White Paper: Customer Revenue Intelligence
Executive summary
Revenue teams need a unified picture of pipeline, product usage, support risk, billing status, and relationship health—updated continuously and grounded in evidence. Intelletto’s Customer Revenue Intelligence (CRI) unifies these signals into a single graph, produces explainable Propensity to Expand and Risk of Churn scores, and boosts forecast reliability with a sidecar that sits inside CRM/CS tools. Role‑specific playbooks and nudges coordinate AEs, AMs, CSMs, and RevOps around the right actions at the right time.
- Higher forecast reliability and fewer end‑of‑quarter surprises
- NRR uplift via targeted expansion plays and risk triage
- Shorter cycle time with prioritized actions and nudges
- Board‑ready transparency with readable reasons and audit trails
Contents
Problem & market context
Revenue data lives in silos: CRM opportunities, product telemetry, billing, support tickets, surveys, and contracts. Teams debate whose number is “right,” and leaders lack a defensible, explainable view of risk and upside. CRI aims to replace guesswork with a shared, auditable revenue map that updates itself.
Solution overview
Unified Revenue Signal Graph
Stitches CRM, product, billing, support, and relationship signals with lineage and freshness metadata.
Propensity & Risk Models
Explainable scores for expansion and churn risk, with sub‑scores and plain‑language reasons.
Forecast Reliability
Objective overlays on rep forecasts; highlights upside/downside with confidence bands.
Playbooks & Nudges
Role‑aware actions (expansion, rescue, adoption) triggered by changes in the signal graph.
Executive Cockpit
NRR/GRR, cohort trends, risk heatmaps, and scenario “what‑ifs” for quarterly planning.
Sidecar Deployment
Embedded components inside CRM/CS tools; no rip‑and‑replace required.
Architecture & data flow
Ingestion & normalization
- CRM (accounts, opps, activities, ownership)
- Product telemetry (seats, depth/breadth, feature adoption)
- Billing (ARR/MRR, invoices, usage‑based spend)
- Support (tickets, SLA, backlog, CSAT)
- Surveys & health (NPS, pulse, EBR notes)
- Contracts (terms, renewals, price caps/floors)
Governed modeling
- Feature store with lineage and freshness
- Cohort definitions and calendar alignment
- Training, validation, and shadow evaluation
Serving & orchestration
- APIs for scores, reasons, and action suggestions
- Sidecar widgets inside CRM/CS for daily use
- Event bus to trigger playbooks & notifications
- Exports for finance and board reporting
Signal catalog
Product usage
DAU/WAU/MAU, seat coverage, feature depth, time to first value, milestone completion.
Billing & contracts
ARR/MRR trend, invoice status, usage spend volatility, renewal dates, term & price clauses.
Support & sentiment
Backlog size, SLA breaches, ticket mix, CSAT/NPS, EBR notes and commitments.
Account activity
Meetings, multi‑threading depth, executive coverage, email/meeting responsiveness.
Company signals
Hiring/firing, leadership changes, funding & filings, technology stack changes.
Value milestones
Outcome adoption, ROI confirmations, referenceability, community participation.
Models & explainability
Propensity & Risk
- Propensity to expand: seat growth, feature unlocks, value milestones
- Risk of churn: adoption decay, support strain, executive disengagement
- Forecast reliability: variance vs. historical, objective vs. rep commits
Each score includes sub‑scores and readable reasons; thresholds can be tuned by cohort.
Human‑in‑the‑loop
- Rep/CSM confirmations and overrides
- Rationale editing with immutable history
- Bias & drift monitors across regions and segments
Go‑to‑market journeys
AE/AM workflow
- Prioritized account list with expand/risk flags
- Drill into reasons and sub‑scores; validate evidence
- Trigger playbooks (multi‑thread, EBR, pilot, pricing)
- Log outcomes; update opportunity confidence
CS leader cockpit
- Risk heatmap by segment and product
- Coverage gaps and SLA trends
- Renewal calendar with risk bands and what‑ifs
- Exports for exec and board reviews
Outcomes & KPIs
Typical post‑deployment focus areas include forecast accuracy, expansion yield, churn reduction, and cycle time. Establish baselines per segment and track monthly with cohort views.
- Forecast reliability (commit vs. actuals)
- NRR/GRR and expansion yield
- Churn rate and risk triage lead time
- Cycle time to close and to renewal
Ranges are illustrative; calibrate targets by segment (SMB/MM/ENT) and product line.
Trust, privacy & governance
Explainability
Readable reasons with feature contributions; change logs for thresholds and playbooks.
Responsible AI
Fairness and drift monitoring across cohorts; alerts and approvals for major model changes.
Privacy
Role‑based access, minimization, and retention; financial data handled with strict controls.
Adoption plan
- Week 0–2: Connect CRM, product telemetry, billing, and support; define segments and KPIs.
- Week 2–4: Baseline forecast and NRR/GRR; enable sidecar widgets; configure playbooks.
- Week 4–8: Pilot in one region/segment; calibrate thresholds; activate alerts.
- Week 8–12: Roll out to more teams; introduce board‑level exports and scenario planning.
- Week 12+: Continuous monitoring; quarterly governance reviews; expand signal coverage.
Limitations & risks
- Data quality: Sparse or lagging telemetry reduces reliability; invest in instrumentation.
- Attribution: Confounding factors (pricing, packaging, seasonality) require careful controls.
- Behavioral change: Reps must trust reasons and engage with playbooks; train and iterate.
- Privacy: Billing and contract data require strict access control and audit.
Appendix: glossary & references
- NRR / GRR
- Net and Gross Revenue Retention: expansion minus churn vs. churn only.
- Propensity to Expand
- Probability that an account will increase spend (seats, features, usage) in a given window.
- Risk of Churn
- Probability that an account will cancel or materially reduce spend in a given window.
This document paraphrases publicly available positioning for Customer Revenue Intelligence and organizes it as a formal white paper.