Cohort Retention AnalyticsをAIに接続

• 01 / 03リテンションのベンチマーク手法
• 02 / 03ユーザーのLTVを算出する
• 03 / 03リテンションカーブのモデル化について

最速日

518ms

最遅日

850ms

14日間の傾向

遅延傾向+13%

Cohort Retention Analytics Connector

準備完了です。MCPクライアントを選択し、セットアップ手順に従ってください。

コネクタリンクhttps://edge.vinkius.com/vk_preview_0clZooXkip3nj1SVREyeX8jIZAq7iA6bQySCHT9q/mcpコピー

Claude Desktop

以下の手順で数秒で接続できます。

1. 1In Claude Desktop, open Settings → Connectors.
2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3. 3Click Add and start a new chat — Cohort Retention Analytics capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "cohort-retention-analytics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_0clZooXkip3nj1SVREyeX8jIZAq7iA6bQySCHT9q/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

各クライアントの手順ガイドはこちらです。 接続方法

Claude向けのガイド付きセットアップ？ Cohort Retention AnalyticsをClaudeや他のAIに設定する

このConnectorが対応するすべてのAIクライアントを見る ↑

• 01

  プロダクトマネージャー

  ユーザーの定着率を把握し、プロダクトの成長戦略を立てるために使用します。

• 02

  データアナリスト

  複雑なコホート計算や業界ベンチマークとの比較作業を効率化します。

• 03

  グロースマーケター

  ユーザーのライフタイムバリューや継続パターンの分析に活用します。

• 01

  What industries is this MCP benchmarked for?

  The MCP includes hardcoded benchmarks for SaaS, E-Commerce, Gaming, and FinTech.

• 02

  Which AI clients can I use with this MCP?

  You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

• 03

  Do I need to host this myself?

  No, Vinkius hosts and manages the MCP for you. You just connect it once and it is ready to use.

• 04

  Can I use this to calculate user lifetime?

  Yes, the calculate_average_lifetime capability determines the expected number of months a user stays active.

• 05

  How do I compare my data to industry standards?

  Use the compare_performance_to_benchmark capability to check your metrics against specific category standards.

• 06

  How do I calculate the retention curve?

  Use the calculate_retention_curve capability by providing an array of retention rates where the first element is 1.0 (representing 100% retention at Month 0).

• 07

  How can I check if my SaaS retention is good?

  Use the compare_performance_to_benchmark capability. Pass 'SaaS' as the product category and your observed metric as the actual value to see if it is 'Above Benchmark' or 'At Risk'.

• 08

  What does average lifetime represent in this capability?

  The calculate_average_lifetime capability calculates the expected number of months a user remains active by summing all retention rates provided in your input array.

• 

  Retention Curve Analyzer AIコネクタ

  Analyze cohort retention curves to identify stability versus churn and compare against industry benchmarks.

  表示
• 

  AI SaaS Feature Churn Correlation AIコネクタ

  Quantify the impact of AI features on customer retention and calculate prevented churn revenue.

  表示
• 

  Accelerator Cohort Diversity Analytics AIコネクタ

  Analyze cohort diversity, inclusion indices, and performance correlations.

  表示
• 

  Enterprise Logo Retention Analytics AIコネクタ

  Analyze customer retention rates, tier breakdowns, and churn risks for enterprise segments.

  表示

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