Fewshot Attempt 02

CRM Retention Analytics Skill

Purpose

Generate structured retention analytics reports (QBR packets, risk queues, action boards, receivables reviews, churn validation) from the ApexCloud Retention Operations API.

API Base URL

Read environment_access.md in the current solver directory. Use the GDPEVO_ENV_BASE_URL value as the API base URL. Do not hard-code localhost as the operative base URL.

Core Endpoint Families

Account & Profile

• GET /api/accounts/<account_id> — account profile (ARR, segment, tenure, renewal date, health flags)
• GET /api/accounts/<account_id>/metrics?start=YYYY-MM&end=YYYY-MM — monthly revenue, SLA, usage metrics
• GET /api/accounts/<account_id>/tickets?start=YYYY-MM-DD&end=YYYY-MM-DD — support ticket counts and SLA breaches
• GET /api/accounts/<account_id>/nps?start=YYYY-MM-DD&end=YYYY-MM-DD — NPS scores by survey date

Finance & Pipeline

• GET /api/finance/ar-aging — A/R aging snapshot; filter by as_of date when needed
• GET /api/opportunities — open/won/lost pipeline; filter by quarter/close-date range
• GET /api/hr/summary — headcount and claims for ops context
• GET /api/events/performance — event orders and revenue for ops context

Product Health

• GET /api/health/usage — product usage trends (often account-scoped or portfolio-scoped)

Exports

• GET /exports/churn/train.csv — churn model training data
• GET /exports/churn/validation.csv — churn model validation data
• GET /exports/churn/candidates.csv — candidate accounts with predicted churn probabilities

Workflow Rules

1. Parse the prompt first: extract account IDs, date ranges, months, as-of dates, quarter, region, and any explicit due dates.
2. Read the answer template: input/payloads/answer_template.json defines the exact output schema, required keys, and ordering.
3. Fetch data in dependency order:
   • Account profiles first (to validate IDs and get ARR/segment/tenure).
   • Metrics/tickets/NPS in parallel per account.
   • Finance/pipeline/HR/event data as a second wave.
   • CSV exports last (only for churn-model tasks).
4. Cross-reference carefully:
   • A/R customers link to CRM accounts by legal name matching; link_status is "linked" when a CRM account_id is found, else "unlinked".
   • Use the exact account_id values from the prompt; never invent or normalize them.
5. Compute derived fields before assembling JSON:
   • average_revenue = mean of monthly revenues.
   • arr_at_risk = sum of current_arr for accounts with risk_level in (critical, high, medium).
   • net_revenue_exposure = arr_at_risk − open_expansion_pipeline.
   • win_rate_pct = won_count / (won_count + lost_count) × 100.
   • ticket_trend = compare early-month ticket count to late-month count: improving if decreasing, worsening if increasing, flat if same.
6. Rank deterministically: when the prompt asks for a ranked list, sort by the primary metric (risk score, churn probability, etc.) descending; break ties by account_id ascending.
7. Populate policy_codes exactly as required by the answer template. Common codes observed:
   • Risk model: RS-6
   • ARR source: REV-4
   • Support hygiene: SUP-8
   • Action priority: ACT-5
   • Board sort: BORD-4
   • Exposure formula: EXP-6
   • Calendar policy: CAL-5
   • Receivable trigger: RCP-7
   • CRM match: CM-5
   • Pipeline window: PW-6
   • Follow-up scope: FS-4
   • Model protocol: MOD-7
   • Probability scale: PRB-4
   • Deployment rule: DEP-5
   • Outreach mapping: OUT-2

Controlled Labels (Enum Vocabularies)

Use these exact strings; never paraphrase.

Risk Levels

• critical, high, medium, low

Primary / Outreach Actions

• collections_followup — overdue receivables exist
• technical_recovery — SLA degradation, usage decline, or NPS drop
• renewal_save — renewal window approaching, low tenure
• executive_qbr — strategic account needing executive engagement
• nurture_monitor — healthy account, no immediate risk
• no_action — low risk, no follow-up needed

Reason Codes

• renewal_window — within renewal period
• overdue_receivable — overdue_balance > 0
• nps_drop — NPS below threshold or declining
• sla_degradation — SLA compliance below 100 % or trending down
• usage_decline — product usage decreasing
• low_tenure_high_churn — short tenure combined with high churn probability
• expansion_offset — large open expansion pipeline offsets risk
• clean_billings — no overdue balance, no critical issues

Ticket Trend

• improving, worsening, flat

Metric Sources

• crm_closed_won, support_export, sla_report, nps_survey, billing_snapshot, ar_aging, pipeline_crm, event_dashboard, hr_report

Review Owner

• solutions_engineering, customer_success, finance_ops

Agenda Topics (QBR)

• partnership_overview, q2_metrics, performance_highlights, q3_initiatives, technical_recovery, commercial_expansion

Link Status (Receivables)

• linked, unlinked

Accuracy Band

• 90_plus

Model Checks

• tenure_risk_direction: negative, positive, not_assessed
• uses_billing_arr_source: boolean

Output Precision Rules

Business Rules & Pitfalls

• Collections first: if overdue_balance > 0, primary_action should normally be collections_followup unless other signals are overwhelmingly stronger.
• Renewal window + low tenure: combine into renewal_save action with renewal_window and low_tenure_high_churn reason codes.
• Expansion offset: when an account has a large open_expansion_pipeline, include expansion_offset in reason_codes and subtract from exposure calculations.
• Clean billings: only add clean_billings reason code when overdue_balance == 0 and no critical/high risk factors are present.
• Next touch due date: map from the prompt’s action-specific due dates; use null for no_action accounts.
• Segment summary: strategic_accounts + enterprise_accounts must equal total accounts reviewed. Count segments from account profile data.
• Do not include test answers: the skill must describe how to derive values, not provide pre-computed numbers.
• Do not access files outside the solver attempt directory: all inputs (prompt, answer template, environment) are inside the staged directory.

JSON Assembly Checklist

1. Top-level keys match answer_template.json exactly.
2. Arrays are ordered as specified (by rank, by date, or alphabetically when instructed).
3. All enum values are from the controlled vocabularies above.
4. Numeric precision matches the table.
5. policy_codes object is present when the template requires it.
6. No extra keys, no missing required keys, no trailing commas.