AI Adoption Analytics: Usage, CSAT, and ROI Dashboards

yaml
version: 1.3
artifact: telemetry_trust_layer
owner: analytics-chief-of-staff@company.com
reviewers:
  - security@company.com
  - legal@company.com
  - data-governance@company.com
regions:
  primary: us-east-1
  dr: us-west-2
residency:
  model_processing: in-region
  warehouse: snowflake://prod_analytics
slo:
  data_freshness_minutes: 15
  survey_response_rate_min: 35
  adoption_score_uptime: 99.9
streams:
  usage_events:
    sources: [zendesk, salesforce, servicenow, slack]
    schema:
      - timestamp: ts
      - user_id: hashed_uuid
      - role: enum[support_agent,sales_ae,manager]
      - event: enum[invoked,completed,edited,accepted]
      - workflow: enum[triage,reply_draft,call_summary,deal_update]
      - latency_ms: int
      - tokens_used: int
      - confidence: float
    rbac:
      read: [analytics, eng_observability]
      write: [ai_platform]
    pii_redaction:
      fields: [user_id]
      method: sha256_salt
    retention_days: 365
  survey_responses:
    sources: [typeform, qualtrics]
    schema:
      - timestamp: ts
      - user_id: hashed_uuid
      - role: enum
      - workflow: enum
      - csat: int[1-5]
      - theme: enum[accuracy,speed,ux,policy]
      - comment: text
    rbac:
      read: [analytics, enablement]
      write: [enablement]
    retention_days: 180
  roi_metrics:
    sources: [snowflake_marts.kpi, timesheets, product_logs]
    schema:
      - week: date
      - workflow: enum
      - baseline_aht_minutes: float
      - current_aht_minutes: float
      - time_returned_hours: float
      - csat_delta: float
      - adoption_score: float
      - confidence_interval: float
    rbac:
      read: [exec, analytics]
      write: [analytics]
  prompt_logs:
    enabled: true
    retention_days: 90
    access: [security, audit, ai_platform]
thresholds:
  adoption_score:
    green: 
      activation_rate_gte: 0.6
      depth_events_per_user_gte: 5
      4wk_retention_gte: 0.5
    amber:
      activation_rate_gte: 0.4
      depth_events_per_user_gte: 3
      4wk_retention_gte: 0.35
    red: otherwise
approvals:
  change_control:
    required: true
    steps:
      - name: schema_change_review
        owner: data-governance@company.com
        sla_hours: 48
      - name: rbac_update
        owner: security@company.com
        sla_hours: 24
observability:
  dashboards: [looker://adoption_scorecard, powerbi://roi_overview]
  alerts:
    - name: adoption_drop_10pct_week
      metric: adoption_score
      condition: week_over_week <= -0.10
      notify: [owner, enablement_lead]
    - name: csat_pulse_low
      metric: csat
      condition: rolling_7day_avg < 3.5
      notify: [owner, product_lead]
notes:
  - never_train_on_client_data: true
  - human_in_the_loop_required_for_external_emails: true
  - audit_trail_enabled: true

{
  "title": "AI Adoption Analytics: Usage, CSAT, and ROI Dashboards",
  "published_date": "2025-11-22",
  "author": {
    "name": "David Kim",
    "role": "Enablement Director",
    "entity": "DeepSpeed AI"
  },
  "core_concept": "AI Adoption and Enablement",
  "key_takeaways": [
    "Adoption needs three lenses: usage analytics, satisfaction signals, and ROI tied to core KPIs.",
    "Instrument once, measure everywhere: centralize telemetry in Snowflake/BigQuery and standardize event schemas.",
    "Launch a weekly Adoption Score with clear thresholds and owners to stop opinion loops.",
    "Use short CSAT pulses in the flow of work; combine with intent and outcome labels for causality.",
    "Keep it governed: prompt logs, RBAC, and data residency build audit-ready trust across Legal and Security."
  ],
  "faq": [
    {
      "question": "How do we avoid vanity metrics like logins?",
      "answer": "Define canonical events that represent value—invoked, completed, edited, accepted—per workflow. Weight activation, depth, and retention into a single Adoption Score and publish thresholds with owners."
    },
    {
      "question": "Can we attribute ROI without randomized trials?",
      "answer": "We use pre/post baselines with matched control cohorts where randomization isn’t feasible and display confidence intervals. We also correlate satisfaction themes with KPI movement to increase signal quality."
    },
    {
      "question": "Will this satisfy Security and Legal?",
      "answer": "Yes. We implement RBAC, prompt logging, redaction, and residency controls. All changes route through change control with audit trails, and models never train on your data."
    }
  ],
  "business_impact_evidence": {
    "organization_profile": "2,500-employee B2B SaaS company operating in North America and EMEA; Support on Zendesk, Sales on Salesforce, data in Snowflake.",
    "before_state": "Fragmented adoption reporting, no post-usage CSAT pulses, and no trusted ROI linkage; legal blocked broader rollout without prompt logs and RBAC.",
    "after_state": "Governed telemetry in Snowflake with a weekly Adoption Scorecard, 10-second CSAT pulses, and an ROI dashboard tied to AHT and CSAT.",
    "metrics": [
      "Weekly active users in targeted cohorts: 38% to 49% (+11 pts) in 30 days",
      "Support analyst time returned: +2.1 hours/week per analyst",
      "CSAT pulse after knowledge answers: 3.6 to 4.2 (+0.6)",
      "Executive weekly decision time on enablement priorities: 60 to 20 minutes"
    ],
    "governance": "Security approved due to RBAC aligned to HR roles, prompt logging with 90-day retention, in-region data residency, and a guarantee that models never train on client data; Legal signed off with redaction and human-in-the-loop for external emails."
  },
  "summary": "Chiefs of Staff: ship a 30-day enablement analytics plan—usage, CSAT, ROI—governed telemetry and dashboards that show what’s adopted and what’s moving KPIs."
}