Lead Scoring

What is lead scoring?

Lead scoring is the practice of attaching a number to every lead that summarizes how worth pursuing they are. Two main inputs: fit (do they match ICP — industry, size, role, geography?) and intent (have they shown buying signals — visited pricing, downloaded ToFu, spiked in third-party intent data?). Output is usually a 0–100 score or letter grade (A/B/C/D), with thresholds that gate automation.

In 2026 most modern scoring is AI-assisted — an LLM reads unstructured signals (a LinkedIn post, a job description, a website) and contributes to the score with explainable rationale.

Why it matters

• Reps spend time on the right leads, not whoever's on top of the queue
• Scoring is the contract between marketing and sales (above X = SQL handoff)
• Surfaces the patterns that predict conversion — feeds back into ICP refinement

Score components

• Demographic / firmographic: title, seniority, company size, industry
• Behavioral: site visits, email engagement, content downloads, demo requests
• Intent: third-party signals, hiring activity, tech-stack changes
• Negative scoring: competitor employees, free-mail addresses, role accounts

How TexAu helps

AI Column lets you define a scoring rubric (fit + intent dimensions, weights, thresholds) and apply it to every lead in a table — with a one-line rationale per score so reps trust it and ops can iterate the model.