Executive Summary

Sales and SDR teams at roughly 3,000,000 organizations waste significant effort on low-probability outbound outreach, with average conversion rates often below 5% and high SDR churn that drives rising cost-per-opportunity. The core problem is noisy, fragmented signals—website visits, product usage indicators, hiring events, traffic spikes—none of which, on their own, reliably predict buying intent; buyers and GTM leaders need a way to prioritize outreach so limited reps focus on the small fraction of accounts that will convert. You could build a SaaS intent-scoring platform that ingests and normalizes multi-source feeds, applies embeddings and LLM-based inference to create a calibrated intent score and confidence band per lead, and pushes explainable signals and recommended next actions into CRMs and sequence tools. Targeting a $6,000 ACV mid-market plan (consistent with the $18.0B market size), the product would include fast onboarding for common feeds, model tuning by outcome, and a simple ROI dashboard that ties scores to conversion lift and cost-per-opportunity improvements. This market is attractive now because three forces are converging: AI-enabled intent inference makes multi-signal fusion practical; commoditized signal feeds lower data acquisition costs; and GTM teams are explicitly shifting to quality-over-volume outreach to combat rising outbound costs. With an addressable market of roughly $18B and many teams already experimenting with intent, adoption can be quick, but winning requires demonstrating measurable conversion improvement within 30–90 days. To stand out you must deliver reliable, auditable predictions rather than opaque scores—surface the contributing signals, show historical lift for each customer, and make integration low-friction so adoption barriers remain small. Challenges are real: signal noisiness, privacy/regulatory constraints, and a crowded competitive field that can copy raw features quickly; the defensibility will come from proprietary model fine-tuning to customer outcomes, closed-loop learning, and enterprise-grade data hygiene and explainability.

Market Opportunity

Qualify SaaS leads before outreach using multi-signal intent scoring targets a $18.0B = 3,000,000 sales & SDR orgs x $6,000 ACV total addressable market with medium saturation and a year-over-year growth rate of 15-25% (sales engagement & intent data growth).

Key trends driving demand: AI-enabled intent inference -- LLMs and embeddings let you infer intent from noisy, multi-source signals.; Signal commoditization -- many raw data feeds exist (job boards, product trackers, traffic APIs) enabling rapid feature assembly.; Shift to quality over volume -- teams prioritize conversion rates as outbound costs and SDR burnout rise.; Privacy-first analytics -- regulation & cookie deprecation push vendors toward aggregated/public signals and event-based models..

Key competitors include 6sense, Bombora (Company Surge), ZoomInfo (including Intent / Scoops), Apollo.io, LinkedIn Sales Navigator (adjacent workaround).

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Qualify SaaS leads before outreach using multi-signal intent scoring

Executive Summary

Market Validation

Market Opportunity

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