enrich every lead for smarter scoring.
Feed real firmographic and demographic data into your scoring models. Know the company size, industry, seniority level, and tech stack before you assign a score.
get started freethe problem
Most lead scoring models rely on form fills and page views — behavioral signals that tell you what a lead did, not who they are. Without firmographic data, your model scores a startup intern the same as an enterprise VP. You end up routing low-quality leads to sales, wasting rep time on prospects that were never going to close, and letting real decision-makers slip through because your model had nothing meaningful to work with.
how it works
enrich lead data
Pass a lead's email address and get back the firmographic and demographic signals your scoring model needs. Name, title, company size, industry — all in one call.
extract scoring signals
Pipe the enriched output through jq or any JSON tool to extract exactly the fields your scoring model needs. Seniority, company size, industry — structured and ready.
score your pipeline
Enrich an entire CSV of leads in one command. Get structured output ready to feed into your scoring model, routing rules, or CRM import.
why teams use enrichcli for lead scoring
firmographic scoring signals
Company size, industry, revenue, tech stack. Score leads based on who they are, not just what they clicked. Real data means your model can distinguish enterprise prospects from early-stage startups.
demographic precision
Job title, seniority level, department. Distinguish decision-makers from researchers automatically. Your scoring model gets the context it needs to prioritize the leads that actually close.
automate the pipeline
Enrich in bulk, pipe to your scoring model, and route leads — all from a single command chain. No manual CSV wrangling, no GUI exports. Build it into a cron job and forget about it.
start scoring leads with real data.
get started free50 free enrichments per day. no credit card required.