Agent skill

Ecom Analytics

by asgard-ai-platform in asgard-ai-platform/skills

Analyze e-commerce performance using GA4 metrics, conversion funnel analysis, and key e-commerce KPIs.

MITAuto-check passedSales & Support

Install Ecom Analytics

skills CLI
$ npx skills add asgard-ai-platform/skills --skill ecom-analytics -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install asgard-ai-platform/skills ecom-analytics --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ecom-analytics .claude/skills/ecom-analytics && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ecom-analytics
GitHub stars
242
Token cost
~1.3k tokens
SKILL.md length
397 words
Files
4 (incl. references)
Skills in repo
207
Repo updated
First seen
Licence
MIT

At a glance

Analyze e-commerce performance using GA4 metrics, conversion funnel analysis, and key e-commerce KPIs.

  • The user needs to evaluate online store performance
  • SKILL.md covers Overview, Framework, Output Format and Gotchas, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Diagnose conversion drop-offs

What it does

Ecom Analytics is an agent skill from asgard-ai-platform/skills. Analyze e-commerce performance using GA4 metrics, conversion funnel analysis, and key e-commerce KPIs. Use this skill when the user needs to evaluate online store performance, diagnose conversion drop-offs, set up e-commerce tracking, or create performance dashboards — even if they say 'why are sales down', 'optimize our online store', 'set up GA4 for e-commerce', or 'what metrics should we track'.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `examples/sample_scenario.md`, `references/ecom-benchmarks.md` and `references/ga4-setup.md`).

It sits in Sales & Support, covering E-commerce operations and Product analytics. It works with Google Analytics. The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.

When your agent uses it

  • The user needs to evaluate online store performance
  • Diagnose conversion drop-offs
  • Set up e-commerce tracking
  • Create performance dashboards — even if they say why are sales down

Example prompts

  • “why are sales down”
  • “optimize our online store”
  • “set up GA4 for e-commerce”
  • “/ecom-analytics”

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ecom Analytics loads about 1.3k tokens when it runs, and up to ~6.6k if it reads all its reference files. Until then it costs about 104 tokens; SKILL.md has 397 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~104
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 397 words, ~1,253 tokens.

Download SKILL.mdSave it as .claude/skills/ecom-analytics/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
ecom-analytics
description
Analyze e-commerce performance using GA4 metrics, conversion funnel analysis, and key e-commerce KPIs. Use this skill when the user needs to evaluate online store performance, diagnose conversion drop-offs, set up e-commerce tracking, or create performance dashboards — even if they say 'why are sales down', 'optimize our online store', 'set up GA4 for e-commerce', or 'what metrics should we track'.
metadata.category
WP-01 電商
metadata.tags
e-commerce, analytics, ga4, conversion

E-Commerce Analytics

Overview

E-commerce analytics measures online store performance across traffic, conversion, and revenue dimensions. This skill covers GA4 e-commerce tracking setup, funnel analysis, and key metric interpretation to diagnose why a store is or isn't performing.

Framework

IRON LAW: Diagnose by Funnel Stage, Not by Symptom

"Sales are down" is a symptom, not a diagnosis. Decompose into funnel stages:
Traffic × Conversion Rate × AOV = Revenue

If revenue drops 20%, is it because traffic dropped (acquisition problem),
conversion dropped (UX/pricing problem), or AOV dropped (product mix problem)?
Each requires a completely different fix.
E-Commerce Funnel & Key Metrics
StageMetricsWhat It Tells You
AcquisitionSessions, Users, Traffic sources, CPC, CACAre you attracting enough visitors? From where? At what cost?
EngagementPages/session, Time on site, Bounce rate, Product viewsAre visitors interested? Are they browsing?
ConversionAdd-to-cart rate, Checkout initiation rate, Purchase conversion rateWhere in the funnel are they dropping off?
RevenueRevenue, AOV, Items per order, Revenue per sessionHow much are they spending? Is the mix healthy?
RetentionRepeat purchase rate, Purchase frequency, Customer lifetime valueAre they coming back?
GA4 E-Commerce Events
EventTriggerKey Parameters
view_itemProduct page viewitem_id, item_name, price, category
add_to_cartAdd to cart clickitems array, value, currency
begin_checkoutCheckout starteditems, value, coupon
add_payment_infoPayment enteredpayment_type
purchaseOrder completedtransaction_id, value, tax, shipping, items
Diagnosis Framework

Phase 1: Traffic Check

  • Is total traffic up/down/flat vs prior period?
  • Which channels changed? (organic, paid, social, direct, referral)
  • Is traffic quality declining? (bounce rate, pages/session by source)

Phase 2: Conversion Check

  • Where is the biggest funnel drop-off?
  • Compare: View → Add to cart → Checkout → Purchase
  • Industry benchmark conversion rates: 1-3% overall, 5-10% add-to-cart

Phase 3: Revenue Check

  • AOV trend: rising (upselling working) or falling (discounting eroding value)?
  • Product mix: is revenue shifting to lower-margin products?
  • Revenue per session: the master metric (traffic quality × conversion × AOV)

Phase 4: Retention Check

  • Repeat purchase rate by cohort
  • Time between first and second purchase
  • LTV trend by acquisition channel
Show full SKILL.md (120 more words)Show less

Output Format

markdown
# E-Commerce Performance Report: {Store}

## Summary Dashboard
| Metric | Current | Prior Period | Change | Status |
|--------|---------|-------------|--------|--------|
| Sessions | {N} | {N} | {%} | 🟢/🟡/🔴 |
| Conversion Rate | {%} | {%} | {%} | 🟢/🟡/🔴 |
| AOV | ${X} | ${X} | {%} | 🟢/🟡/🔴 |
| Revenue | ${X} | ${X} | {%} | 🟢/🟡/🔴 |

## Funnel Analysis
| Stage | Volume | Rate | Drop-off | Benchmark |
|-------|--------|------|----------|-----------|
| Sessions | {N} | 100% | — | — |
| Product Views | {N} | {%} | {%} | — |
| Add to Cart | {N} | {%} | {%} | 5-10% |
| Checkout | {N} | {%} | {%} | 40-60% of ATC |
| Purchase | {N} | {%} | {%} | 1-3% overall |

## Diagnosis
- Primary issue: {funnel stage} — {specific problem}
- Root cause: {analysis}

## Recommendations
1. {action targeting the diagnosed stage}

Gotchas

  • Conversion rate is meaningless without traffic quality context: A 5% conversion rate from email (high-intent) and 0.5% from display ads (low-intent) are both normal. Don't compare across channels.
  • GA4 sessions ≠ Universal Analytics sessions: GA4 uses event-based model. Session timeout and attribution rules differ. Expect 5-15% discrepancy during migration.
  • Mobile conversion is always lower: Mobile: 1-2%, Desktop: 3-5% is typical. Don't mix them in one number — analyze separately.
  • Seasonality matters: Compare same period YoY, not just MoM. E-commerce has strong seasonal patterns (11.11, Christmas, Chinese New Year).
  • Revenue ≠ profit: A 20% revenue increase from aggressive discounting may reduce profit. Track margin alongside revenue.

References

  • For GA4 setup guide, see references/ga4-setup.md
  • For e-commerce benchmark data by industry, see references/ecom-benchmarks.md

© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in ecom-analytics of asgard-ai-platform/skills.

  • SKILL.md
  • examples/sample_scenario.md
  • references/ecom-benchmarks.md
  • references/ga4-setup.md

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Ecom Analytics next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Olore Gtag Latestolorehq/olore104—~411Automated safety check: PassMIT
Amazon Subscribe Savenexscope-ai/Amazon-Skills741—~456Automated safety check: PassMIT
Ga4 Analyticssundial-org/awesome-openclaw-skills663—~1.6kAutomated safety check: NotesNone
List Segment Builderaaron-he-zhu/aaron-marketing-skills2.9k2 repos~3.2kAutomated safety check: PassApache-2.0

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Categories

Questions about Ecom Analytics

What does Ecom Analytics do?

Analyze e-commerce performance using GA4 metrics, conversion funnel analysis, and key e-commerce KPIs. Ecom Analytics is an agent skill from asgard-ai-platform/skills. Analyze e-commerce performance using GA4 metrics, conversion funnel analysis, and key e-commerce KPIs.

When should I use Ecom Analytics?

Ecom Analytics fits situations like: the user needs to evaluate online store performance; diagnose conversion drop-offs; set up e-commerce tracking; create performance dashboards — even if they say why are sales down.

How do I install Ecom Analytics in Claude Code?

Run `npx skills add asgard-ai-platform/skills --skill ecom-analytics -a claude-code`. Or copy the skill folder (ecom-analytics in asgard-ai-platform/skills) into .claude/skills/ecom-analytics in your project. Claude Code loads it when a task matches its description.

How do I install Ecom Analytics in Codex?

Run `npx skills add asgard-ai-platform/skills --skill ecom-analytics -a codex`. Or copy the skill folder (ecom-analytics in asgard-ai-platform/skills) into .agents/skills/ecom-analytics in your project. Codex loads it when a task matches its description.

Can I use Ecom Analytics in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add asgard-ai-platform/skills --skill ecom-analytics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ecom-analytics, .gemini/skills/ecom-analytics, .github/skills/ecom-analytics and .opencode/skills/ecom-analytics in your project.

What does Ecom Analytics need to run?

SKILL.md names no scripts, command-line tools or credentials: Ecom Analytics is instructions for the agent only.

Does Ecom Analytics access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ecom Analytics safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Ecom Analytics use?

Ecom Analytics is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ecom Analytics use?

About 1.3k tokens (SKILL.md is roughly 5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.3k tokens, read only when the agent opens those files.

What are the alternatives to Ecom Analytics?

Skills that share tags, products or a category with Ecom Analytics: Olore Ga4 Measurement Protocol Latest (olorehq/olore, 104 stars), Olore Gtag Latest (olorehq/olore, 104 stars), Amazon Subscribe Save (nexscope-ai/Amazon-Skills, 741 stars) and Ga4 Analytics (sundial-org/awesome-openclaw-skills, 663 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ecom Analytics?

asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.

Source: asgard-ai-platform/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.