An intent signal is a behavioral clue showing that a prospect is actively researching a problem your product solves. Instead of reaching out to everyone who fits your target profile, intent signals help you focus on accounts already in motion — people visiting competitor pages, hiring for roles your tool supports, or engaging with relevant content. The shift is from "does this person match my ICP?" to "does this person match my ICP and is actively looking right now?" Learn how signals fit into a broader B2B prospecting strategy.

Lead scoring assigns a static number based on fit criteria — job title, company size, industry — to rank how well a lead matches your ICP. Intent signals measure real-time behavior — what a prospect is doing right now that suggests buying interest. The key difference: a lead score tells you who could be a good customer; an intent signal tells you when they're ready to hear from you. The best outbound strategies combine both: use your ICP and lead management criteria to filter, then use intent signals to prioritize and time your outreach.

Intent signals work by continuously monitoring prospect activity across multiple data sources and flagging patterns that indicate buying interest. Topo's AI sales agent scans these sources automatically and triggers outreach when signals fire. The process follows three steps:

• Collection — the agent monitors web activity, social engagement, hiring posts, tech stack changes, and CRM history in real time
• Scoring — signals are weighted by relevance and recency to surface the highest-priority accounts
• Action — when a signal crosses your threshold, the agent initiates a personalized outreach sequence

This happens continuously, so you never miss a timing window.

The biggest impact comes from using signals to decide when and how to reach out — not just who. A prospect who just followed your competitor on LinkedIn gets a different message than one who posted a job listing matching your use case. Best practices:

• Layer signals on top of ICP — filter by fit first, then prioritize by intent
• Personalize based on the signal itself — reference the trigger event in your outreach to show relevance
• Act fast — intent signals decay quickly; reaching out within 24–48 hours dramatically improves reply rates

This approach is what makes signal-based sales outperform volume-based outbound.

Topo tracks six categories of intent signals, each surfacing a different type of buying behavior:

• Competition — prospects following, engaging with, or evaluating your competitors
• Social — event participation, influencer interactions, relevant content engagement on LinkedIn
• Hiring — job postings or new hires in roles your product supports
• Technology — adoption of compatible tools or signs they're switching from a competitor's stack
• CRM — reactivated deals, content downloads, or re-engagement from past contacts
• Custom — any signal you define based on your market, tracked by Topo's AI research agent

All signals are sourced from Topo's own data sources, so you don't need separate subscriptions.

Yes. Beyond the six built-in signal categories, Topo lets you define custom intent signals tailored to your market. You describe the behavioral pattern you're looking for — for example, "companies posting about GDPR compliance challenges" or "SaaS startups that just closed a Series A" — and Topo's AI research agent actively scans for matches. Custom signals are tracked the same way as standard ones: they feed into the AI sales agent, which prioritizes and triggers outreach automatically. This means your prospecting adapts to your niche without manual monitoring.