Checks return eligibility and routes outcomes
The source instruction checks policy eligibility, distinguishes final-sale and item-condition cases, then routes the request to refund, store credit, exchange, or escalation.
BeginnerChatGPT GPTs
Weekly Ecommerce Performance Analyst
Weekly Ecommerce Performance Analyst is an ecommerce AI skill for ChatGPT GPTs, built for teams working with Shopify, WooCommerce, Amazon. Use it to decide the next…
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System Prompt Original link: no public source found
What this Skill does
You need operating data to decide the next budget, product, or channel investment. The first decision to test is whether Weekly team meeting report and Investor update preparation hold up together before letting the team review and allocate resources on the same basis. Start with a small test around “Weekly team meeting report”, then check whether “Investor update preparation” fits the way your team actually works.
What makes it different
Breaks down a competitor page by operating dimension
The instruction separates positioning, pricing, conversion tactics, user experience, and search content instead of returning one undifferentiated summary.
Uses inventory signals for operating decisions
The source works with stock, demand, or reorder information to identify what should be replenished, monitored, or investigated.
Before you use it
Source file or structured data
This instruction refers to file or tabular input. Prepare the requested file and confirm that the model you use can read it.
No installation needed
Copy and paste into a model chat
- Expand and copy the complete original Skill.md below.
- Open a new conversation in a compatible AI model, then paste it into the chat box.
- Add verified task details, run one low-risk example, and review the result before using it in store operations.
Original Skill.md
The complete source is shown below. Copy it from the top right to use it.
You are an ecommerce performance analyst. When given weekly store data, generate:
1. EXECUTIVE SUMMARY (3 bullet points):
- Top-line: Revenue vs last week (%, $)
- Traffic: Sessions, conversion rate, AOV trends
- Alert: Any metric outside normal range
2. WIN/LOSS ANALYSIS:
- Top 3 winning products (by revenue growth)
- Top 3 declining products
- Top 3 traffic sources (by conversion quality)
3. CUSTOMER INSIGHTS:
- New vs returning customer split
- Average order value trend
- Customer acquisition cost estimate
4. INVENTORY ALERT:
- Products at risk of stockout (< 2 weeks)
- Overstock items (> 90 days)
5. RECOMMENDATIONS (prioritized):
- 1 immediate action (do today)
- 2 short-term actions (this week)
- 1 strategic initiative (this month)
6. COMPETITIVE PULSE:
- Any notable competitor activity or pricing changes
- Industry benchmark comparison
Format as a clean, boardroom-ready report. Include % changes, not just absolute numbers. Flag anything red (>20% negative change) with 🚨.Get started
Starter prompts for the main use cases—copy and use them directly.
01Start with one real task
Do not begin with a store-wide rollout. Pick one reversible task where Weekly Ecommerce Performance Analyst can help you turn store, pricing, and performance data into operating decisions. Use this when the input boundary, owner, and one primary measure from data completeness, calculation accuracy, contribution margin, and decision follow-through are written down.
Show prompt and variablesHide prompt and variables
Start with one real task
Do not begin with a store-wide rollout. Pick one reversible task where Weekly Ecommerce Performance Analyst can help you turn store, pricing, and performance data into operating decisions. Use this when the input boundary, owner, and one primary measure from data completeness, calculation accuracy, contribution margin, and decision follow-through are written down.
Use the Skill above to help me with this task: Start with one real task.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Do not begin with a store-wide rollout. Pick one reversible task where Weekly Ecommerce Performance Analyst can help you turn store, pricing, and performance data into operating decisions.
Return a practical result and clearly flag anything that needs human review.Replace these variables
[TASK_DETAILS]- The facts, context, or source material for this task.
[CONSTRAINTS]- Replace this placeholder with your verified store-specific information.
02Prepare the input and guardrails
Collect only the consistent exports, metric definitions, cost data, date ranges, and known data gaps needed for this test. Remove unrelated personal data and state which actions must never run automatically. Use this when every input has a known source, sensitive fields are minimized, and the approver knows what the trial can read or change.
Show prompt and variablesHide prompt and variables
Prepare the input and guardrails
Collect only the consistent exports, metric definitions, cost data, date ranges, and known data gaps needed for this test. Remove unrelated personal data and state which actions must never run automatically. Use this when every input has a known source, sensitive fields are minimized, and the approver knows what the trial can read or change.
Use the Skill above to help me with this task: Prepare the input and guardrails.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Collect only the consistent exports, metric definitions, cost data, date ranges, and known data gaps needed for this test. Remove unrelated personal data and state which actions must never run automatically.
Return a practical result and clearly flag anything that needs human review.Replace these variables
[TASK_DETAILS]- The facts, context, or source material for this task.
[CONSTRAINTS]- Replace this placeholder with your verified store-specific information.
03Inspect the source Skill, then run it
Read the source, installation method, and permission notes before adding Weekly Ecommerce Performance Analyst to a separate test project. Keep commands and Skill text exactly as published. Use this when you have a decision-ready analysis that a responsible operator can inspect, and it stayed inside the approved boundary.
Show prompt and variablesHide prompt and variables
Inspect the source Skill, then run it
Read the source, installation method, and permission notes before adding Weekly Ecommerce Performance Analyst to a separate test project. Keep commands and Skill text exactly as published. Use this when you have a decision-ready analysis that a responsible operator can inspect, and it stayed inside the approved boundary.
Use the Skill above to help me with this task: Inspect the source Skill, then run it.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Read the source, installation method, and permission notes before adding Weekly Ecommerce Performance Analyst to a separate test project. Keep commands and Skill text exactly as published.
Return a practical result and clearly flag anything that needs human review.Replace these variables
[TASK_DETAILS]- The facts, context, or source material for this task.
[CONSTRAINTS]- Replace this placeholder with your verified store-specific information.
04Review it against a baseline
Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time. Use this when data completeness, calculation accuracy, contribution margin, and decision follow-through has a pre-test baseline, and errors and exceptions are logged separately.
Show prompt and variablesHide prompt and variables
Review it against a baseline
Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time. Use this when data completeness, calculation accuracy, contribution margin, and decision follow-through has a pre-test baseline, and errors and exceptions are logged separately.
Use the Skill above to help me with this task: Review it against a baseline.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time.
Return a practical result and clearly flag anything that needs human review.Replace these variables
[TASK_DETAILS]- The facts, context, or source material for this task.
[CONSTRAINTS]- Replace this placeholder with your verified store-specific information.
Risks and operating notes
Use the current return policy, not the example rule
The instruction includes example eligibility and resolution paths. Replace its time window, final-sale handling, refund, exchange, and store-credit rules with the policy that is currently approved for your store.
A chat instruction does not update inventory
If the instruction mentions inventory, treat that as an operational step to verify. A pasted Skill cannot change stock records unless a separately configured and approved integration performs that action.
Use the minimum customer data needed
The workflow may need an order reference or case facts. Do not paste payment details, full addresses, or unrelated order history into a model conversation; redact them unless they are essential to the decision.
Verify commercial terms before acting
Any price, discount, cost, or margin recommendation is only as current as the values you provide. Recheck live prices, tax, shipping, and margin rules before publishing or sending an offer.
Network-collected; original author unavailable.
The complete available Skill content is cataloged and reviewed; public web material does not currently name the original author. Attribution does not affect its directory visibility or content-based recommendation eligibility.
Network-collected; no author source is listed. This label describes attribution only, not capability, visibility, or recommendation eligibility.
Risk, permissions, and limitations
Review third-party permission scopes before providing store data. Never paste payment credentials, customer passwords, or unnecessary personal data into a model. Outputs must be checked by the operator responsible for the workflow.
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