full-link-data-analysisTransforms business questions into structured analytical reports using seven-layer architecture with tailored Python code, quality checks, and Feishu doc out...
Install via ClawdBot CLI:
clawdbot install openlark/full-link-data-analysisGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
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https://clawhub.ai/user/openlarkAudited Jun 2, 2026 · audit v1.0
Generated Jul 26, 2026
An e-commerce company notices a month-over-month sales decline. Using the full-link analysis engine, the agent identifies the persona (operations manager), scopes relevant data (orders, traffic, promotions), decomposes the problem into funnel and cohort analyses, selects causal inference methods, and outputs a report with actionable insights.
A SaaS company wants to understand why customer churn increased last quarter. The agent analyzes usage logs, support tickets, and billing data across customer segments, applies survival analysis and logistic regression, and delivers a Feishu report highlighting key drivers and retention recommendations.
A retail chain wants to attribute sales lift to specific marketing campaigns across regions. The agent uses time-series decomposition and difference-in-differences to isolate campaign effects, accounts for confounding factors, and provides a report with confidence intervals and cross-validation.
A fintech company needs to detect new fraud patterns in transaction data. The agent applies clustering (e.g., DBSCAN) and anomaly detection methods to identify suspicious clusters, then validates with statistical tests, outputting a report with risk scores and recommended rules.
A hospital wants to reduce emergency department wait times. The agent analyzes patient flow data, runs a funnel analysis from arrival to discharge, identifies bottlenecks via queuing theory, and proposes staffing adjustments in the report.
Offer the full-link data analysis capability as a monthly subscription service for businesses, charging based on the number of analysis runs or data volume. Customers get access to the AI agent for on-demand reports.
Provide tailored analysis reports for clients on a per-project basis. Each report includes the full seven-layer process and a Feishu document with actionable insights. Pricing depends on complexity and data scope.
Integrate the analysis engine as an add-on module for existing business intelligence or CRM platforms. Charge per active user or per query. Target enterprise clients who need automated, rigorous analysis.
💬 Integration Tip
Integrate with Feishu by using the Feishu API to push reports directly to user chat or docs; ensure the agent can request data via APIs or local file uploads.
Scored Jul 26, 2026
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