In B2B marketing, the instinct is often to go wide: more leads, more outreach, more activity. But in today’s buying environment, more doesn't always mean better.
We believe the best marketers aren’t just lead generators—they’re probability optimizers.
Rather than chasing quantity, the modern B2B marketer should focus on identifying and nurturing the leads most likely to convert—not just those most likely to click.
Why “Lead Volume” Is an Outdated Metric
Historically, B2B marketing was evaluated by how full the funnel appeared. If you delivered thousands of leads, you were seen as doing your job. But the truth is, low-quality leads clog sales funnels, waste resources, and create organizational friction.
61% of B2B marketers say that poor lead quality is one of the biggest reasons marketing-sourced leads don’t convert.
— DemandGen Report, 2023[^1]
Marketing must evolve from being a lead factory to becoming a probability engine—a system that generates and prioritizes the right leads based on likelihood to progress and convert.
Understanding “Probability-Weighted” Lead Generation
A better use of time and resources is to invest in identifying buying signals, understanding intent, and using behavioral data to predict which accounts are in-market and which are not.
This is the crux of what Kerry Cunningham (6sense) and John Steinert (TechTarget) explore in their work on probabilistic vs. deterministic models in go-to-market (GTM) strategies. They argue:
“Marketing is about increasing the probability that a sale will occur. When marketers focus on engaging the right accounts with the right content, they create the conditions for sales success.”
— Kerry Cunningham, 6sense[^2]
Cunningham explains this in the context of pre-pipeline activity—the crucial phase where anonymous buying behavior (like content consumption or competitor comparisons) often begins months before sales ever hears about it.
High-Probability Leads: What Sets Them Apart?
A high-probability lead is not defined by how fast they filled out your form—but by what they’re doing before and after that interaction. Signals that indicate a high probability include:
- Multiple individuals from the same account engaging with related content (buying group behavior)
- Intent signals from third-party networks (e.g., TechTarget, Bombora)
- Repeat visits and longer dwell time on specific product or solution pages
- Engagement with mid-funnel assets like case studies, pricing, or ROI calculators
- Responses to specific, high-friction CTAs (e.g., requesting a demo or pricing)
90% of the B2B buying journey may be completed before a customer reaches out to a sales rep.
— Forrester, 2023[^3]
In this context, marketing’s influence is upstream—building affinity, trust, and clarity early so that when sales steps in, the path to close is smoother and faster.
Time Well Spent: Moving from Volume to Precision
Let’s reframe how we think about marketing efficiency. The question isn't “How many leads did we generate?” It’s:
- How much time did we spend on accounts with actual buying intent?
- What percentage of those accounts moved deeper into the funnel?
- How many of those converted into opportunities that closed?
High-performing marketers today are reallocating their time to:
- Refine ICPs (ideal customer profiles) using real behavior data, not gut feel
- Collaborate with sales on target account lists that evolve dynamically based on signal
- Build nurture programs personalized to buying group personas and stage
- Use AI-powered scoring models to prioritize outreach and content based on conversion likelihood
How AI Supercharges High-Probability Lead Targeting
The volume of data modern marketers have access to is both a gift and a challenge. That's where AI comes in—not to replace marketers, but to make them more precise.
Artificial intelligence helps B2B marketing teams:
- Score leads dynamically using multiple signals—behavioral, firmographic, technographic, and intent—rather than static rules.
- Predict purchase intent using historical data patterns across industries, verticals, and buying stages.
- Prioritize accounts based on likelihood to convert and potential revenue impact, not just engagement volume.
- Generate personalized content and outreach at scale that aligns with a buyer's stage, persona, or pain point.
According to McKinsey, B2B companies that use AI in their sales and marketing workflows have seen up to a 50% increase in leads and appointments, and a 40–60% reduction in customer acquisition costs[^4].
Platforms like 6sense, Demandbase, and Drift now offer AI-driven recommendations on which accounts to prioritize, which channels to use, and what messaging resonates most—turning probabilistic targeting into something scalable and actionable.
AI enables marketers to spend less time chasing every possible lead and more time accelerating the right ones toward revenue.
Probability Is the New Performance Metric
The best B2B marketers aren't chasing vanity metrics. They’re engineering better odds.
By shifting focus from lead volume to lead quality and conversion probability, they’re improving not just marketing efficiency—but business outcomes.
In a noisy, competitive B2B landscape, the marketer who helps sales spend time in the right place will always win. Not because they made more noise—but because they made more sense.
Citations
[^1]: DemandGen Report, 2023 B2B Buyer Behavior Survey
[^2]: 6sense Webinar, Probabilistic & Deterministic GTM with Kerry Cunningham and John Steinert, 2024
[^3]: Forrester, The B2B Buying Journey Has Changed, 2023
[^4]: McKinsey & Company, The Future of B2B Sales Is Hybrid, 2022
Photo by Brett Jordan on Unsplash