Design Lifecycle Journey

Produces a customer lifecycle journey map with stages, triggers, plays, and owners.

Published by @gtmagents·from gtmagents/gtm-agents·0 agent reads / 30d·0 saves·Updated June 14, 2026

Command: design-lifecycle-journey

Inputs

segment – SMB, mid-market, enterprise, strategic, etc.
product – product line or package the journey targets.
objectives – adoption, expansion, advocacy, retention goals.
signals – optional health metrics or telemetry to align on.
tooling – optional stack info (Gainsight, HubSpot, Pendo, etc.).

Workflow

Insight Alignment – analyze current health, usage, NPS, and pipeline targets.
Stage Definition – outline onboarding, adoption, value realization, expansion, advocacy.
Trigger & Play Mapping – define triggers (usage dips, milestone hits) with recommended plays.
Owner & Channel Assignment – map CS, product, marketing, automation responsibilities.
Measurement Plan – set KPIs per stage and dashboards/alerts for monitoring.

Outputs

Journey map table (stage, trigger, play, owner, channel, KPI).
Trigger-to-play matrix for automation/CS tooling.
Measurement checklist with dashboard queries and alert rules.

Agent/Skill Invocations

lifecycle-strategist – orchestrates journey design.
customer-insights skill – supplies telemetry + signal definitions.
expansion-plays skill – recommends stage-specific offers.

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Sharebench · Public bench

Connect via MCP.

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1Pick your tool

# Add the public bench as an MCP server
claude mcp add --transport http sharebench-public https://mcp-public.sharebench.ai

# Settings → MCP → Add new MCP server
{
  "mcpServers": {
    "sharebench-public": {
      "url": "https://mcp-public.sharebench.ai"
    }
  }
}

# Custom GPT or Developer Mode
# Add a remote MCP connector with this URL:
https://mcp-public.sharebench.ai

# Append to ~/.codex/config.toml
[mcp_servers.sharebench_public]
url = "https://mcp-public.sharebench.ai"

2Ask your agent for an artifact

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