PlaybookPrompts

Write SEO-optimised copy for an e-commerce category page

Marketing & SEO ecommerceseocopywriting

Category pages are the highest-traffic pages on most e-commerce sites, yet most have thin or no copy. This prompt generates structured, keyword-aware copy that satisfies both crawlers and shoppers without reading like it was written for a crawler.

Prompt
You are an e-commerce SEO copywriter. Write copy for a product category page with the following details:

- Category name: {{CATEGORY_NAME}}
- Primary keyword: {{PRIMARY_KEYWORD}}
- Secondary keywords to work in naturally: {{SECONDARY_KEYWORDS}}
- Products in this category (describe briefly): {{PRODUCT_TYPES}}
- Brand tone: {{BRAND_TONE}}
- Target customer: {{TARGET_CUSTOMER}}

1. Write an opening paragraph (60–90 words) that leads with the customer's goal, not the product. Include the primary keyword in the first sentence.
2. Write a 'What to look for' section with 3–4 short buying-guide tips. Each tip should be 2–3 sentences. Naturally include 1–2 secondary keywords across this section.
3. Write a closing paragraph (40–60 words) that reinforces why this category fits the customer's need and includes a soft call to action.
4. Suggest an H1 tag and a page title tag (under 60 characters) for this page.
5. Flag if the primary keyword has navigational intent (e.g. includes a brand name) that would make this copy approach less effective.

Avoid listing product specs — this is about the customer's decision context, not the inventory.
Variables to fill in
  • {{CATEGORY_NAME}}
  • {{PRIMARY_KEYWORD}}
  • {{SECONDARY_KEYWORDS}}
  • {{PRODUCT_TYPES}}
  • {{BRAND_TONE}}
  • {{TARGET_CUSTOMER}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{CATEGORY_NAME}}{{PRIMARY_KEYWORD}}{{SECONDARY_KEYWORDS}}{{PRODUCT_TYPES}}{{BRAND_TONE}}{{TARGET_CUSTOMER}}.
  3. Paste it into one of the recommended tools below.
  4. Iterate: tighten constraints in the prompt if the output is generic.

Why this prompt is structured this way

The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.

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Pair this prompt with a tool

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