{
  "id": "okf_vamsiramakrishnan_ge_agent_factory_okf_l_5dac1c38",
  "kind": "okf",
  "category": "dados",
  "name": "Loyalty Churn Prediction Agent",
  "tagline": "Score every active loyalty member weekly against online_orders purchase-cadence decay, cart_events browsing signals, and segment_records eng",
  "body": "# Loyalty Churn Prediction Agent\n\n> R-1501 • Customer & Loyalty\n\n## Overview\n\n- **Persona:** Loyalty Program Manager\n- **Department:** retail\n- **Objective:** Score every active loyalty member weekly against online_orders purchase-cadence decay, cart_events browsing signals, and segment_records engagement history to identify at-risk members before lapse, lifting 12-month member retention from 58% toward 73% and at-risk identification from 12% toward 78% while raising win-back campaign ROI from 1.4x to 4.2x.\n\n## KPI summary\n\n- **12-month member retention**: 58% → 73%\n- **At-risk members identified before lapse**: 12% → 78%\n- **Win-back campaign ROI**: 1.4x → 4.2x\n\n## Contents\n\n- [Playbook — role, scope, guardrails](/playbook.md)\n- [Source Systems](/systems/index.md)\n- [Data Entities](/tables/index.md)\n- [Agent Tools](/tools/index.md)\n- [Workflow Stages](/workflow/index.md)\n- [Query Capabilities](/queries/index.md)\n- [Eval Scenarios](/tests/index.md)\n- [Source Documents](/documents/index",
  "url": "https://github.com/vamsiramakrishnan/ge-agent-factory/blob/HEAD/okf/loyalty-churn-prediction-agent/index.md",
  "status": "live",
  "origin": "okf_github",
  "origin_id": "vamsiramakrishnan/ge-agent-factory:okf/loyalty-churn-prediction-agent/index.md",
  "install": "https://raw.githubusercontent.com/vamsiramakrishnan/ge-agent-factory/HEAD/okf/loyalty-churn-prediction-agent/index.md",
  "source": "https://github.com/vamsiramakrishnan/ge-agent-factory",
  "transporte": "",
  "ns": "vamsiramakrishnan",
  "versao": "0.1",
  "oficial_status": "",
  "repo_host": "github.com",
  "topico": "marketing",
  "linguagem": "",
  "licenca": "",
  "repo_topics": "",
  "repo_slug": "vamsiramakrishnan/ge-agent-factory",
  "stars": 0,
  "forks": 0,
  "prs_abertos": 0,
  "pushed_at": "",
  "repo_estado": "",
  "likes": 0,
  "comments": 0,
  "visits": 0,
  "readme_bytes": 21443,
  "readme_api": "https://agentalog.com/api/listings/okf_vamsiramakrishnan_ge_agent_factory_okf_l_5dac1c38/readme",
  "readme_fonte": "repo",
  "created_at": "2026-09-09 05:08:26",
  "updated_at": "2026-09-09 05:08:26",
  "mine": false,
  "api": "https://agentalog.com/api/listings/okf_vamsiramakrishnan_ge_agent_factory_okf_l_5dac1c38",
  "go": "https://agentalog.com/api/go/okf_vamsiramakrishnan_ge_agent_factory_okf_l_5dac1c38",
  "comments_api": "https://agentalog.com/api/listings/okf_vamsiramakrishnan_ge_agent_factory_okf_l_5dac1c38/comments",
  "readme_sha": "b07574f06342d8a1d2c44982c4914464b1679357a875e63a76b2c1788e125936",
  "readme_em": "2026-08-31 06:55:23",
  "payload": {
    "name": "vamsiramakrishnan/ge-agent-factory:okf/loyalty-churn-prediction-agent/index.md",
    "title": "Loyalty Churn Prediction Agent",
    "version": "0.1",
    "okf_bundle_dir": "okf/loyalty-churn-prediction-agent",
    "okf_index_path": "okf/loyalty-churn-prediction-agent/index.md",
    "okf_conceitos": 13,
    "okf_ref": "HEAD",
    "okf_type": "Knowledge Bundle"
  },
  "volatil_em": "2026-09-13 23:02:16"
}