GTM leaders no longer need to delegate strategy implementation. With tools like ChatGPT, their spoken words can become code, allowing them to rapidly prototype and test complex, data-driven prospecting campaigns themselves, directly connecting high-level strategy to on-the-ground execution.
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.
Horizontal SaaS companies fracture their customer knowledge across diverse industries, forcing generic messaging. Vertical SaaS companies build compounding knowledge with each customer within a niche. This leads to deeper insights, stronger competitive secrets, and more effective, specific messaging over time.
Traditional ICP scores reflect who *you* want to sell to (e.g., wallet size), which is useless for reps. Instead, sort your entire market based on the quantifiable size of their pain (e.g., projected fines). This gives reps a clear, actionable, and customer-centric reason for outreach.
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.
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.
Effective outreach uses public data to create a unique, valuable insight for the prospect (e.g., "Your building portfolio will face X dollars in fines by 2030 based on this new law"). This earns you the right to a conversation, where the pitch can happen later, rather than being ignored upfront.
