Last month, we made the case for a critical shift in how revenue teams think: from chasing leads to scoring accounts. As B2B buying grows more complex: with multi-threaded decision makers, longer sales cycles, and crowded inboxes, leaning too hard on lead-level signals or intent alone can leave big opportunities overlooked. Account scoring brings clarity to the chaos by helping you identify the companies that look like your best customers, whether or not they’re “active” today.
But what happens after you identify the right accounts?
This is the leap many teams fail to make: they know who they want to sell to, but not how much that account is worth, or when the revenue is likely to materialize. Without those dimensions, your TAM model remains theoretical, your prioritization stays reactive, and your pipeline strategy starts to blur.
That’s where weighted TAM comes in. It’s what happens when you connect your pricing model to your scoring logic and start to see your market through the lens of revenue probability, not just intent heat or fit quality.
Total Addressable Market (TAM) is one of those concepts that sounds strategic but often gets reduced to a slide in a pitch deck. A classic back-of-the-napkin calculation: “We sell to mid-market financial firms. There are 20,000 of them in North America. Our ACV is $30K. So, $600M TAM.”
It’s useful for storytelling, not for strategy. Because in real life, not all ICP-fit companies are equal. Two accounts might check the same boxes: industry, size, role titles, but have vastly different revenue potential based on usage complexity, rollout velocity, or expansion likelihood.
Here’s an example:
Now here’s the curveball: Company B is clicking every ad. Company A hasn’t filled out a form.
If you’re only looking at intent or activity volume, you go after Company B. But if you’re modeling both fit and value, you recognize that Company A, even with lighter signals, is the whale.
This is where weighted TAM changes how you operate. Weighted TAM is the more intelligent way of scoring what’s already in your market.
Weighted TAM = Total Account TAM × Propensity-to-Buy Score
It brings together two key ingredients:
So instead of saying “Company X is a fit” or “Company Y is active,” you now ask: which accounts are worth the most soon?
If an account could be worth $150K but has a low score, maybe it goes into a nurture stream. If an account is worth $50K but has a high score and clear buying signals, sales can strike while the iron’s hot.
In this model, prioritization becomes multidimensional. You’re stopping sales reps from chasing noise and guiding their efforts by both revenue potential and timing.
We’ve seen this play out with teams that felt “account-based” in theory but still chased leads in practice.
One mid-sized SaaS company we work with had built a detailed ICP and scoring model: firmographics, tech stack, engagement behavior. But reps were still frustrated: they were closing deals, but the deals were small. Pipeline value was too low to hit their growth targets.
The breakthrough came when they layered in account-level pricing estimates. By estimating expansion potential (e.g., seat count, feature fit, historical LTV by segment), they recalibrated their opportunity scoring. Now, sales wasn’t just optimizing for activity. They were optimizing for outcome.
As a result, average deal size increased by 34% in two quarters, not because they chased bigger logos, but because they prioritized high-fit accounts with high modeled value.
Another example: a PLG company with usage-based pricing used weighted TAM to re-rank their onboarding accounts. By combining product telemetry (number of active users, integrations deployed) with revenue model projections, they surfaced early-stage customers with 10x expansion potential. Customer success teams shifted their focus, and expansion revenue spiked.
In the ZIRP (Zero Interest Rate Policy) era, TAM was an aspirational number—something to signal upside. Today, it needs to be operational. You can’t just ask, “What’s our market size?” You need to ask, “Where’s our revenue most likely to come from next quarter?” and “How do we efficiently generate that revenue?”
Weighted TAM connects GTM functions that often work in silos:
It also creates tighter feedback loops. As deals close (or don’t), you refine both your scoring and pricing models. Over time, your TAM model doesn’t just describe the market, it predicts it.
We believe this is where B2B revenue teams are headed: toward a weighted, account-level understanding of their market, where pricing isn’t just a downstream step but an upstream input to prioritization.
With revenue teams being constrained by limited time, finite bandwidth, and high expectations, your best move is to focus on the accounts that will actually move the needle.
That’s why we’re building this logic into the foundation of our platform, because revenue success in B2B doesn’t come from chasing the most active accounts. It comes from focusing on the most valuable ones, at the moment they’re most likely to buy.