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Build a back-in-stock demand list from customers who asked about out-of-stock or discontinued products — ranked by demand, with a per-product notify list — to drive back-in-stock campaigns and inform the next buy. Read-only.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | restock-demand-list |
| description | Build a back-in-stock demand list from customers who asked about out-of-stock or discontinued products — ranked by demand, with a per-product notify list — to drive back-in-stock campaigns and inform the next buy. Read-only. |
Every "when is this coming back?" ticket is a pre-qualified sale waiting on inventory. Most of that demand evaporates because nobody captures it. This recipe aggregates restock requests by product, so you can size real demand, build a back-in-stock notify list per product, and hand merch a hard signal for the next buy. Read-only.
| Variable | Example |
|---|---|
{{WINDOW}} | "the last 90 days" |
{{TOP_N}} | "the top 15 products by demand" |
Using the Gorgias MCP, build a restock demand list from my support data over {{WINDOW}}.
- Find tickets and conversations asking about out-of-stock, sold-out, discontinued, or "when will this be back" products.
- Group by product and rank by number of distinct requesters — that's your demand signal. Show the top {{TOP_N}}.
- For each product, return an export-ready notify list (email, first name) of the customers who asked.
- Flag the products with demand far above the rest — those are the ones to prioritize restocking, not just notifying.
Nothing in Gorgias — read-only. It produces per-product customer lists for you to load into back-in-stock flows. Handle like any customer export.
returns-reduction so you don't reorder a high-return product.Build a targeted win-back segment from support signal — customers who hit a problem, left low CSAT, or went quiet after a bad experience — as a list you can hand to your email/SMS tool. The most qualified re-engagement audience you have is in your tickets. Read-only.
Turn the last 7 days of Gorgias tickets into an executive-ready weekly CX digest — analyzed across five business functions (Product, Marketing, Ecommerce/Revenue, Product Marketing, Leadership) with a TLDR, signal-status tagging, a PDP-gap table, and owner-tagged actions. Read-only; optionally publishes to Notion.
Turn recurring customer language, objections, and praise from tickets into marketing angles, FAQ content, and on-site or ad copy — written in your customers' own words. The best copy you'll write is already in your inbox. Read-only.
Find the products generating the most pre-sales questions and post-purchase confusion, and get a concrete list of what to add to each product page. Turns support tickets into PDP improvements that lift conversion and cut returns. Read-only.
Cluster why customers actually return products — sizing, quality, expectation gaps — by product, from ticket and return language, so you can fix the root cause instead of just processing the refund. Returns are a margin killer; this finds where they start. Read-only.
Analyze how your Shopping Assistant is performing as a revenue channel — most recommended products, best-converting recommendation pairs, revenue and time-to-purchase per conversation, and the pre-sales topics and handover reasons behind it. Read-only. Analytics are in beta — directional.