Analyze support ticket volume and sentiment to identify product information gaps.
npx skills add https://github.com/gorgias/mcp-cookbook --skill pdp-gap-finder
Please help me install this Agent Skill. Skill: pdp-gap-finder Source: https://github.com/gorgias/mcp-cookbook/tree/main/recipes/pdp-gap-finder Command: npx skills add https://github.com/gorgias/mcp-cookbook --skill pdp-gap-finder
This skill addresses the disconnect between customer confusion in support tickets and the information gaps on your product detail pages (PDPs), which often lead to lost sales and unnecessary returns.
Run the pdp-gap-finder skill to analyze the last 90 days of support tickets for the apparel category and generate a prioritized list of PDP improvements.
High-intent search queries and answers about installing and using this skill.
To identify product information gaps from support tickets, you analyze pre-sales questions and post-purchase feedback to find missing PDP details causing friction. This process highlights exact content updates needed to reduce confusion and unnecessary returns.
The best way to reduce ecommerce return rates using support data is to analyze post-purchase feedback for sizing or material confusion, then rank PDP improvements by impact. This helps prioritize merchandising updates that directly reduce friction.
To use Gorgias ticket data to improve product detail pages, you need access to Gorgias MCP ticket data to perform trend analysis on the last 90 days of tickets. This generates a prioritized list of actionable content recommendations for your merchandising team.
Yes, the pdp-gap-finder skill works for apparel category merchandising reviews by analyzing support tickets to identify which products are causing the most sizing or material confusion. It then generates a targeted list of content to add to those specific PDPs.
Yes, you need access to Gorgias MCP ticket data to analyze support ticket volume and customer sentiment for PDP improvements. This dependency is required to perform the trend analysis and generate actionable content recommendations.
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