Lead Enrichment

Lead enrichment is the step between a raw prospect name and an outbound touch that has a real reason to exist. A raw lead is usually a name, a company, and an email guess. Enrichment turns that into a profile: company headcount, funding stage, tech stack, recent press, hiring signals, the founder last LinkedIn post, podcast appearances, product launches in the last 30 days. Without enrichment, the only thing an SDR can write is a template with a name token, which is why human SDR outbound averages a 1% reply rate. With enrichment, the first sentence references something the prospect did last week, which is why researched outbound averages 4% to 5%.

Enrichment splits into four layers. Firmographic data covers the company facts: headcount, revenue band, funding stage, vertical. Demographic data covers the person: role, tenure, prior companies, LinkedIn activity. Technographic data covers the stack: what tools they use, what they switched from, what their build versus buy posture is. Behavioral data covers real-time signals: hiring, funding events, job changes, content the prospect posted, conferences they attended. The fourth layer is where the differential reply rates come from, because firmographic and demographic data are commodity, while behavioral signals are the angle that earns the reply.

Inside the AI Sales Department, enrichment is the work the agent does before writing each email, and it is the work a human SDR cannot afford to do at 80 emails a day. An AI SDR running 500 touches a day spends agent minutes per prospect reading their feed, their funding history, their stack signals, their recent posts. The cost per minute of agent compute is near zero compared to human salary, which is why the volume math works. See also alternative to Clay for clients comparing this to tool-only enrichment workflows where humans still write every email at the end.