Salesforce lead scoring is a system that ranks prospects by assigning points based on explicit data (such as job title) and implicit data (like website interactions) to identify which leads are likely to become customers, allowing sales teams to focus their efforts efficiently. This approach not only prioritizes leads but also aligns sales and marketing teams by establishing a shared understanding of lead quality, enhancing productivity by up to 32% using AI-driven tools. Effective lead scoring requires combining explicit and implicit data, maintaining data hygiene, and using custom fields to capture unique success indicators. Advanced tactics such as score degradation, negative scoring, and data enrichment further refine the process, ensuring the model remains dynamic and accurate. Employing Salesforce tools like Sales Cloud Formula Fields, Marketing Cloud Account Engagement, and Einstein Lead Scoring, organizations can tailor their scoring methods to suit their needs, whether they are just starting or have substantial historical data. Automation through Salesforce Flow is crucial for converting high scores into actionable sales activities, ultimately improving conversion rates, reducing sales cycles, and increasing revenue impact. Continuous optimization, supported by sales feedback and enriched data, transforms lead scoring into a powerful engine for generating meaningful sales conversations.