Clearbit's journey in refining its lead qualification process reflects its growth from a small startup to a mid-sized company with diverse products and strategies. Initially, lead qualification relied on manual efforts by a small sales team, but as the company expanded to include over 50 sales and 25 customer success team members, it evolved into a sophisticated system emphasizing predictive scoring and specialized tools. The lead scoring process has transitioned from simple binary assessments to advanced predictive models using machine learning, incorporating firmographic, demographic, and behavioral data to prioritize leads. This evolution is supported by a robust tech stack that includes tools like Salesforce and LeanData for lead routing, as well as marketing technologies that track and analyze customer data. Clearbit's Ideal Customer Profile (ICP) has also shifted, moving from a focus on leads likely to close to those with higher lifetime value, driven by insights such as the correlation between a company's web traffic and its potential value to Clearbit. This ongoing adaptation in lead qualification is a testament to Clearbit's commitment to aligning its resources and strategies with its growing and changing market presence.