Pipeline intelligence that reads signal, not self-report.
Deep inside your CRM data is a pattern of deal health that reps can't see and spreadsheets can't surface. Quotavue finds it.
The eight deal signals we track
Every signal is derived from CRM activity data, not rep input. We surface patterns reps can't see.
Detects when meeting cadence or email replies fall below the deal's own baseline pace.
Flags deals that have spent more time in a stage than comparable won deals in your pipeline history.
Identifies when champion contacts stop engaging, signaling political risk or lost internal sponsor.
When competitor names start appearing frequently in activity logs and notes, the buyer is actively evaluating alternatives. The spike is a risk signal, not a coincidence.
A champion moving up in decision-making authority is a positive signal. A champion who stops copying the VP on emails, or who gets replaced as primary contact, is a warning. We track the trajectory, not just the current state.
Counts how many times the close date has moved and how recently, weighting recent slips more heavily.
Measures how many unique stakeholders from the buying org are active in the deal, not just aware of it.
A $200K deal that has generated 2 meetings and 8 emails in 60 days is under-resourced. A $40K deal with 30 touchpoints is likely stalling on price. Both patterns predict outcome in our model.
Forecast engine: how we call the number
Each deal receives a signal-derived probability score. We bucket your pipeline into three tiers: Commit (80+), Likely (50-79), and Pipeline (below 50). The weighted sum across tiers produces a single defensible number with an explicit confidence band.
This is different from what Salesforce or HubSpot give you natively. Their forecast is built from what your reps choose to enter in the forecast category field: commit, best case, pipeline. Our probability is derived from how the deal is actually behaving: stage velocity, engagement patterns, stakeholder activity, close-date history. The rep's manual forecast category is not an input to our model at all.
When a signal combination in our training data consistently predicts a loss, the score drops, regardless of whether the rep marked it "commit."
Deep CRM integration, not a surface sync
Most CRM integrations sync the current state of a deal. We read the history: every stage transition, every timestamp gap, every contact who stopped responding. A deal stuck in "Negotiation" for 45 days looks different from one that moved there three days ago, and our model treats them differently.
Read-only OAuth connection. No ETL project. No IT ticket. We do not write to opportunity stage, amount, or close date fields. The RevOps plan includes optional write-back to custom score fields only.