Lead scoring is an important tool for sales and marketing teams, allowing them to focus on the most engaged users and convert them at a higher rate. It works by using rules to "qualify" each lead in the pipeline, assigning it a new priority based on its historical conversion rates. To get started with lead scoring, a basic system requires a data stack, including collection, storage, modeling, and activation tools. The quality of the data is crucial, as garbage-in-garbage-out applies, and ensuring that data is stored in a standardized way, regularly snapshotted, and uniquely matched to conversions can make a significant difference. Lead scoring models can be used for marketing email automation and product qualified leads (PQLs), which convert at a higher rate and are less likely to churn once they become customers. Effective lead scoring systems require an operational analytics stack, including data collection, storage, modeling, and sharing tools. By prioritizing the right leads and automating engagement, sales teams can save valuable time and improve conversion rates.