Expected output
The deliverable should include Sales bridge, Driver decomposition, Anomalous SKUs and channels, Opportunities and risks, and Next analysis steps.
IntermediateData, Profit & Decision AI
Sales Analysis | Diagnostic Analysis Prompt
Sales Analysis | Diagnostic Analysis Prompt is a copyable AI prompt for ecommerce sellers. Use it to explain sales movement through traffic, conversion, price, mix, inventory, and returns from verified business inputs. Copy the full instruction, add your inputs and check the result before use.
- Views
- 0
- Uses
- 0
- Favorites
- 0
How the Sales Analysis | Diagnostic Analysis Prompt works
Explain sales movement through traffic, conversion, price, mix, inventory, and returns from verified business inputs. The prompt identifies data gaps first, ranks findings by evidence strength, and ends with phased actions that require human review.
Key instructions and output
The points below describe the task and expected output in this prompt.
Parameter guide
Prepare the task information listed below and replace placeholders with verified details from the actual case.
[Order detail]
Replace this placeholder with verified, task-specific information before running the prompt.
[Traffic and conversion]
Replace this placeholder with verified, task-specific information before running the prompt.
[Price and discount]
Replace this placeholder with verified, task-specific information before running the prompt.
[Inventory]
Replace this placeholder with verified, task-specific information before running the prompt.
[Returns and channels]
Replace this placeholder with verified, task-specific information before running the prompt.
Copy the complete prompt
The complete source is shown below. Copy it from the top right to use it.
You are an ecommerce business analyst. Your objective is to explain sales movement through traffic, conversion, price, mix, inventory, and returns. Analyze the following real inputs: [Order detail], [Traffic and conversion], [Price and discount], [Inventory], [Returns and channels]. First list data gaps and definitions that need confirmation. When information is missing, mark it as 'To be confirmed' rather than guessing. Then provide: (1) key findings and supporting evidence; (2) prioritized root causes or opportunities using impact × evidence strength; (3) Sales bridge, Driver decomposition, Anomalous SKUs and channels, Opportunities and risks, Next analysis steps; (4) executable actions for the next 7, 30, and 90 days; and (5) risks, counterexamples, and assumptions requiring human validation. Special requirement: Do not interpret simultaneous movement as causation. Flag promotions, stockouts, and definition changes.Test this prompt on a real task
Copy a starter instruction, add the required inputs, then run one example and review the output.
01Sales Analysis | Diagnostic Analysis Prompt
The deliverable should include Sales bridge, Driver decomposition, Anomalous SKUs and channels, Opportunities and risks, and Next analysis steps. Diagnose sales analysis issues and prioritize evidence-backed action
Show prompt and variablesHide prompt and variables
Sales Analysis | Diagnostic Analysis Prompt
The deliverable should include Sales bridge, Driver decomposition, Anomalous SKUs and channels, Opportunities and risks, and Next analysis steps. Diagnose sales analysis issues and prioritize evidence-backed action
You are an ecommerce business analyst. Your objective is to explain sales movement through traffic, conversion, price, mix, inventory, and returns. Analyze the following real inputs: [Order detail], [Traffic and conversion], [Price and discount], [Inventory], [Returns and channels]. First list data gaps and definitions that need confirmation. When information is missing, mark it as 'To be confirmed' rather than guessing. Then provide: (1) key findings and supporting evidence; (2) prioritized root causes or opportunities using impact × evidence strength; (3) Sales bridge, Driver decomposition, Anomalous SKUs and channels, Opportunities and risks, Next analysis steps; (4) executable actions for the next 7, 30, and 90 days; and (5) risks, counterexamples, and assumptions requiring human validation. Special requirement: Do not interpret simultaneous movement as causation. Flag promotions, stockouts, and definition changes.Inputs to replace in this prompt
[Order detail]- Replace this placeholder with verified, task-specific information before running the prompt.
[Traffic and conversion]- Replace this placeholder with verified, task-specific information before running the prompt.
[Price and discount]- Replace this placeholder with verified, task-specific information before running the prompt.
[Inventory]- Replace this placeholder with verified, task-specific information before running the prompt.
[Returns and channels]- Replace this placeholder with verified, task-specific information before running the prompt.
What to check before using the output
The generated result is a draft; check claims, numbers and operating conditions against source data before publishing, importing or acting on it.
Operating note 1
Replace every placeholder before running the prompt, and label key figures with their source, date range, and definition.
Operating note 2
Do not interpret simultaneous movement as causation. Flag promotions, stockouts, and definition changes.
Operating note 3
Before uploading order, customer, contract, or supplier data, redact sensitive information and comply with platform terms, privacy policies, NDAs, and company data-governance requirements. Have the responsible operator review the result before it is published, sent, or executed.
Source & attribution
Compilation note and reference material
This section identifies the prompt’s creator and source, and marks details that could not be verified.
Vendolune
This Prompt was compiled by Vendolune from the scenario requirements and public reference material. The reference-page author is not credited as this Prompt's author.
Reference materialGraas
This link is reference material and does not establish its page author as the author of this Prompt. The article offers prompts for ecommerce data analysis and recommends starting with an overall diagnosis before narrowing into products, channels, cohorts, and time periods.
The original page does not publish a rating, review, Product Hunt upvote, star, fork, install, or download count.
Content checked:
No reviews yet.