What Is Lead Scoring?

Lead scoring assigns numerical values to leads based on how well they match the ideal customer profile and how engaged they are with the brand. This scoring helps sales teams prioritize their outreach, focusing time and effort on leads most likely to convert.

Lead scoring models typically consider two categories of signals: fit-based signals (how well the lead matches the ICP based on firmographic data like company size, industry, and role) and behavior-based signals (engagement indicators like website visits, email opens, content downloads, and demo requests).

Enriched data dramatically improves lead scoring accuracy. Without enrichment, scoring models rely on limited form-fill data. With enrichment, models can incorporate company revenue, employee count, technology stack, and other firmographic data that strongly correlate with purchase likelihood.

AI-powered enrichment platforms like Enrichabl enable more sophisticated lead scoring by appending data points that traditional forms cannot capture. Custom AI enrichment columns can research prospects' recent news, funding status, technology usage, and hiring patterns - all valuable signals for lead qualification.