PartnerSignals finds it, measures it, and helps you drive more of it on purpose — converging four partner-ecosystem signal streams your CRM can't see, months before your CRM does.
Three scenarios most enterprise revenue leaders recognize before they recognize the category.
Your largest deal of the quarter just slipped commit. Three weeks ago, the technology partner shifted their architecture recommendation away from your platform. That signal lived in a partner call no one logged. The revenue was recoverable — if the signal had surfaced in time.
Your VP of Alliances reports 40% of pipeline is partner-influenced. Your CRO repeats the number on the QBR. The board asks how it's measured. The honest answer is “rep narrative.”
Partner-influenced deals miss commit more often than direct deals — but they're governed by the same stage gates, the same forecast call, and the same QBR inspection. The variance keeps showing up; the operating model doesn't change.
PartnerSignals™ connects to the tools your team already uses — and surfaces partner signals directly inside them.
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Partner-influenced revenue is happening. It just doesn't show up in your CRM until the window has closed — the co-sell window opened and closed before anyone could act on it.
The signals that drive partner-influenced deals operate in four places your CRM doesn't capture: conversation intelligence from partner calls, partner motion signals from your ecosystem activity, intent signals from technology stack changes and organizational shifts, and financial signals from funding events and budget timing.
Two of those signal streams tell you what's happening now. Two more tell you what's coming — months before it shows up in your CRM. Without convergence across all four, you're forecasting from the inside of the window.
That gap is the Forecast Delta — and today it's invisible.
What's being said on co-sell calls. Which partners are pushing. Which went quiet at Stage 3.
Deal registration activity, co-sell engagement cadence, activation patterns across your ecosystem.
Market and technology signals that predict partner-relevant buying intent months before a deal exists: technology stack changes, organizational signals, content engagement patterns.
Financial indicators and investment signals that surface acquisition activity before your CRM sees it: funding events, budget cycle signals, technology investment patterns.
When multiple streams converge on the same account, forecast confidence compounds. One source is guesswork. Four converging sources is a defensible case.
The Signal Convergence architecture cross-corroborates all four streams. Where they disagree — that becomes the signal. We call it the Forecast Delta.
Four steps. Built into the workflows your revenue team already runs.
Every partner call, co-sell conversation, and ecosystem activity stream is ingested — without manual logging or new workflows for your reps.
Each signal is tagged for partner influence, buyer intent, and deal risk — then checked against your partner motion data and pre-intent signals.
All four signal streams converge across one model. Where they disagree, that becomes the Forecast Delta.
The signal-adjusted forecast shows up inside your CRM workflow — pipeline upside, at-risk deals, and Forecast Delta, alongside CRM stage probability.
Your forecast is only as good as your signal sources. One source is guesswork. Four converging sources is a defensible case.
Most signal tools capture one surface — conversation intel, or partner mapping, or pre-intent. PartnerSignals captures four and converges them. The disagreement between streams is where the growth signal surfaces.
Foundation models change every quarter. The intelligence layer doesn't. PartnerSignals' moat is the proprietary signal ontology, scoring models, and partner-influence graph that sit above any model — your data informs our architecture, not someone else's training corpus.
PartnerSignals doesn't replace your CRM or your partner portal. It sits on top of both — surfacing the signals neither can.
"I built and ran enterprise partner ecosystems across four technology eras — internet, channel, cloud, AI. In every era, I watched the same pattern: partner-influenced revenue is real, and the revenue system can't see it.
PartnerSignals is the convergence layer I wished I'd had."
— Rick Hartley, Founder
Omdia — Jay McBain, Chief Analyst, Channels, Partnerships & Ecosystems.
Read more about Rick →Revenue Convergence is the discipline that converges partner-ecosystem signals into your CRM to grow partner-influenced revenue you can forecast. Direct pipeline has a decade of audit-trail tooling — conversation intelligence, deal-velocity scoring, engagement telemetry — so the signal that feeds it is structured and defensible. Partner-influenced pipeline is the adjacent layer that still gets called from rep narrative. Revenue Convergence brings forecast-grade rigor to that layer by running four signal streams — Conversation Intelligence, Partner Motions, Intent Signals, and Financial Signals — and converging them into a single number a CRO can defend.
You forecast it by converging the four signal streams that predict it — what was said (Conversation Intelligence), what the partner did (Partner Motions), where the account is heading (Intent Signals), and the account's financial context (Financial Signals) — into your CRM, and by reading the Forecast Delta: the gap between what the CRM says will close and what the field signals are actually showing. The disagreement between streams is the earliest warning a CRO can get.
12 questions. About 5 minutes. See where your partner program sits on the four-band maturity curve and what's blocking the next level.
Run the Partner Growth Scorecard →A structured conversation about how partner ecosystem dynamics are influencing your pipeline — and where the gaps are.
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