Instead of guessing who to target, review your past positive interactions. Identify common characteristics among responsive and appreciative clients to build a data-informed profile of who you should be approaching next.
Related Insights
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.
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.
Rear-view attribution is flawed because markets, ICPs, and competitors constantly change. A more effective approach is to identify common traits among your best current customers and actively seek more prospects who fit that evolving profile.
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.
Many businesses fail by creating an offer and then searching for a customer. The correct sequence is to first deeply understand and select your ideal customer segment. Only then can you reverse-engineer an offer that resonates perfectly.
Don't just target the same job titles as your best customers. Dig deeper into the buyer's professional history (e.g., a COO with a 20-year sales background). This backstory is often the true indicator of an ideal fit, allowing for more precise and effective targeting.
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.
Instead of broad surveys, interview 10-12 satisfied customers who signed up in the last few months. Their fresh memory of the problem and evaluation phases provides the most accurate insights into why people truly buy your product, allowing you to find patterns and replicate success.
