becomes behavior-driven

• Predictive models become possible

• CXO-level insights stop being anecdotal

Product intent is not just a scoring enhancement.
It is the foundation of modern revenue intelligence.

Conclusion: Qualify Reality, Not Activity

If there’s one thing I’ve learned over the years, it’s this:

Buyers don’t announce intent. They reveal it.

Your job as a marketer is not to create noise - it’s to detect truth.

Product intent allows you to:

• Stop guessing

• Stop over-scoring curiosity

• Stop flooding sales with false positives

And start qualifying real buying motion.

About Me

I’m Raghav Chugh, a seasoned digital marketing and technology professional with nearly two decades of experience designing scalable, data-driven marketing systems. I hold four Marketo Certified Expert (MCE) certifications and have spent years deep in lead lifecycle architecture, behavioral analytics, database governance, and revenue attribution.

My work focuses on turning marketing data into decision-grade intelligence - not just dashboards. I specialize in aligning marketing automation, intent signals, and analytics to how revenue teams actually operate.

You can connect with me on LinkedIn here:
https://www.linkedin.com/in/raghavchugh/

About SMRTMR.com

This article is published on SMRTMR.com (Strategic Marketing Reach Through Marketing Robotics).

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