What is Sales Signals?

The shift from volume-based to signal-based selling represents one of the biggest changes in B2B sales methodology in the past decade. According to McKinsey, B2B companies that use advanced analytics and signals in their sales process grow revenue 2-3x faster than competitors.

Sales signals solve the fundamental prioritization problem: with thousands of potential accounts, which ones deserve attention today? Without signals, reps default to arbitrary criteria — company size, industry, or whoever is next on the list. With signals, they focus on accounts where something meaningful just happened.

The volume of available signals has exploded. SEC filings, job postings, technology adoption data, social media activity, patent filings, press releases, and review site behavior all generate signals that were invisible to sales teams five years ago. The challenge has shifted from "we don't have enough data" to "how do we filter the noise and surface what matters." Teams that solve this filtering problem consistently outperform their peers.

Sales signals are collected, processed, and delivered through a multi-stage pipeline.

**Collection:** Signals originate from structured sources (SEC EDGAR filings, job board APIs, CRM data) and unstructured sources (news articles, social media posts, earnings call transcripts). Web scraping, API integrations, and NLP extraction are the primary collection methods.

**Processing:** Raw signals go through entity resolution (matching a signal to a specific company), deduplication (merging the same event from multiple sources), enrichment (adding firmographic context like company size and industry), and classification (categorizing the signal type — e.g., "hiring," "funding," "technology change").

**Scoring:** Each signal receives a relevance score based on recency, source reliability, and alignment with the sales team's ICP. A fresh funding round at a target-segment company scores higher than a two-month-old press release from a non-ICP account.

**Delivery:** Processed signals are pushed to reps through CRM integrations, email digests, Slack notifications, or embedded in outbound tools. The best delivery mechanisms include suggested messaging that references the signal, reducing the cognitive load on reps.

The entire pipeline — from event occurrence to rep notification — should complete within hours, not days. Signal freshness degrades rapidly: a signal that is 48 hours old is worth roughly half as much as one that is 2 hours old.

Autobound's Signal Engine monitors 26 distinct signal types across 400+ individual signals, covering everything from SEC filings and earnings transcripts to GitHub activity, G2 reviews, and ad spend changes. Signals are processed through entity resolution and scored by Autobound's AI for relevance to each customer's ICP. The platform delivers not just the raw signal but AI-generated outreach copy that references the specific event, so reps can act within minutes. The Generate Insights API makes these signals available programmatically for platforms that want to embed signal intelligence into their own products.