What are buying signals?

A buying signal is any observable event or behavior that raises the odds that a person or account will buy soon. The useful ones do two jobs at once: they tell you the timing is good ("why now") and they often give you a reason to reach out ("congrats on the new role"). That combination is what makes a signal more than a data point — it's a conversation starter with built-in relevance.

Signals exist at two levels. Account-level signals (a funding round, a hiring spree, a surge in research on your category) tell you which companies are in-market. Person-level signals (a promotion, a job change, a demo request) tell you who to talk to and why. The best plays stack them.

It helps to group them. Fit signals tell you an account matches your ICP (industry, size, tech stack). Intent signals show active research — first-party (visits to your pricing page, free-tier usage) or third-party (topic research across the web). Engagement signals are interactions with you (email replies, event attendance, repeat visits). Timing signals are events that open a window — funding, job changes, new hires, reorgs, contract renewals.

A second cut is by source. First-party signals come from your own systems (website, product, CRM) and are high-trust but limited to people already in your orbit. Third-party signals are bought from data vendors and widen your view to accounts that have never touched you — at the cost of being noisier. Mature teams blend both.

Digital and account-level examples include: a champion changing jobs, a company raising funding, a target account hiring for roles your product supports, a technology being installed or removed, a free-tier user hitting an activation milestone, and a spike in third-party intent for your category.

In a live conversation, buying signals are verbal and non-verbal cues. Verbal signals include questions about price, implementation, timelines, or contracts ("how long does onboarding take?"), and shifting from "if" to "when." Non-verbal signals include looping in additional stakeholders, fast responses, and asking for a trial or a proposal. Both senses matter — the digital signals tell you when to start a conversation; the conversational ones tell you it's time to advance the deal.

Not every signal is green. Negative buying signals indicate falling intent or rising risk: a prospect goes quiet after being engaged, repeatedly reschedules, pushes the timeline out indefinitely, or raises the same objection without resolution. On existing accounts, a champion leaving the company is a classic negative signal — and an early churn warning.

Reading negative signals well is as valuable as chasing positive ones. It tells reps when to disqualify and reallocate effort, and it tells customer teams when to intervene before a renewal is at risk.

Three rules: be fast, be relevant, and prioritize. Speed matters because signal value decays — a funding round is freshest in the first 30–60 days, and a job change in the first weeks. Relevance means leading with the signal, not burying it under a generic pitch. Prioritization means scoring signals by ICP fit and strength so reps spend time on the few that predict a purchase, not the many that don't.

The operational challenge is doing all three consistently across hundreds of accounts. That requires detecting signals automatically, enriching them with research, and turning each into a ready-to-send play — which is the gap automation fills.

Komo monitors buying signals across your accounts, and when one fires it researches the account and contact and drafts the outreach and follow-up — so the signal becomes a relevant, ready message instead of a row in a dashboard you'll act on later (or never).

Because the repetitive detection-research-draft loop is automated but you stay on every send that matters, you get the speed and coverage that make signals valuable without sacrificing the quality that makes them convert.