The best initial segment to target isn't always the biggest. It's the one with the richest, most structured public data available. This data allows you to create a "demonstrable" value proposition, connecting a specific pain point to your solution with near-perfect information before you send a message.
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Don't start with messaging. Build a hyper-specific list based on observable public data that signals a clear pain point. This data-driven list itself becomes the core of a highly relevant message, moving beyond generic persona-based outreach and hollow personalization.
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.
For consumption-based models, simple size-based segmentation (SMB, Enterprise) is insufficient. Stripe and Vercel use a two-axis model: company size (x-axis) and growth potential (y-axis). A small company growing at 200% YoY is more valuable and warrants more sales investment than a large, stagnant one.
The conversation around Ideal Customer Profile (ICP) has evolved beyond simple refinement. With newly accessible data, companies are fundamentally re-evaluating their Total Addressable Market (TAM), challenging long-held assumptions about who their potential customers are and how big the opportunity is.
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.
The process of defining a GTM strategy isn't just about choosing which segments to target; it's equally about deciding which ones to ignore. Failing to actively say "no" creates fuzziness, dilutes resources, and leads to misaligned sales and marketing efforts downstream.
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.
Instead of theorizing about their Ideal Customer Profile, Assembled's first GTM hire created a list of all existing customers. By looking for patterns and creating groups based on traits like tech stack (Zendesk), agent count (20-200), and channel complexity, a data-driven, highly specific ICP emerged organically.
