Every signal, scored and written back
RevSure extracts the predictions and signals that matter at every level of the funnel, from the lead to the buying group, lands them on the resolved record, writes them back to your live tools, and exposes them to any agent through MCP.
Predictive lead scoring ranks leads and accounts by how likely they are to convert, using machine learning over your funnel data. RevSure extracts predictions and signals at every level, from the individual lead to the buying group, lands them on the resolved record on its context layer, writes them back to your live tools, and exposes them to any agent through MCP, so the whole stack acts on the same scores.
A signal at every level of the funnel
| Level | Signal | Value |
|---|---|---|
| Account | Propensity | 0.82 · high |
| Opportunity | Deal health | At risk |
| Buying group | Coverage | 4 of 6 mapped |
| Meeting | Sentiment | Positive · pricing |
| Upsell | Expansion fit | Strong |
RevSure reads the resolved record and extracts the signals that matter at each grain: the lead, the opportunity, the account, the campaign, the meeting, the expansion motion, and the buying group behind them. Every signal carries its source and its confidence.
- Lead: fit, intent, engagement, and routing priority
- Opportunity: deal health, stage-conversion likelihood, and risk flags
- Account: propensity to buy, whitespace, and expansion fit
- Campaign: influence, incrementality, and attributed pipeline
- Meeting: sentiment, topics, and competitor mentions from every call
- Upsell: usage and product-fit signals that flag the expansion
- Buying group: committee mapping, roles, and engagement coverage
Forward-looking, not a rear-view report
The same learning engine that scores the record projects it forward: how likely this converts, what pipeline lands, which accounts are surging, and the next best action to move each one. One model over the whole graph, not six disconnected reports.
- Propensity and conversion likelihood at lead, account, and opportunity
- Pipeline predictions and coverage against the number
- Churn and expansion signals on the installed base
- Next best action, ranked and explained per record
Part of the context layer, so every tool and agent reads them
| Surface | Reads | Cadence |
|---|---|---|
| Salesforce | Scores + signals | Scheduled |
| MAP | Propensity | Scheduled |
| MCP · Claude | Any field | On request |
| Slack | Next best action | Real time |
Predictions and signals are not trapped in a RevSure dashboard. They land on the resolved golden record, write back to your CRM and MAP, and are exposed through the MCP Server, so your reps, your workflows, and any external agent act on the same scored truth.
- Land on the resolved record, next to the fields that drove them
- Write back to Salesforce, HubSpot, and your MAP on a schedule
- Exposed via MCP to Claude, ChatGPT, or your own agents
- Every score explainable and reversible, never a black box
Scored on the graph, explained on the record
Related capabilities
Questions, answered
What is predictive lead scoring?
Predictive lead scoring uses machine learning over historical funnel data to rank leads and accounts by conversion likelihood, so teams focus on the ones most likely to buy. It replaces static, points-based rules with models that learn from real outcomes.
What signals does RevSure score?
Signals at every level of the funnel, from an individual lead's behavior to buying-group and account-level intent. They land on the resolved record and are written back to your CRM and ad platforms so teams act on them where they work.
Can other tools use these scores?
Yes. RevSure writes scores back to your live tools and exposes them to any agent through the MCP server, so the same predictions drive routing, activation, and agent actions across the stack.
Score it once. Act on it everywhere
See the signals and predictions RevSure writes back to your stack.