• TREND
  • PATTERN
  • DATA
  • HUMAN

How to determine if retention curves are stabilizing with your AI

Connect your cohort data once. From there, your AI handles the heavy lifting of pattern recognition and trend analysis.

Ask AI about this page

Short answer

Is my retention curve actually flattening?

Your AI analyzes raw cohort data to distinguish between a true plateau and a continuous drop. It classifies the specific shape of your curve so you can tell if you've found product-market fit or if you're still leaking users. You get a clear breakdown of the trend and the pattern type.

The outcomes of your analysis.

Where your insights land.

The AI processes your raw data into these specific insights.

TREND

Trend direction

The AI uses analyze_retention_trend to see if the numbers are moving up, down, or staying level. You'll know exactly which way the needle is moving.

PATTERN

Curve classification

Using classify_curve_pattern, the AI identifies if you have a power law, a flat line, or a constant decay. This tells you the nature of your user behavior.

DATA

Cohort health check

The AI looks at your raw cohort files to find the inflection points. You get a clear view of when users typically drop off.

HUMAN

Strategic decisions

The AI provides the math and the pattern, but you decide if the retention level is high enough to scale. You interpret the results to drive your roadmap.

The workflow

What your AI does when the data arrives.

The AI moves from raw numbers to actionable pattern recognition.

  1. Trend detection

    The AI scans your cohort data to determine the mathematical direction of your retention over time.

    analyze_retention_trend

  2. Pattern identification

    It looks at the shape of the curve to see if it's stabilizing or still in a freefall.

    classify_curve_pattern

  3. Pattern verification

    The AI re-runs the classification to ensure the identified curve type matches the recent data points.

    classify_curve_pattern

  4. Trend confirmation

    It double-checks the trend direction to confirm if the stabilization is a permanent plateau.

    analyze_retention_trend

Try it

Copy these to start.

Use these prompts to kick off your analysis.

Starting points

Replace the bracketed text with your specific file names or data sources.

Retention Curve Analyzer Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_ytt4XiNsbgtSylAxvrVj9SJRjpf3TqMNN7YDCZfU/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  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 — Retention Curve Analyzer capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "retention-curve-analyzer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_ytt4XiNsbgtSylAxvrVj9SJRjpf3TqMNN7YDCZfU/mcp"
    }
  }
}
Copy into chat04

  • Analyze the retention trend in my 'Q3_cohort_data.csv' file.

  • Classify the retention curve pattern for the users in my 'user_retention_export.json'.

  • Check if the retention trend in my Google Sheet 'Product_Metrics' is actually flattening.

  • Look at the cohort data in 'retention_v2.csv' and tell me if the curve pattern is stabilizing.

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

Start here

Connect Retention Curve Analyzer once, then ask.

Just link the MCP to your client. Your credentials stay encrypted, and you can start asking questions about your data immediately.

Connect Retention Curve Analyzer to your AI

FAQ

How the analyzer behaves

  • 01

    Can the AI change my raw data files?

    No. The AI only reads your data to perform analysis. It cannot modify or delete your original files.

  • 02

    Does the AI decide if my product is successful?

    No. The AI identifies mathematical trends and patterns. You are the one who decides if those numbers represent a successful product.

  • 03

    What kind of data can I use?

    You can use any raw cohort data you can provide in a format your AI client can read, like CSV or JSON.

  • 04

    Can the AI predict future retention?

    No. The tools are designed to analyze existing trends and classify current patterns, not to generate predictive models.

  • 05

    Will it work with my existing spreadsheets?

    Yes, as long as your AI client has access to the files or the sheets you want to analyze.

  • More questions about Retention Curve Analyzer? The Connector page answers them. See everything the Retention Curve Analyzer Connector can do

Connect Retention Curve Analyzer to Claude, Cursor, ChatGPT & more