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When selling to what you believe is a single ICP, but some buyers have intense 5/5 "Pull" and others have a mild 2/5, your ICP definition is flawed. The difference in their behavior is the key signal. You must diagnose the non-obvious differences between these groups to define your true, high-intensity ICP.
An Ideal Client Profile (ICP) is insufficient. Adopt a Perfectly Profitable Prospect Profile (P3P) to filter for alignment on core values, culture (e.g., agile vs. structured), and delivery fit (are they ready for your solution?). This proactively avoids friction and ensures engagement with high-value, low-headache clients.
Company-level Ideal Customer Profiles (ICPs) are standard, but top reps should define their own personal ICP. This helps them filter prospects and avoid closing deals that, despite high commissions, will inevitably lead to churn, support issues, and reputational damage down the line.
To define Ideal Customer Profiles (ICPs), go beyond analyzing past data. Use the Analytic Hierarchy Process (AHP), a statistical method where the executive team weights criteria and scores potential markets. This forces a rigorous, data-driven prioritization of the most promising customer segments.
Founders often believe their ICP is a theoretical construct for their website and pitch decks. In reality, a company's true ICP is determined by the customers the sales team is actively pursuing and successfully closing, which can reveal a critical disconnect from the intended strategy.
A traditional ICP mixes high- and low-intent buyers, yielding mediocre 20-30% close rates. An ICP based on "pull" focuses exclusively on the specific situations that create urgent, blocked demand. This forces hyper-specificity and builds a more efficient GTM motion by targeting a cohort with a near-100% close rate.
Stop defining your Ideal Customer Profile with abstract firmographics. Instead, feed context from your best closed-won deals into an AI and ask it to find public data that signaled their specific pain *before* they engaged you. This reverse-engineers a truly effective, data-driven targeting model.
Executive teams often create an ICP based on a 'wishlist' of big logos. The most accurate ICP is actually found by analyzing your first-party CRM data. Examining patterns across both close-won and close-lost deals reveals surprising truths about which customer segments are actually the best fit for your solution.
Ditch the aspirational "Ideal Client Profile," which represents a rare, perfect-world scenario. Instead, build a "Target Client Profile" that defines which customers will perceive the most meaningful value from your offering. This provides a realistic, operational benchmark for qualifying leads.
Defining an ICP based on who you *want* to sell to is flawed. A "Pull"-based ICP is defined reactively: it's the specific group of people currently experiencing such an urgent, blocked project that it would be illogical for them *not* to buy your solution right now.
Instead of a generic persona, define your target customer with a 'pull hypothesis': who would be *weird not to buy*? This structured framework forces you to articulate the specific project they're trying to accomplish, why their current options are bad, and why your solution becomes irresistible. It focuses on their demand, not your product's features.