Customer Return Multi-Dimensional Analysis Report Skill with 7-Dimension Structured Analysis

Customer Return Data a Mess? This Skill Can Help You Get It Organized

Friends who work in quality management should all know that analyzing customer return data is a headache-inducing taskThe reasons for returns are all over the placedata is scattered across various spreadsheetsand every time you want to put together a reportit takes half a day or moreTodayI want to recommend a skill specifically designed to solve this problem—the Multi-Dimensional Customer Return Analysis ReportIt can automatically break down your customer return data into 7 dimensions and generate a clearly structured analysis reportIt's absolutely amazing!

So what exactly does this skill do? In simple termsall you need to do is feed it your customer return dataand it will automatically analyze the overall overview of returnsacceptance reasonsretest resultsdefect causesdefective materialsresponsibility attributionand handling statusFinallyit will also provide core conclusions and recommendationsWhat's moreit has a very user-friendly design: it answers exactly what you askFor exampleif you only want to look at "handling status," it will only output the analysis of handling statusrather than dumping a pile of useless information on youThis is really thoughtful.

7 Dimensions That Break Down Return Issues with Perfect Clarity

Let's take a closer look at what these 7 dimensions include:

• Overall Overview: Product nameproduction plantrepair plantreturn quantityretest completion raterework completion rate—see the full picture at a glance.
• Acceptance Reason Analysis: Summarized by four categories—quality-related7-day no-reasonpaid exchangeand others—with detailed reasons visible under each category.
• Retest Result Analysis: Displays the TOP 5 retest resultswith the rest grouped under "Others," so key issues are immediately visible.
• Defect Cause Analysis: Also displayed as TOP 5helping you pinpoint the main failure causes.
• Defective Material Analysis: See which materials are most prone to problems.
• Responsibility Attribution Analysis: TOP 10 ranking of responsible partiesso you always know who is accountable.
• Handling Status Analysis: Quantities and percentages for each handling statusmaking it easy to see if progress is lagging behind.

To be honestthese 7 dimensions basically cover all the pain points of customer return analysisWhether you're looking for quality issues or trying to assign accountabilityyou'll find the answers here.

Easy to UseBut Pay Attention to a Few Details

Installing this skill is simpleFirstmake sure you have Node.js on your computerthen run the following command:

npx skills add https://github.com/youyouguoke/quality-agent --skill return-analysis

Once installedyou can use it in supported clients (such as )Howeverthere are a few details to keep in mind when using it:

• If you ask for a "comprehensive analysis" or "customer return report," it will output all 8 sections (including core conclusions and recommendations)If you only ask about a specific dimension—for example"How many returns are there?"—it will only output the overall overview and nothing elseSo be precise with your questions.
• For single-dimension outputthe title does not include a numberFor exampleit will simply say "Handling Status Analysis," not "7Handling Status Analysis." You'll need to get used to that.
• In terms of data processingthe defect cause and defective material fields may contain multiple values separated by commasThe skill will automatically perform multi-value splitting for statistics—very smart.
• Empty values are excludedand only records with retest results are countedwhich ensures the calculated retest completion rate is accurate.

Built-in Domain Knowledge Saves You from Calculation Headaches

What surprised me most is that this skill has built-in calculation rules from the domainFor examplethe retest completion rate = (retested + pending rework + reworked + completed) / total returnsand the rework completion rate = (reworked + completed) / total returnsYou don't have to calculate these formulas yourselfMoreoverthe classification rules for acceptance reasons are also pre-configured: things like "platform merchant - quality" and "exchange within warranty period" are classified under quality-relatedwhile "7-day no-reason return" goes under the 7-day no-reason categoryIt's very clear.

Additionallyit provides core conclusions and recommendations at the end of the reportcomparing against baseline standards to give a normal/warning/severe judgmentFor those who need to report to leadershipthis is a lifesaver—it saves you the effort of summarizing and analyzing on your own.

Real-World Usage Experience

I tried it myself and found that the output format is very standardizedthe tables are clearand all the percentages are pre-calculatedThe responsibility attribution analysis in particular can list the TOP 10 responsible partieswhich is especially useful for driving supplier improvementThe only thing I'd like to remind you of is that this skill needs to work with MCP tools to retrieve dataso you need to make sure your data source is configured correctly; otherwiseyou might not be able to get the data.

Overallif you frequently need to do customer return analysisthis skill can really save you a massive amount of timePlusthe analysis dimensions are comprehensiveand you can use it directly out of the boxI strongly recommend it to colleagues in quality management and after-sales analysisOnce you use ityou'll know just how great it is! 😄