--- name: customer-lifecycle-segmentation-tagger description: "Classifies SaaS accounts into lifecycle segments from ARR, product tier, usage stage, and engagement score, then assigns a recommended CS motion, health flag, and next-best-action for each account. Use when tagging a book of business, building segmentation logic for a CS/RevOps model, or triaging accounts into the right customer success play." argument-hint: "[account-data] [segment-model]" allowed-tools: ["Read"] --- # Customer Lifecycle Segmentation Tagger ## Purpose Take raw account data and return a consistent lifecycle segment label plus a recommended CS motion for each account — replacing gut-feel bucketing with a repeatable rule-based model that CS Ops and RevOps can apply across an entire book of business. ## When to Use Invoke this skill when the user asks to: - Tag or segment a list of accounts by lifecycle stage - Assign CS motions or playbooks to a book of business - Build or standardize a customer segmentation model - Triage accounts into onboarding, adoption, retention, or expansion plays - Identify at-risk or expansion-ready accounts from usage and engagement data - Prepare account data for CSM territory assignment or health scoring ## Inputs Required Before starting, collect: - **Account list**: One or more accounts with identifiers (account name or ID) - **ARR per account**: Annual recurring revenue in dollars - **Product tier**: Plan level (e.g., Starter / Pro / Enterprise, or the account's actual tier names) - **Usage stage**: Where the account is in the product journey (Onboarding / Ramping / Established / Declining) - **Engagement score**: A 0–100 score or a qualitative band (Low / Medium / High) - **Contract timing** (optional): Days since start and days until renewal, if available - **Segment thresholds** (optional): Any existing ARR tier cutoffs or engagement bands the company already uses If contract timing is missing, infer lifecycle stage from usage stage alone. If segment thresholds aren't provided, apply the default model below and state the assumption. ## Instructions ### Step 1: Normalize the Inputs For each account, standardize the raw inputs before classifying: - **ARR tier**: Low (<$10K) / Mid ($10K–$50K) / High ($50K–$250K) / Strategic (>$250K) — adjust to provided thresholds if given - **Engagement band**: Low (0–39) / Medium (40–69) / High (70–100), or map qualitative values to these bands - **Usage stage**: Confirm one of Onboarding / Ramping / Established / Declining — if ambiguous, choose the stage that matches the described behavior and note it ### Step 2: Assign the Lifecycle Segment Classify each account into exactly one segment using this decision logic (evaluate top-down; first match wins): - **New / Onboarding** — Usage stage is Onboarding regardless of engagement. Account has not yet reached first value. - **Adopting** — Usage stage is Ramping and engagement is Medium or High. Account is actively building habits. - **Stalled Onboarding** — Usage stage is Onboarding or Ramping and engagement is Low. Account is at early-churn risk. - **Healthy / Established** — Usage stage is Established and engagement is Medium or High. Steady, value-realizing account. - **Expansion-Ready** — Established, engagement High, and ARR tier is Low or Mid relative to product tier (room to grow). Strong upsell candidate. - **At-Risk** — Usage stage is Declining, or engagement is Low with an Established stage. Churn signal present. - **Strategic Account** — ARR tier is Strategic or product tier is the top tier, overriding the above for motion prioritization (but keep the health read visible). ### Step 3: Set the Health Flag Assign a one-word health flag independent of segment: - **Green**: Engagement High and usage stage is not Declining - **Yellow**: Engagement Medium, or High engagement with a renewal inside 90 days - **Red**: Engagement Low, usage stage Declining, or Stalled Onboarding ### Step 4: Recommend the CS Motion Map each segment to a specific, named CS motion — not a generic "engage the customer": - **New / Onboarding** → Guided onboarding sequence; schedule kickoff and first-value milestone check within 14 days - **Adopting** → Adoption acceleration; targeted feature enablement + monthly usage review - **Stalled Onboarding** → Rescue play; CSM-led re-onboarding call, identify the blocked use case, executive nudge if strategic - **Healthy / Established** → Low-touch check-in cadence; quarterly business review, monitor for expansion triggers - **Expansion-Ready** → Expansion play; usage-based upsell conversation, loop in AE, present tier/seat upgrade - **At-Risk** → Save play; root-cause churn call, stakeholder re-engagement, escalate to CS leadership if ARR is Mid+ - **Strategic Account** → High-touch executive motion; named CSM, executive sponsor alignment, custom success plan ### Step 5: Define the Next-Best-Action For each account, state one concrete next action tied to the motion — a single sentence naming what to do, who owns it, and the timeframe (e.g., "CSM to book a re-onboarding call within 5 business days"). ## Output Format - **Structure**: A single table with one row per account, followed by a short summary block - **Length**: Table plus a 100–150 word summary; scales with the number of accounts provided - **Format**: Table with columns — Account | ARR Tier | Usage Stage | Engagement Band | Lifecycle Segment | Health Flag | CS Motion | Next-Best-Action - **Sections**: Segmentation table → Portfolio summary (segment distribution counts, health flag breakdown, top 3 priority accounts and why) - **Tone**: RevOps analyst — precise, decision-ready, no filler; every field populated with a defensible value ## Quality Checklist Before delivering output, verify: - [ ] Every account has exactly one lifecycle segment (no account left unclassified or double-tagged) - [ ] Every account has all 8 table columns filled — no blanks or placeholders - [ ] Health flags are consistent with the rules (no Green account in a Declining usage stage) - [ ] Each CS motion matches its segment per the Step 4 mapping - [ ] Next-best-actions are specific — each names an action, an owner, and a timeframe - [ ] The summary reports accurate segment distribution counts that sum to the total number of accounts ## Notes - The decision logic is intentionally top-down and first-match — this makes classification deterministic and auditable, which matters when CS leadership questions why an account was tagged a certain way. - Strategic Account is a motion-priority override, not a health signal — a Strategic account can and should still carry a Red health flag when the data warrants it. - When engagement score and usage stage conflict (e.g., high engagement but Declining usage), treat usage stage as the stronger churn signal and flag the account for manual review in the next-best-action. - If the company already runs a segmentation model, ask for their thresholds first — reusing existing cutoffs keeps this output compatible with their CRM tags and reporting. --- ## How to use this skill This file is a Claude Code skill in [Anthropic's standard format](https://docs.anthropic.com/en/docs/claude-code/skills) — markdown with YAML frontmatter at the top. **Installing in Claude Code:** - `~/.claude/skills//SKILL.md` — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects) - `/.claude/skills//SKILL.md` — auto-loads only when working in that project (recommended for project-specific skills) Restart Claude Code or open a new session to register. **Using in Claude.ai, ChatGPT, Gemini, or other AI tools:** 1. 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