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Your ICP list has 500 companies on it. Your SDR has time for 30 outreach sequences this week.
How do you decide which 30?
Most teams either go by gut ("these feel like the right accounts"), go by recency ("whoever came into the CRM this week"), or go by ICP score alone. And the result is the same: a pipeline that's full of ICP-fit accounts that never close because no one checked if those accounts were actually ready to buy. Gartner research on account-based strategy confirms the pattern: intent data - signals of active buying behaviour - is consistently the missing layer in account prioritisation, with 70% of B2B marketers now recognising it as a necessary complement to firmographic ICP scoring.
ICP fit is the baseline. It's not the differentiator.
Why ICP Score Alone Fails Your Pipeline
Your Ideal Customer Profile captures the firmographic and technographic characteristics of your best-fit accounts - company size, industry, tech stack, team structure. It tells you: if this company buys our product, they're likely to get value from it.
What it doesn't tell you is: is this company in a position to buy right now?
Two companies can have identical ICP scores with completely different buying realities and this is precisely why qualified leads don't close at the rate your pipeline suggests they should. The Ehrenberg-Bass Institute's 95:5 rule (LinkedIn B2B Institute, 2021) quantifies this: because B2B vendors are typically replaced every five or more years, approximately 95% of your ICP is out of market in any given quarter:
- Company A: 14 months into a strong relationship with your closest competitor. Just renewed. Active champions at the vendor. No evaluation underway.
- Company B: 8 months into a difficult implementation with a competitor. Renewal in 45 days. Three seats reduced last month. Champion just left.
On your ICP scoring model, these two companies look the same. In reality, Company A is effectively out of market; Company B is one bad renewal conversation away from a switch.
If your prioritisation process can't distinguish between these two accounts, you're routing your reps' time to a coin flip.
The Tri-Score Framework: ICP Fit × Purchase Intent × Win Likelihood
The framework that closes this gap adds two dimensions to your existing ICP model:
Dimension 1: ICP Fit -> What you're already measuring. Firmographic match, tech stack alignment, team size, industry fit. This is your filter, it removes companies that aren't worth pursuing regardless of timing.
Dimension 2: Purchase Intent -> Evidence that a company is actively considering a change. For a detailed breakdown of what genuine purchase intent signals look like, and how to distinguish them from casual interest, see how to know when a prospect is actually ready to buy. Not inferred from content consumption - that's weak intent. Direct evidence: competitor trial activity, renewal windows opening, seat count declining, negative vendor reviews posted, product incidents at the current vendor. Gartner's analysis of B2B intent data in ABM draws the same distinction: direct buying signals (competitive research, renewal-stage activity) are strong indicators; passive content engagement is weak.
Purchase intent is the timing dimension. It separates accounts that are passively ICP-fit from accounts that are actively in a buying motion right now.
Dimension 3: Win Likelihood -> Not every in-market opportunity is equally winnable. A company 6 weeks into a Zendesk trial that's going well is a harder competitive fight than a company 2 weeks into an Intercom trial with visible signs of friction.
Win likelihood is derived from historical competitive outcomes: which accounts, in which situations, with which signals, convert to customers? This is where data at scale separates teams that guess from teams that know.
The Tri-Score is the intersection of all three. An account that's ICP-fit, actively in-market, and winnable based on competitive context. That's a Qualified Opportunity - the highest-value unit of work your reps can touch.
How to Score Each Dimension
Scoring ICP Fit
Your ICP scoring model should include at minimum:
- Company size (employee count, revenue band)
- Industry and sub-industry
- Tech stack (current tools in the relevant category)
- Team structure (presence of dedicated CS/CX function)
- Geographic market
Weight these based on what your best existing customers look like, not based on theory. The most dangerous ICP model is one built on aspiration rather than evidence.
Score range: 1–10 per company. Minimum threshold to advance: 6+. For a framework on building the account list that feeds this scoring model, see 6 strategies to build high-quality target account lists.
Scoring Purchase Intent
This is where most teams are flying blind — and where the most leverage exists.
Strong purchase intent signals (score these higher):
- Competitor trial detected: Direct evidence of active evaluation
- Renewal window opening: 60–90 days before renewal, decision-making begins
- Seat count reduction: Usage decline suggests dissatisfaction
- Champion departure: New stakeholder = fresh evaluation of the incumbent
Weaker purchase intent signals (score these lower):
- Content downloads about your category
- G2 profile browsing activity
- LinkedIn engagement with category content
Score range: 1–10. Weight heavily toward direct evidence signals (competitor trial, renewal window) over inferred signals.
Scoring Win Likelihood
Win likelihood is the hardest to calculate without historical outcome data but you can build a proxy:
- How long has the account been on their current vendor? (shorter = higher opportunity)
- Which competitor are they with / trialling? (vs. competitive record)
- Is there a visible trigger event? (new funding, leadership change, product incident)
- How many competitors are already in the evaluation? (more competition = lower win likelihood)
Score range: 1–10. This dimension should narrow your list, not expand it.
Putting the Tri-Score Into Practice: An Example
Imagine your weekly account prioritisation review. You have 80 ICP-fit accounts to evaluate. Here's how the Tri-Score narrows and prioritises:
Notice that Syncsole has the highest ICP fit score of the group and sits at the bottom of the priority list. It's a great potential customer. Just not right now.
Without the Tri-Score, your rep might spend their best outreach time on Syncsole because the firmographic fit is perfect. With it, they're spending that time on Acme Corp where a competitor trial has opened an active buying window.
Building the Tri-Score Into Your Weekly Workflow
The framework is only useful if it runs automatically, not as a manual exercise that gets skipped when the team is busy.
In practice, the Tri-Score workflow looks like this:
- ICP list is static: Updated quarterly based on your ICPs. These are the accounts your reps should ever be touching.
- Purchase intent signals are real-time: Competitor trial alerts, renewal windows, and usage signals surface daily. These update the intent dimension automatically.
- Win likelihood is semi-dynamic: Updated when competitive context changes (a new competitor enters the account, a key champion departs, a product incident occurs).
- A prioritised account list is generated weekly: The top 20–30 accounts by Tri-Score become the outreach focus. No other accounts get sequences that week.
The discipline this creates: Reps stop working from a static list of favourite accounts and start working from a dynamic, signal-driven priority stack that changes as the market changes.
The Accounts Worth Your Reps' Time This Week
The question your prioritisation framework should answer isn't "which accounts are a good fit?" It should be "which accounts are a good fit AND ready right now AND winnable?"
That intersection is smaller than your full ICP list. It's also far more valuable because every hour your rep spends on a Tri-Score account is an hour spent where the market is actually moving.
Every hour spent on an ICP-fit account without timing signals is an hour that might produce a good conversation and no deal because the prospect simply isn't in a buying window yet.
Stop Prioritising the Accounts That Look Right. Start Prioritising the Ones That Are Ready.
Your best customers looked exactly like your ICP before they bought. The ones that didn't close also looked exactly like your ICP. The difference was timing.
The Tri-Score doesn't find you better accounts. It finds you the right accounts at the right moment which is the only version of "better accounts" that closes. And you don't need to figure all of this out by yourself. That's why we built MarketSizer, where all of this intelligence is already baked in.
See your highest Tri-Score accounts right now. Start with 500 free Qualified Opportunities at marketsizer.io.
Frequently Asked Questions
How do you prioritise accounts for outreach?
The most effective account prioritisation combines three factors: ICP fit (firmographic and technographic match), purchase intent (direct signals like competitor trials and renewal windows), and win likelihood (probability of winning based on competitive context and timing). Prioritising only on ICP fit - the most common approach - ignores whether the account is actually in a position to buy right now.
What is account scoring in B2B sales?
Account scoring is the process of ranking target companies by their likelihood to buy. Most scoring models use firmographic criteria (industry, size, tech stack). More sophisticated models layer on timing signals like competitor trial activity, renewal windows, and churn signals, to distinguish accounts that fit your ICP from accounts that are actively in a buying motion.
What is the difference between ICP score and purchase intent?
ICP score tells you whether a company is a good potential customer based on their profile. Purchase intent tells you whether that company is currently in a buying motion. A high ICP score with no purchase intent signals means the company could be a great customer but not right now. The combination of both is what identifies a Qualified Opportunity worth prioritising.
How often should I update my account prioritisation list?
Purchase intent signals (competitor trials, renewal windows) should update your priority list in real time or daily. ICP scoring criteria should be reviewed quarterly. Win likelihood adjustments should be made when material competitive context changes, like a new champion, a competitor product release, or an account trigger event.
What tools help with account prioritisation?
CRM systems provide historical relationship context. Intent data platforms (6sense, Bombora) provide inferred interest signals. Subscription intelligence platforms like MarketSizer provide direct evidence signals, e.g. competitor trial detection, renewal windows, and switching patterns, that populate the purchase intent and win likelihood dimensions of account scoring.
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