customer review product optimizer
Transform raw customer reviews into high-converting listing copy, ad angles, and a prioritized product backlog.
$5
Works with the AI Agents you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+21 moreClaude CodeCursorCodex CLIMuseDots
Manus
Grok
Grok Bot+18 agentscustomer review product optimizer
Example session with this skill installed
Analyze these 5-star and 2-star reviews for our ergonomic office chair. Customers love the lumbar support but hate the assembly instructions. Suggest listing fixes and a prioritized backlog.
- Read your context and instructions
- Compiled the customer review product
I have analyzed the feedback patterns for the ergonomic office chair. The primary conflict exists between high satisfaction with physical support and significant friction during the initial setup phase.
Customer Review Optimization
| Theme | Category | Evidence/Buyer Language | Actionable Fix |
|---|---|---|---|
| Lumbar Relief | Praise | "Finally, my lower back doesn't ache after 8 hours." | Move "8-hour lumbar relief" to the main hero image copy. |
| Assembly Friction | Expectation | "Instructions look like a blurry photocopy," "Part B and C look identical." | Add a "10-Minute Visual Setup Guide" PDF to the listing. |
| Build Quality | Praise | "Heavy duty," "Feels like a $500 chair." | Highlight "Heavy-duty steel base" in bullet points. |
| Tooling Issues | Support | "Included Allen wrench stripped immediately." | Recommend upgrading the hardware kit quality. |
Buyer Language Bank
- "Lower back doesn't ache after 8 hours"
- "Feels like a $500 chair"
- "Solid, heavy-duty build"
Prioritized Product Backlog
High Impact / Low Effort: Replace current assembly manual with high-resolution, labeled diagrams. Add a video walkthrough to the listing.
2.
Medium Impact / Medium Effort: Re-label Parts B and C with physical stickers to prevent orientation errors during assembly.
3. High Impact / High Effort: Source higher-grade hardened steel assembly tools to prevent stripping reports.
Next steps
- Update the second image in your carousel to highlight the lumbar support using the "8-hour" customer quote.
- Print a QR code on the box linking to a video assembly tutorial to preempt negative reviews.
Connects securely to your tools. The creator never sees your data.
About this skill
Stop guessing what your customers want and start using their own words to sell to them. This skill transforms raw customer reviews, support tickets, and feedback patterns into a structured growth engine for marketplace listings and product development.
What it does
- Sentiment extraction categorizes praise, friction, expectation mismatches, and feature requests.
- Language mapping identifies recurring buyer phrases to use in copy without inventing fake quotes.
- Copy optimization generates listing improvements and advertising angles based on proven customer triggers.
- Support reduction creates FAQ sets that address specific, recurring points of confusion.
- Backlog prioritization ranks product fixes by evidence, recurrence, impact, and estimated effort.
How it works
- Analyze input: Processes review text, patterns, and product context provided by the user.
- Thematic synthesis: Separates product defects from expectation-setting problems.
- Translation: Converts themes into specific marketing assets like ad angles and listing fixes.
- Action planning: Builds a prioritized backlog of product or onboarding improvements.
Frameworks & tools
This tool works with any text-based customer feedback data from platforms like Amazon, Shopify, Etsy, or Zendesk. It outputs standard Markdown tables and lists compatible with project management tools.
Why this beats prompting it yourself
Generic prompts often hallucinate customer quotes or fail to distinguish between a broken product and a bad product description. This skill enforces strict quality rules to separate evidence from inference, ensuring every marketing claim is grounded in actual user data.
Use cases
- Listing overhauls for Amazon or Shopify products suffering from high return rates.
- Ad creative briefs based on the specific benefits customers praise most often.
- Product roadmap planning using evidence-based friction themes from real users.
- Onboarding optimization to fix preventable confusion in the customer journey.
Known limitations
Requires sufficient review volume or feedback patterns to provide meaningful insights. Effectiveness depends on the quality of the input review text provided.
Requires sufficient review volume or feedback patterns to provide meaningful insights. Effectiveness depends on the quality of the input review text provided.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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