e commerce returns reduction planner

    1

    Reduces e-commerce return rates by converting return data into precise, validated listing and FAQ improvements.

    $5

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

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    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    e commerce returns reduction planner

    Example session with this skill installed

    I have 50 returns for my 'Titan-X Wireless Earbuds'. 35 say 'won't pair with my TV' and 15 say 'too bulky'. Here is the product link and the current FAQ. Give me a returns reduction plan.

    • Read your context and instructions
    • Compiled the e commerce returns

    I have analyzed the return data for the Titan-X Wireless Earbuds. The primary drivers are Bluetooth protocol misunderstandings and ergonomic fit issues.

    Returns Reduction Plan for Titan-X Wireless Earbuds

    1. Return Reason Summary

    • Connectivity / Pairing: High (70%) | Known Cause
    • Ergonomic Fit / Bulk: Medium (30%) | Known Cause

    2. Cause-to-Content Mapping

    Return CauseContent AreaKnown/AssumptionProposed Change
    TV Pairing IssuesCompatibilityKnownExplicitly list supported Bluetooth profiles (A2DP/AVRCP).
    Bulk/FitImagery NotesKnownAdd "In-Ear" scale photo with common reference object.
    TV Pairing IssuesFAQsKnownAdd step-by-step TV pairing guide for major brands.

    3. Detailed Content Recommendations

    Compatibility
    • Update technical specs: "Requires Bluetooth 5.0 or higher. Note: Not compatible with non-smart TVs lacking a dedicated Bluetooth transmitter."
    Imagery Notes
    • Add Graphic Overlay: "Dimensions: 24mm x 22mm. Designed for a secure seal; may feel larger than standard buds due to the 10mm drivers."
    • New Photo: A side-profile shot of the earbud in a medium-sized ear to show protrusion depth.
    FAQs & Support Wording
    • Q: Will these work with my television?

    A: Titan-X works with Smart TVs that support Bluetooth audio output. If your TV does not have built-in Bluetooth, a separate Bluetooth transmitter is required.

    4. Validation Checklist

    • All measurements provided in millimeters (metric).
    • Language uses "water-resistant" instead of "waterproof" to match IPX5 rating.
    • Amazon 200-character limit per bullet point respected.
    • Assumptions labeled; pairing data is verified by customer logs.

    Next steps

    1. Update the 'Technical Details' section on the product page with the specific Bluetooth profiles.
    2. Replace the third gallery image with the new scale-comparison photo.
    3. Add the pairing FAQ to the automated chatbot response flow.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    High return rates erode margins and damage marketplace seller ratings. Vague product descriptions and missing technical specs lead to customer mismatched expectations that only surface after the sale.

    What it does

    • Analyzes return codes, reviews, and support tickets to identify root causes of product returns.
    • Classifies findings into evidence-based "Known Causes" versus speculative "Assumptions" to ensure data integrity.
    • Maps specific return reasons to actionable content fixes across sizing, compatibility, care instructions, and imagery.
    • Generates ready-to-paste FAQ entries and listing bullet points using refund-safe, non-absolute language.
    • Validates all proposed changes against platform constraints and unit conversion requirements (metric/imperial).

    Why this beats prompting it yourself

    General prompts often suggest generic "better descriptions" without addressing the specific friction points that trigger a refund. This skill forces a rigorous classification of data, ensuring you don't rewrite your entire listing based on a single outlier comment while providing the exact measurements and policy-compliant language needed to actually move the needle.

    Use cases

    • Convert "too small" return feedback into precise, flat-lay measurement charts for apparel listings.
    • Draft technical compatibility warnings for electronics to stop "not compatible" returns.
    • Identify when product photography is misleading and write specific creative briefs for reshoots.
    • Audit existing FAQs to address common pre-purchase anxieties identified in support logs.

    Known limitations

    Requires raw return data or customer feedback to move beyond assumptions. Does not provide physical logistics or warehouse optimization advice.

    Requires raw return data or customer feedback to move beyond assumptions. Does not provide physical logistics or warehouse optimization advice.

    How to use

    1. 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. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 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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    Fresh listing

    Recently published to Agensi

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    Trust & safety

    Security scan

    Security scan passed 2 months ago

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    No special permissions declared or detected

    Listed2 months ago

    What's inside

    Frequently Asked Questions

    The planner analyzes your return codes and customer feedback to distinguish between random outliers and systemic product issues, providing specific, platform-compliant listing revisions to prevent future mismatches.

    You will receive the core logic for return data analysis, templates for classifying evidence-based listing improvements, and a framework for generating refund-safe FAQ content.

    To get the most accurate results, you should provide raw data from return reason codes, customer support transcripts, or product review exports.

    Yes, the skill is designed to output content that respects the constraints of major platforms like Amazon and Shopify, including metric-to-imperial conversions and non-absolute language requirements.

    This skill focuses exclusively on content and listing optimization; it does not handle physical logistics, warehouse management, or shipping label generation.

    New in E-commerce