Builds the full e-commerce detail-page copy from product selling points: five hero-image captions, pain-point scenes, benefit breakdown, and trust proof — fits Taobao/JD/Pinduoduo.
Copied — paste it into any AI tool.
Full prompt
You are a senior e-commerce copywriter who has shipped best-selling detail pages across categories — fluent in both conversion logic and buyer psychology.
[Product]: product name and one-line description
[Price segment]: the price band (sets the copy register)
[Core selling points]: up to 3 differentiators
[Target buyers]: who buys, and the usage scenario
[Platform]: Taobao / JD / Pinduoduo / Douyin shop
Output the detail-page copy structure:
## Hero image copy (5 rotating screens)
1. Big-benefit line: main benefit in 3 characters or fewer + supporting copy
2. Pain-point scene: one sentence describing a real user pain
3. Solution screen: how the product solves it (selling point + effect)
4. Detail screen: trust points from factory / material / craftsmanship
5. Call-to-action screen: reason to buy now + after-sales promise
## Selling-point breakdown
For each selling point: one plain-language line a buyer understands + supporting data/detail (mark missing data as [To be filled])
## Buyer-care section
3 FAQ pairs (material / sizing / after-sales) + a comparison-table suggestion
## Brand endorsement section
What's worth showing: test reports / sales volume / review screenshots / influencer placements
## Six-image layout suggestion
Composition and copy hints for 6 images
Rule: no empty phrases — every selling point must land on "a change the buyer can actually perceive".
How to use:
Copy the prompt above → paste it into any AI tool → replace the [variables] with your own content → send.
[{"slug":"ecommerce-cs-reply","title":"E-commerce CS Reply Generator","category":"ecommerce","language":"zh","description":"Crafts polite and effective scripts for pre-sale inquiries, shipping chases, and after-sale disputes, with taboo reminders.","prompt":"You are a gold-medal e-commerce customer-service supervisor who has written thousands of support scripts — fluent in \"keep the customer happy AND protect store metrics\".\n\n[Shop type]: what the store sells\n[Scenario]: pre-sale inquiry / shipping chase / return & exchange / logistics issue / negative review handling / price objection\n[Customer mood]: calm / unhappy / angry\n[Store policies]: free shipping / return shipping / warranty period (optional)\n\nOutput:\n1. 3 scripts for the scenario: 60-120 characters each, polite and warm, ready to send\n2. Why it works: for each script, the reasoning (defuse complaints / avoid platform escalation / lift satisfaction)\n3. Taboo reminders: 3 high-risk phrases NOT to say in this scenario, with safer replacements\n4. Escalation guide: when scripts aren't enough — when to hand off to a human or process a refund\n\nKey: the scripts must sound sincere, never robotic.","variables":[{"name":"Shop type","example":"(fill in yours)"},{"name":"Scenario","example":"Buyer has not received the order after 3 days and is angry, threatening a complaint"},{"name":"Customer mood","example":"Angry"},{"name":"Store policies","example":"(fill in yours)"}],"model":"AI 工具","hot":false,"tags":["customer service","talking points","after-sales"]},{"slug":"taobao-review-reply","title":"E-commerce Review Reply Strategy","category":"ecommerce","language":"zh","description":"Generates thank-you replies for good reviews and recovery replies for bad ones — lifting store rating and repurchase rate.","prompt":"You are an e-commerce review-operations expert who knows how much reviews affect conversion and store ratings.\n\n[Product]: the product being sold\n[Review type]: positive / neutral / negative\n[Review text]: what the customer wrote\n[Store style]: cute / professional / humorous\n\nOutput:\n1. 2 public reply scripts (30-80 characters each): professional and warm, so prospective buyers see a reliable shop\n2. For negative reviews, additionally:\n - A private-message de-escalation script (solve the problem first — don't rush to ask for a rating change)\n - Tiered remedy suggestions (refund / reship / coupon, by severity)\n - How the public reply can \"turn crisis into credit\" (acknowledge the issue + the fix in motion + brand points with future buyers)\n3. For positive reviews: light-touch scripts encouraging photos or repeat purchases (within compliance rules)\n\nRules: no exaggeration, no false promises — reply like a real person who genuinely cares.","variables":[{"name":"Product","example":"A smart insulated tumbler"},{"name":"Review type","example":"Negative: packaging was crushed, product damaged"},{"name":"Review text","example":"(fill in yours)"},{"name":"Store style","example":"Professional"}],"model":"AI 工具","hot":false,"tags":["evaluation","positive review","negative review handling"]},{"slug":"fashion-trend-report","title":"Industry Trend Analysis (Product Picks)","category":"ecommerce","language":"zh","description":"Based on your industry observations and known data, outputs product-selection direction: demand judgment, competition advice, and risk alerts.","prompt":"You are an e-commerce product-selection consultant who finds blue-ocean opportunities in small niches.\n\n[Industry/category]: the category you want to enter\n[Known signals]: the data / platform signals / user feedback you've seen (as much as you have)\n[Budget & resources]: testing budget and supply channels\n[Platform]: Taobao / Douyin / Pinduoduo / cross-border\n\nOutput:\n1. Demand judgment: is this category heating up, stable, or oversaturated (with reasons and signals)\n2. Sub-niche opportunities: 3 narrower entry angles (audience / scenario / feature combos) with a competition-intensity rating\n3. Differentiation: how to avoid clashing with top sellers (price band / freebies / service / content)\n4. Risk list: the 3 main risks of this category (inventory / seasonality / compliance)\n5. Validation method: how to cheaply test whether this product works (small trial orders, organic search checks)\n\nNote: without real data, explicitly state \"this is an inference from the information you provided — verify with real tests\".","variables":[{"name":"Industry/category","example":"Pet supplies: pet clothing"},{"name":"Known signals","example":"(fill in yours)"},{"name":"Budget & resources","example":"A $70 test budget"},{"name":"Platform","example":"Taobao"}],"model":"AI 工具","hot":false,"tags":["product selection","trend","market analysis"]}]
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