Run the motion the signal asks for
Every buyer leaves evidence. In a call, a Slack thread, an open objection, a job change, a funding round. RevSure captures the signal, resolves it onto the context layer, and fires the marketing, prospecting, sales or customer success motion it calls for.
Positive across meetings, driven by strong champion engagement and fast pilot progress.
Active pilot moving toward enablement, with next steps already scheduled.
Economic buyer has not joined a call, and procurement stakeholders are still unnamed.
Signal-based selling means running marketing, prospecting, sales and customer success off observed buyer behaviour instead of static lists and calendar cadences. A signal is any evidence of buyer state: a sudden engagement spike, a champion changing jobs, an objection raised on a call, a feature request in Slack. RevSure captures signals from inside your stack and from the open web, resolves each one onto the same identity on the context layer, and hands it to a playbook that knows which motion it belongs to. Every resulting move is proposed, approved, committed and reversible.
Audiences that rebuild themselves
| Signal | Reads as |
|---|---|
| Account state | Advancing or stalling on the journey |
| Campaign responsiveness | Which channels this account answers |
| ICP fit | Match to ideal customer profile |
| High-intent activities | Active buying research, not browsing |
| Product signals | Product-page and feature engagement |
A list built on firmographics goes stale the week after you export it. Signal-based marketing replaces the export with a standing definition, then lets account state, ICP fit, high-intent activity and campaign responsiveness decide who is in it today. The same signals run the other direction — deep funnel conversion events write back to Google, Meta and LinkedIn so bidding optimises against pipeline rather than form fills.
- Stage-aware nurture: content follows the account from Awareness to Decision, and reacts when it stalls or regresses
- Anonymous demand made addressable: deanonymized visitors enter ABM audiences before they ever fill a form
- Spend judged on causality: incrementality and mix modelling separate campaigns that created demand from ones that rode it
- Microsegments by propensity: conversion likelihood splits a broad audience into segments worth different budgets
Reach out the day something changed
| Signal | Reads as |
|---|---|
| Job change signals | Promotions and moves across champions |
| Leadership change | A new decision-maker in the seat |
| High-intent activities | Leads researching right now |
| Engagement velocity | How fast interest is building |
| Buyer group engagement | Roles still untouched |
Outbound fails on timing far more often than on messaging. Signal-based prospecting watches a named set of leads and accounts continuously and surfaces the moment worth a message — a champion lands somewhere new, a team starts hiring for the problem you solve, engagement velocity jumps. Because the signal carries its own context, the outreach can too.
- Warm paths from cold lists: a champion who moves takes a working relationship to a net-new account
- Net-new engagers surfaced: organic LinkedIn activity exposes people who never touched your site
- Prioritisation with a reason: every lead arrives with the signal that raised it, not just a score
- Routed automatically: signals filter to the right rep or agent and write contact data back to the CRM
Deal health you did not have to ask for
| Signal | Reads as |
|---|---|
| Overall sentiment | How the conversation is trending |
| Top objections | What keeps coming up unresolved |
| Buyer group engagement | Role activity and missing DMs |
| Account state | Advancing, stalled or regressing |
| Job change signals | Champion leaving or ally arriving |
A CRM stage is a claim made by a rep at a point in time. Signal-based sales reads how sentiment moved across the last three calls, whether the economic buyer has ever engaged, which objections resurfaced, and whether the account advanced or quietly stalled — modelled weekly so risk shows up before the close date does the telling.
- Conversations summarised into state: sentiment, momentum, qualification, pain points and product interest
- Multi-threading made visible: champion, technical buyer, economic buyer and influencer scored by role
- Stalls detected as they happen: advancing, stalled and regressing accounts separated week by week
- The next step, with its reason: playbooks return the motion, messaging and specific action
Renewal risk and expansion, caught early
| Signal | Reads as |
|---|---|
| Chat signals | Sentiment, topics, feature requests |
| Upsell signals | Seat growth and cross-dept pull |
| Overall sentiment | Direction across recent conversations |
| Job change signals | Champion departures and landings |
Churn is rarely a surprise to the data — it is a surprise to the calendar. Signal-based customer success reads the same conversation and engagement layer the sales motion uses, and keeps reading it after the close. When a call or chat mentions seat growth, a new product or another department, that becomes an upsell signal attached to the account.
- Upsell detected in the conversation: seat growth, new product interest and cross-department expansion
- Product feedback becomes a signal: feature requests, questions and objections map to lead and account
- Champion departure caught in days: a job change is a retention risk here and a warm opening there
Every signal, on its own
Internal context from your GTM stack, blended with external web signals for target leads and accounts. Meeting and conversational signals come from note takers, Slack and email. Engagement signals are derived from the unified context layer. Other signals add buying intent and account activity from real-time web monitoring. Every signal maps to a lead, account or opportunity so agents can trigger outreach, CRM writebacks, alerts and workflows in real time.
Overall Sentiment
Reads how a conversation is trending call over call, from note takers, Slack and email, so shifts in tone surface before they show up in the pipeline.
Account State
Places the account in its buying journey and tracks whether it's advancing, stalled or regressing, updated as new conversations come in.
Intent Level
Scores how strongly a conversation signals active buying intent, separating real urgency from polite interest.
Top Pain Points
Surfaces the problems a buyer raises most often across calls and chats, ranked by how frequently they come up.
Stakeholder Coverage
Shows which roles at the account have actually been reached in conversation, and which are still missing.
Open Gaps
Flags unresolved questions or missing information from conversations before they stall a deal.
Product Interest
Tracks the features and use cases a buyer asks about or reacts to across every conversation.
Top Objections
Surfaces the objections that come up most and haven't been resolved, so reps walk in prepared.
Upsell Signals
Catches seat growth, new product interest or cross-department mentions the moment they're said out loud.
Chat Signals
Extracts sentiment, topics, questions and feature requests from Slack and other chat sources, without anyone reviewing every thread.
High-Intent Activities
Flags behaviour that indicates active, in-market research, separating real buying signals from passive browsing.
Engagement Velocity
Measures how quickly interest is building across an account's touchpoints, so momentum shows up before a rep asks.
Campaign Responsiveness
Tracks which channels and campaigns an account actually answers, not just which ones it was sent.
Recency of Last Touch
Tracks how long it's been since the account last engaged, so quiet accounts surface before they go cold.
Multithreading
Counts how many people at the account are actually engaging, not just the one contact who replies.
Product Signals
Reads engagement with product pages, features and usage touchpoints as part of the same account picture.
Buyer Group Engagement
Scores role-level engagement across Champions, Technical Buyers, Economic Buyers and Influencers, so gaps in the buying group are visible early.
Funding
Detects funding rounds on the open web and attaches them to the account they concern.
ICP Fit
Checks whether an account matches your ideal customer profile, refreshed as firmographic details change.
Leadership Change
Flags new leadership at an account, detected from public sources, before it shows up anywhere else.
Product Launches
Tracks new product or feature announcements from an account's company as a read on their priorities.
Financials
Surfaces public financial events or disclosures relevant to an account.
Hiring
Reads job posting volume and role mix as evidence of team build-out and where budget is heading.
Job Change Signals
Tracks promotions and company moves across tracked contacts, preserves relationship history, and writes the update back to the CRM.
Related capabilities
Predictions & Signals
The models that score every resolved record.
ExploreReal-Time Orchestration
Signals trigger action in seconds, not the nightly batch.
ExploreWritebacks & Activation
Scores and stages committed back into your live tools.
ExploreAgent Builder
Compose the agent that acts on a signal you care about.
ExploreQuestions, answered
What is signal-based selling?
Signal-based selling means running marketing, prospecting, sales and customer success off observed buyer behaviour instead of static lists and calendar cadences. A signal is any evidence of buyer state: a sudden engagement spike, a champion changing jobs, an objection raised on a call, a feature request in Slack. RevSure resolves every signal type onto one context layer, scores it, and fires the motion it calls for.
How does RevSure calculate account state?
RevSure aggregates engagement, campaign, pipeline, conversion and account activity for each account every week, then models where it sits between Awareness and Decision. The output carries the current state, a confidence score, and a transition history showing whether the account is advancing, stalled or moving backward.
How do signals turn into action?
Playbooks match each resolved signal to a motion using your ICP criteria, segments, triggers and rules, then return the reason, the sales motion, the messaging and the specific next step. Agents commit it through CRM, ad-platform writebacks, audience syncs, Slack or MCP-connected assistants, behind the approval gate you set and reversible in one click.
Do signals write back into the CRM?
Yes. Scores, account state, resolved identities, job change updates and attribution outputs write back to Salesforce and other connected systems through the governed writeback path, and can also be pushed to ad platforms, marketing automation, email tools and the warehouse.
Stop reporting the signal. Act on it
See what RevSure picks up on your own stack, and which motion it would have fired.