- Home
- Skills
- Shaul1991
- Shaul Agents Plugin
- Growth Analytics
growth-analytics_skill
- Makefile
0
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill shaul1991/shaul-agents-plugin --skill growth-analytics- SKILL.md592 B
Overview
This skill is a Growth Analyst Agent that tracks and analyzes product growth metrics to surface actionable insights. It focuses on cohort, funnel, and segment analyses to help prioritize experiments and optimize user acquisition and retention. The agent delivers concise, data-driven recommendations for teams responsible for growth and product performance.
How this skill works
The agent ingests metric definitions and time-series event data, then computes core growth KPIs like activation, retention, churn, and conversion rates. It runs cohort and funnel analyses to identify drop-off points and segment-based performance differences. Outputs include clear visual summaries and prioritized recommendations tied to measurable impact.
When to use it
- When you need to understand why a conversion funnel is underperforming
- To measure retention changes after a product or marketing experiment
- When prioritizing growth initiatives based on potential impact
- To compare behavior across user segments or acquisition channels
- When building dashboards and reports for growth stakeholders
Best practices
- Define consistent metric names and event schemas before analysis
- Use cohorts aligned to meaningful start events (signup, first purchase, activation)
- Segment results by acquisition source, geography, and device for deeper insight
- Validate data quality and sampling before drawing conclusions
- Translate analysis into prioritized actions with expected impact and metrics to track
Example use cases
- Perform cohort retention analysis to quantify the effect of a product onboarding change
- Run funnel analysis to locate the highest-impact drop-off and recommend A/B tests
- Compare lifetime value and churn across acquisition channels to reallocate budget
- Segment new users to identify high-value profiles for targeted campaigns
- Generate a weekly growth report summarizing KPIs and suggested next steps
FAQ
Time-stamped event data and clear metric definitions (e.g., activation, purchase) plus any segment keys like channel or country.
Can it prioritize recommendations?
Yes. Recommendations are scored by estimated impact and confidence based on historical effect sizes and sample sizes.