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Track J: Product Management & Analytics

Priority: MEDIUM — Data-driven decisions post-launch Agent: product-analytics-specialist, ab-test-analyst Sprint Range: S6-S8 Reference: docs/product/11-product-roadmap.md (Phase 3-4 analytics features)

Status Summary​

Progress: 0% (0/22 tasks)

SectionTitleStatusTasks
J.1Product Telemetry InfrastructurePending0/5
J.2Feature Analytics & AdoptionPending0/5
J.3WO Analytics DashboardPending0/5
J.4A/B Testing & ExperimentationPending0/4
J.5Feedback & Roadmap ManagementPending0/3

J.1: Product Telemetry Infrastructure​

Sprint: S6 | Priority: P1 | Depends On: C.1 Goal: Event tracking framework with privacy controls

  • J.1.1: Implement event tracking framework
    • Client-side: page views, clicks, feature interactions
    • Server-side: API calls, WO events, agent invocations
    • Schema: event_name, user_id, tenant_id, properties, timestamp
  • J.1.2: Build event pipeline
    • Collection: client SDK + server middleware
    • Transport: Cloud Pub/Sub or Redis Streams
    • Storage: raw events -> BigQuery or ClickHouse
  • J.1.3: Implement user identification and session tracking
    • Stitching: anonymous -> identified user
    • Session: 30-min inactivity timeout
    • Cross-device: tracking via user_id
  • J.1.4: Create data privacy controls
    • Opt-out: mechanism per user
    • PII scrubbing: before analytics storage
    • Retention: 24 months for analytics events
  • J.1.5: Build real-time event dashboard
    • Live stream: for debugging
    • Volume monitoring: anomaly detection
    • Quality checks: missing fields, schema violations

J.2: Feature Analytics & Adoption​

Sprint: S6-S7 | Priority: P1 | Depends On: J.1 Goal: Feature adoption tracking with cohort analysis and segmentation

  • J.2.1: Build feature adoption tracking
    • Correlation: feature flag -> usage
    • Funnel: exposed -> tried -> adopted -> power user
    • Metrics: per-feature DAU/WAU/MAU
  • J.2.2: Create cohort analysis engine
    • Retention curves: signup cohort
    • Feature adoption: by onboarding cohort
    • Revenue cohort: expansion tracking
  • J.2.3: Implement user segmentation
    • Behavioral: power users, casual, dormant, churning
    • Role-based: QA Manager, IT Tech, Compliance Director
    • Tier-based: by subscription plan
  • J.2.4: Build product KPI dashboard
    • Engagement: DAU/WAU/MAU with trends
    • Adoption matrix: features x segments
    • Stickiness: DAU/MAU ratio
  • J.2.5: Create automated insight reports
    • Weekly: product health email to PM team
    • Anomaly alerts: usage drop, feature regression
    • Monthly: product review deck auto-generation

J.3: WO Analytics Dashboard​

Sprint: S7-S8 | Priority: P1 | Depends On: C.2, J.1 Goal: Work order performance, resource utilization, and compliance analytics

  • J.3.1: Build WO performance analytics
    • Cycle time: by WO type, priority, team
    • Bottleneck detection: longest-waiting state
    • SLA compliance: rate and breach patterns
  • J.3.2: Create resource utilization analytics
    • Workload heatmap: technician view
    • Skill-based: availability analysis
    • Capacity: overtime and planning
  • J.3.3: Implement compliance analytics
    • First-pass approval rate: target >92%
    • Audit finding trends: by category
    • CAPA effectiveness: recurrence rate
  • J.3.4: Build cost analytics
    • Cost per WO: by type and complexity
    • Budget vs. actual: per department
    • Vendor comparison: cost benchmarking
  • J.3.5: Create predictive analytics
    • Duration estimation: historical regression
    • Demand forecasting: resource needs
    • Risk scoring: compliance risk (predictive)

J.4: A/B Testing & Experimentation​

Sprint: S8 | Priority: P2 | Depends On: J.1 Goal: Experimentation framework with compliance guardrails

  • J.4.1: Build experimentation framework
    • Feature flags: percentage rollout
    • Assignment: deterministic hashing for A/B
    • Significance: Bayesian or frequentist calculator
  • J.4.2: Create experiment management UI
    • Define: hypothesis, metric, audience, duration
    • Monitor: running experiments
    • Auto-stop: on significance or guardrail violation
  • J.4.3: Implement guardrail metrics
    • Compliance: must not degrade in any experiment
    • Error rate: guardrail, latency guardrail
    • Auto-rollback: if guardrail breached
  • J.4.4: Build experiment reporting
    • Results dashboard: treatment vs. control
    • Statistics: confidence intervals and p-values
    • Long-term: holdout groups for impact tracking

J.5: Feedback & Roadmap Management​

Sprint: S7 | Priority: P2 | Depends On: C.1 Goal: Customer feedback collection, voting, and public roadmap

  • J.5.1: Build feature request system
    • Portal: customer-facing submission
    • Prioritization: voting system
    • Status tracking: submitted -> under review -> planned -> building -> shipped
  • J.5.2: Create public product roadmap
    • Format: Now / Next / Later
    • Filters: compliance, workflow, integration, analytics
    • Linking: changelog to shipped items
  • J.5.3: Implement NPS & satisfaction surveys
    • In-app NPS: quarterly + post-milestone
    • CSAT: after support interactions
    • Automated: analysis and trend reporting

Updated: 2026-02-14 Compliance: CODITECT Track Nomenclature Standard (ADR-054)