The marketing leader celebrates hitting their MQL target. Meanwhile, the sales team groans at another batch of “qualified” leads they don’t believe in.
Sound familiar? This is not signal-based ABM.
We’ve created a fundamental disconnect in B2B organizations: marketing teams are incentivized to generate volume, while sales teams are held accountable for quality. And the metrics we’ve relied on for years — MQLs, lead scores, and basic attribution models — are only making the problem worse.
This dysfunctional cycle is costing B2B companies millions in wasted marketing spend, sales inefficiency, and missed opportunities. The core issue isn’t that either team is failing—it’s that they’re operating from completely different intelligence.
Signal-based ABM Solves Traditional Lead Qualification Problem
For most B2B companies, the marketing-sales handoff has become a friction point rather than a seamless transition. Here’s what typically happens:
- Marketing generates leads through various channels and scores them based on demographic data and engagement metrics
- Once leads hit a certain threshold score, they become MQLs and get routed to sales
- Sales reviews these MQLs, rejects a significant percentage, and focuses on the ones they believe are actually qualified
- Marketing gets frustrated that their “qualified” leads aren’t being followed up properly
- Sales gets frustrated with low-quality leads that waste their time
- Both teams retreat to their corners, each believing the other doesn’t understand their challenges
Why Traditional MQLs Are Failing Both Teams
The MQL framework was created when marketing had limited ability to understand true buying intent. It relies on proxies like form fills, content downloads, and email clicks — actions that may or may not indicate genuine purchase interest.
These engagement metrics tell you someone is interested in your content, but they don’t reliably predict if an account is actively in-market. And for complex B2B purchases involving multiple stakeholders, individual lead scoring becomes even less effective.
Sales teams know this instinctively. They’re looking for actual buying signals:
- Budget discussions and approval processes
- Active evaluation of multiple vendors
- Executive sponsorship and timeline commitments
- Genuine business pain that demands immediate action
Traditional MQLs rarely capture these critical indicators, creating a fundamental disconnect between what marketing provides and what sales needs.
When marketing and sales align around this approach, the traditional divide disappears, replaced by a unified revenue team focused on what really matters: driving business growth.
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Signal-Based ABM: A New Approach to Qualification
Account-Based Experience (ABX) starts by acknowledging that B2B buying is an account-level decision, not an individual one. Signal-based ABM takes this further by focusing on actual buying intent signals rather than arbitrary lead scoring thresholds.
Here’s how it transforms the marketing-sales relationship:
1. Unified Intelligence
Instead of marketing tracking form fills while sales tracks discovery calls, both teams operate from a shared signal intelligence foundation. This includes:
- First-party engagement data across all channels and touchpoints
- Third-party intent signals showing research and evaluation activity
- Technographic data revealing competitive opportunities
- AI-enriched insights about account behavior patterns
When both teams can see the same signals, they begin speaking the same language about what constitutes a qualified opportunity.
2. Account-Level Focus
Signal-based ABM shifts from qualifying individual leads to qualifying entire accounts based on collective buying group activity. This aligns with how enterprise deals actually happen — through multiple stakeholders working together, not a single decision-maker.
This account-centric view helps both teams understand:
- Which accounts show genuine buying intent
- Which stakeholders are involved in the decision
- Where each account is in their buying journey
- What specific triggers activated their interest
3. Signal Pattern Recognition
The most powerful aspect of this approach is identifying signal combinations that truly predict purchase readiness. For example:
- When 3+ stakeholders from the same account engage with competitive comparison content within a two-week period
- When technical evaluation content engagement is followed by pricing page visits from finance team members
- When engagement patterns mirror those of your best recently closed customers
These signal patterns become a shared qualification language that both teams trust because they’re based on actual buying behaviors, not marketing assumptions.
The Results: Alignment Around What Matters
Companies implementing signal-based ABM consistently report transformative changes in the marketing-sales relationship:
- Higher conversion rates: MQL-to-SQL conversion improves by 40-60% when both teams align on qualification criteria
- Faster sales cycles: When sales trusts marketing’s signals, they engage accounts more quickly and progress deals more efficiently
- Resource optimization: Marketing spends less time defending lead quality and more time optimizing campaigns
- Revenue acceleration: Pipeline velocity increases as accounts move more smoothly between marketing and sales
Most importantly, the constant tension between teams begins to dissolve. Marketing stops pushing MQL volume metrics that sales doesn’t value. Sales stops dismissing marketing’s contribution to pipeline. Both teams start collaborating around a shared goal: identifying and converting accounts that are genuinely ready to buy.
Moving Forward: Implementing Signal-Based ABM
Transforming your approach doesn’t happen overnight, but these steps can start you on the path:
- Audit your current signals: What data points do marketing and sales currently use to define “qualified”?
- Build a unified signal foundation: Create a shared view of account activity and intent that both teams can access
- Define signal patterns: Work together to identify combinations of signals that truly indicate buying intent
- Align on a new qualification framework: Replace arbitrary MQL definitions with signal-based qualification criteria
- Measure what matters: Track conversion rates, pipeline velocity, and deal progression rather than just lead volume
The future of B2B revenue generation isn’t about generating more MQLs — it’s about leveraging signal intelligence to identify the right accounts at the right time, and creating seamless experiences that convert them into customers.
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