Marketplace for the claude-ecom plugin: turn order/sales CSVs into a narrative business review with KPI decomposition and prioritized actions
npx claudepluginhub takechanman1228/claude-ecomEcommerce data analytics toolkit for D2C stores
takechanman1228
Turn order/sales CSV into a business review — KPI decomposition, prioritized findings, and concrete next actions. One command.
# Install
curl -fsSL https://raw.githubusercontent.com/takechanman1228/claude-ecom/v0.1.3/install.sh | bash
# Drop your orders CSV, Start Claude Code, and run:
/ecom review
Requires: Claude Code CLI, Python 3.10+, and git
/plugin marketplace add takechanman1228/claude-ecom
/plugin install claude-ecom@claude-ecom
/reload-plugins
Restart Claude Code. The Python backend installs automatically on session start.
The command becomes /claude-ecom:ecom review when installed as a plugin.
A single REVIEW.md that reads like a consultant wrote it:
# Business Review
> Revenue reached $9.37M for the year, essentially flat YoY (-1.7%), despite strong
> short-term momentum — the last 90 days surged 84% and November posted +28.5%,
> both driven by Q4 seasonal demand rather than structural growth. The flat annual...
30d Pulse 90d Momentum 365d Structure
Revenue $1.47M (+ 28%) $3.73M (+ 84%) $9.37M (= -2%)
Orders 3,499 (+ 26%) 8,814 (+ 60%) 24,812 (- 11%)
AOV $419 (+ 2%) $424 (+ 15%) $378 (+ 10%)
Customers 1,676 (+ 11%) 2,918 (+ 51%) 4,296 (= flat)
...
Revenue $9.37M (YoY: -1.7%)
├── 🔴 New Customer Revenue $1.45M (15.5%)
│ ├── New Customers: 1,559 (-57.8%)
│ └── New Customer AOV: $305
└── 🟢 Existing Customer Revenue $7.92M (84.5%)
├── Returning Customers: 2,737 (+345%)
├── Returning AOV: $395
└── Repeat Purchase Rate: 75.4%
Executive summary → Multi-horizon dashboard → KPI trees with 🔴/🟢 signals → Findings with "what / why / what to do" → Prioritized action plan with deadlines, success metrics, and guardrails. See a full example output →
| Command | Description |
|---|---|
/ecom review | Full business review — auto-selects 30d / 90d / 365d |
/ecom review 30d / 90d / 365d | Focus on a specific period |
/ecom review How's retention? | Ask a question instead of a full report |
Any e-commerce/retail orders CSV works.
Required columns: order ID, order date, customer ID or email, revenue (after discounts, before tax/shipping). Optional (enables deeper analysis): quantity, SKU or product name, discount amount. In many cases, column names don't need to match exactly.
Orders CSV → Python engine → review.json → Claude → REVIEW.md
Python computes every KPI and runs health checks. Claude reads the structured output and writes the business narrative. Numbers are precise because Python owns them. Interpretation is sharp because Claude owns that.
Tested on Online Retail II (UCI, CC BY 4.0) — a real UK retailer with ~1M transactions over 2 years.
See the full report → | Try it yourself →
Inspired by claude-ads by @AgriciDaniel.
MIT