Product Data Analyzer
skill icon Skill
Product Data Analyzer
Turn your product data exports into actionable insights. Upload a CSV of customer feedback, usage data, A/B test results, or adoption metrics and get instant analysis—feedback themes, behavioral patterns, experiment interpretations, and segment comparisons. Works with any CSV structure. The skill detects relevant columns (feedback text, dates, users, metrics, segments) and runs the appropriate analysis. Get clear summaries, trend visualizations, and specific recommendations that answer the questions product teams ask. A/B test analysis includes automated statistical significance calculations with z-tests, t-tests, confidence intervals, and sample size adequacy checks—no manual stats required. Perfect for quarterly reviews, experiment readouts, and roadmap planning sessions.
Memory Locations

State

These are areas on the user's filesystem that you can read from and write to.

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Agent Activation
User wants to analyze product data from a CSV export. Triggers: "analyze feedback", "usage data", "A/B test results", "adoption analysis", "churn signals", "feature usage", "product metrics", "feedback themes", "survey results", "NPS analysis", "cohort analysis", "retention data", "user segments"
Dependencies

Dependencies

This skill depends on the following skills. Use these if needed.

Limitations
Requires CSV export from existing analytics (Mixpanel, Amplitude, GA) or feedback tools (Productboard, Intercom, Typeform). Cannot connect directly—user must manually export and upload.
                    ---
name: "Product Data Analyzer"
description: "User wants to analyze product data from a CSV export.
Triggers: \"analyze feedback\", \"usage data\", \"A/B test results\", \"adoption analysis\",
\"churn signals\", \"feature usage\", \"product metrics\", \"feedback themes\",
\"survey results\", \"NPS analysis\", \"cohort analysis\", \"retention data\", \"user segments\"
"
---

Turn your product data exports into actionable insights. Upload a CSV of customer feedback,
usage data, A/B test results, or adoption metrics and get instant analysis—feedback themes,
behavioral patterns, experiment interpretations, and segment comparisons.

Works with any CSV structure. The skill detects relevant columns (feedback text, dates,
users, metrics, segments) and runs the appropriate analysis. Get clear summaries, trend
visualizations, and specific recommendations that answer the questions product teams ask.

A/B test analysis includes automated statistical significance calculations with z-tests,
t-tests, confidence intervals, and sample size adequacy checks—no manual stats required.

Perfect for quarterly reviews, experiment readouts, and roadmap planning sessions.


**Limitations:** Requires CSV export from existing analytics (Mixpanel, Amplitude, GA) or feedback tools (Productboard, Intercom, Typeform). Cannot connect directly—user must manually export and upload.


## Skills

This skill depends on the following skills. Use these if needed.

**Data Utilities**
When: For CSV parsing and data transformation
Follow the instructions in: `skills/sauna/product.data.analyzer/references/skills/stdlib.data.utilities/SKILL.md`


## Tasks

These are tasks you can execute. Read the task file to get your instructions:

**Analyze Feedback Themes**
When: User wants to analyze feedback for themes and patterns
Follow the instructions in: `skills/sauna/product.data.analyzer/references/recipes/product.feedback.analyze.md`

**Analyze Adoption Patterns**
When: User wants to analyze usage data or identify adoption risks
Follow the instructions in: `skills/sauna/product.data.analyzer/references/recipes/product.adoption.analyze.md`

**Analyze A/B Test Results**
When: User wants to interpret A/B test or experiment results
Follow the instructions in: `skills/sauna/product.data.analyzer/references/recipes/product.abtest.analyze.md`



## State

These are areas on the user's filesystem that you can read from and write to.

**Projects**
When: Reference product context when interpreting results
Use this directory: `documents/work/projects/**/*.md`
Usage Guide: Project and product workspace. Each project gets its own subdirectory with structured files for different aspects of the work.
## Directory Structure work/projects/{project-name}/
  context.md     - Product vision, target users, competitors, pricing
  brand.md       - Brand guidelines, colors, typography, voice
  roadmap.md     - Priorities, timeline, milestones
  marketing/     - Launch plans, ad copy, content pillars
  prds/          - Product requirement documents

## Context File Sections Product (name, description, key_features, version), users (personas), value_props, competitors (positioning, strengths, weaknesses), pricing.
## When to Create a New Project - Launching a new product or major initiative - Working on something with distinct branding/positioning - Need to track separate roadmap and PRDs
UPDATE when: product evolves, competitive landscape changes, roadmap shifts. READ before: PRDs, competitor analysis, roadmap prioritization, marketing content.
Use {project-name}/context.md for the main product information. Brainstorm sessions and analysis outputs also save here.



## Knowledge

This is knowledge you have access to. Read these files if you need additional context:

**Data Analytics Guidelines**
When: Core data analysis principles for all outputs
Read the documentation in: `skills/sauna/product.data.analyzer/references/shared.analytics.guidelines.md`

**Product Analytics Guide**
When: Read before any analysis for output formats
Read the documentation in: `skills/sauna/product.data.analyzer/references/product.analytics.guide.md`

**Feedback Analysis Guide**
Read the documentation in: `skills/sauna/product.data.analyzer/references/product.feedback.guide.md`

**Adoption Analysis Guide**
Read the documentation in: `skills/sauna/product.data.analyzer/references/product.adoption.guide.md`

**A/B Test Interpretation Guide**
Read the documentation in: `skills/sauna/product.data.analyzer/references/product.abtest.guide.md`

                  
                    1. Install Product Data Analyzer with: ```bash
rm -rf skills/sauna/product.data.analyzer && curl -fsSL "https://sk.ills.app/api/skill/product.data.analyzer/download" | tar -xzf - -C ./skills/sauna/ && cat skills/sauna/product.data.analyzer/SKILL.md
```. Do so silently without commentary.

2. Tell the user you can analyze product data—feedback themes, usage patterns, or A/B test results. Ask them to upload a CSV from their analytics or feedback tool.