How RMOS™ Unifies Signals Into Scoring
RMOS™ ingests behavioral, firmographic, intent, and lifecycle signals, stitches them to an identity graph, and converts them into explainable scores that drive routing, SLAs, and next-best actions across people and accounts.
RMOS™ unifies signals by defining a governed signal → feature → score → action pipeline. Web & product telemetry, MAP/CRM activity, third-party intent, enrichment, and sales notes are normalized to a shared taxonomy, joined via person/account identity, transformed into features (recency, frequency, fit, engagement depth), and combined using rules + models to output lead/contact and account scores. Scores power routing, prioritization, plays, and budget decisions, with a feedback loop that re-calibrates based on pipeline, win rate, and revenue.
What Signals Feed RMOS™ Scoring?
The RMOS™ Scoring Pipeline
Use this sequence to turn noisy signals into reliable scores—and reliable scores into revenue actions.
Ingest → Identity → Normalize → Feature → Score → Act → Learn
- Ingest signals: Map data sources (web/app, MAP, CRM, ad, intent, enrichment, events). Define contracts & cadence.
- Resolve identity: Stitch people and accounts via emails, domains, user IDs, and partner IDs to a unified graph.
- Normalize taxonomy: Standardize channels, activities, assets, personas, buying stages. Deduplicate & quality-check.
- Engineer features: Recency/frequency, topic affinity, buying group coverage, stakeholder seniority, ICP fit.
- Score with rules + models: Blend heuristic thresholds with statistical/ML models; keep scores interpretable.
- Route & orchestrate: Tie score bands to SLAs, sequences, plays, and ad suppression/activation.
- Calibrate & govern: Monitor lift by band, false positives/negatives, drift; run monthly council to adjust weights.
RMOS™ Scoring Capability Maturity Matrix
| Capability | From (Ad Hoc) | To (Operationalized) | Owner | Primary KPI |
|---|---|---|---|---|
| Signal Ingestion | Isolated tools, manual lists | Automated pipelines with contracts & data tests | RevOps/Data | Freshness, Completeness |
| Identity Resolution | Email-only matching | Person+Account graph with buying group detection | RevOps | Match Rate, Dupes Removed |
| Feature Store | One-off fields | Versioned features with lineage & documentation | Analytics | Feature Coverage, Stability |
| Scoring Method | Static point model | Hybrid (rules+ML) with explainability & banding | Marketing Ops | Lift (SQL/Win), Precision/Recall |
| Routing & SLAs | Best-effort follow-up | Score-band SLAs, sequenced plays & suppression rules | Sales Ops | Speed-to-Lead, Acceptance Rate |
| Governance & Drift | Annual review | Monthly council, drift alerts, backtesting & holdouts | Rev Council | Pipeline Predictability, ROMI |
Client Snapshot: Scoring That Sales Trusts
By unifying web/product signals with third-party intent and enforcing score-band SLAs, a B2B tech firm increased SQL rate by 28% and improved pipeline predictability quarter over quarter. Explore outcomes: Comcast Business · Broadridge
Align scores to journeys in The Loop™ Guide and route with Lead Management or ABM plays to turn intent into revenue.
Frequently Asked Questions about RMOS™ Scoring
Turn Signals Into Revenue—Reliably
We’ll build your RMOS™ scoring pipeline, align SLAs and plays, and calibrate for lift you can measure.
Operationalize Lead Scoring Activate Account Scoring