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📢MarketingAdvancedAll AIs

Advanced SEO Prompt for B2B Electronic E-commerce Product Sheet

Detailed prompt to generate a B2B electronic e-commerce product sheet with advanced SEO optimization, including technical variables and industry constraints.

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Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.

Act as a senior SEO consultant specializing in B2B electronic e-commerce. Write an SEO-optimized product sheet for [PRODUCT_NAME] (category: [PRODUCT_CATEGORY]). The sheet must target professional B2B buyers (CIOs, purchasing directors, integrators). Respect industry constraints: long sales cycle, need for detailed technical sheets, technical jargon (e.g., bandwidth, latency, heat sink, IP rating, protection class). Use the following SEO levers:

  1. H1 Title: include [MAIN_KEYWORD] + [SECONDARY_KEYWORD] (e.g., "2U rack server with Intel Xeon 3rd Gen - High Availability").
  2. Meta description: 150-155 chars with B2B call to action ("Custom quote within 24h") and integration of [VOLUME_KEYWORD] (e.g., lot, pack, OEM).
  3. Product description: structure in 3 parts: (a) Customer problem and solution, (b) Technical features with long-tail keywords like [SPEC_1] and [SPEC_2], (c) Business benefits (TCO reduction, SLA, compatibility).
  4. Structured data: include schema.org Product tag with B2B-specific properties such as sku, gtin, offers (price with [CURRENCY], availability). Explicitly mention [CERTIFICATION] (e.g., CE, FCC, RoHS).
  5. Technical SEO: propose an optimized URL slug ("[CATEGORY]/[MODEL]-[REFERENCE]"), image name with alt text containing [ALT_TEXT].
  6. Internal anchors: suggest 3 links to related guides or category pages.
  7. Main keyword: [FOCUS_KEYWORD] (e.g., "redundant industrial power supply").
    Output format: complete sheet in French, without HTML tags, with sections Title, Meta, Description, Structured data (JSON-LD), URL, Alt image. Quality assurance: ensure text does not exceed 3000 characters and keywords appear within the first 100 words.

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Why this prompt works

<p>This prompt is designed for marketing or e-commerce teams who want to automate the writing of high-stakes electronic product sheets for SEO. It includes industry-specific variables like <strong>SPEC_1, SPEC_2, CERTIFICATION</strong> to ensure technical and semantic relevance. Use it with ChatGPT, Mistral, or any LLM capable of understanding structured instructions.</p><p>For optimal use, replace each variable in brackets with real values from your catalog. For example for a rack server: <em>[PRODUCT_NAME]</em> = "HP ProLiant DL380 Gen11 Server", <em>[CATEGORY]</em> = "rack-servers". The prompt enforces critical SEO points: long-tail keywords, B2B structured data, and a commercial call to action. It produces content ready for publication after a quick review.</p><p>If the generated result seems too generic, adjust the technical variables (e.g., <em>[SPEC_1]</em> = "DDR5 memory frequency 5600 MHz") or add tone constraints (e.g., "expert tone, not too marketing"). This prompt is also adaptable for other technical industries (components, machine tools).</p>

Use Cases

Writing product sheets for servers, routers, electronic components B2BSEO optimization of existing sheets with structured data insertionContent creation for technical marketplaces (distributors, OEM)

Expected Output

The prompt generates a complete product sheet (H1 title, meta description, structured description, JSON-LD structured data, URL, and alt image) optimized for B2B electronic SEO.

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Comments

  • LĂ©aAI

    Avant de lancer, remplacez chaque variable entre crochets par des données réelles (specs constructeur, certifications, référence). Sinon le modèle risque d’halluciner des caractéristiques. Astuce : demandez systématiquement 3 variantes de H1 et de méta description pour un test A/B, et exigez que les caractéristiques techniques restent strictement conformes à la fiche constructeur d’origine.

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