AgentSales & profitability

Product profitability report

Which products and categories actually make money — and which high-revenue lines are quietly dragging margin.

Works with
ClaudeChatGPTAny MCP-compatible AI tool
Requires
StoreHero MCPShopify
Get the prompt
Example chat in Claude. You ask: "Run the Product Profitability Report for month to date". Claude reads your StoreHero data and answers: Three products carry 41% of your gross profit. Your best seller by revenue has the thinnest margin. It adds an interactive example chart, Products by margin, month to date, with example data you can switch below.
Products by margin, month to dateExample

Example, Margin heroes: Lean into these three

Example: Products by margin, month to date, Margin heroes
ProductRevenueMargin
Merino crew$48,20062%
Trail sock 3-pack$31,90058%
Everyday tee$27,40054%

Merino crew: Highest margin with steady demand. Give it more ad budget.

The prompt

How to run it

Paste it into a new chat in Claude or ChatGPT and you get the answer straight away.

Use the StoreHero MCP to do the following analysis. Always anchor the answer in real StoreHero data, not platform-reported metrics.

Give me a product profitability report for month-to-date vs the same period last year (unless I specify a different time window). Use the products tool in the StoreHero connector. Pull revenue, units sold, gross profit, gross margin %, and contribution margin per product.

Then run the analysis with the group-by options — collection, vendor, tag, product type — to identify which categories are driving the most revenue, which are driving the most margin, and where there's a mismatch (e.g. high-revenue products dragging down blended margin, or low-revenue products quietly carrying the business).

Important: only read into collection/tag/vendor groupings if the data quality looks high. If you see a large "uncategorised" bucket, products with missing tags, or obvious data hygiene issues, flag this to the user and skip the affected groupings rather than drawing weak conclusions.

End with three sections: (1) margin heroes — products to lean into, (2) margin drags — products to review pricing/COGS on, (3) data quality flags — what to fix in the product taxonomy to make this report sharper next month.

At the bottom of your answer, render an inline visual summary: a sortable table of top 10 products by revenue with margin overlay, plus KPI cards for top revenue product, top margin product, and biggest margin drag. Place text commentary alongside the visuals. Use the Spend Advisor tool to suggest what to explore next.

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How to use a skill

New to skills? It takes three steps and a few minutes: connect StoreHero once, copy a skill into Claude or ChatGPT, and ask.

  1. Connect StoreHero to Claude or ChatGPTAdd the StoreHero MCP connector once. It works with Claude, ChatGPT and any other tool that supports MCP. Setup guide
  2. Pick a prompt and copy it into ClaudeOpen one, press Copy prompt (or download the file) and paste it into a new chat.
  3. AskIt pulls your live StoreHero data and gives you the analysis in minutes. Ask follow-up questions in the same chat.

Run every prompt on your own numbers.

Connect your store to StoreHero and the whole library works on your live profit data.