{"uid":"cap_9LKOvXmYkdHan6CLxG0g8","slug":"marketing-contribution-return-iqr-outlier-flags-588fb7a6","name":"Marketing Contribution Return – IQR Outlier Flags","description":"Marketing contribution return - IQR outlier flags: Flag observations beyond 1.5 times the interquartile range; statistical flags are not errors or fraud findings. Metric: Marketing contribution return. Supplied figures only; returns JSON with formula, units and limitations. One of 50 calculators with 20 analysis modes. No live feed, financial advice or trade execution. 0.01 USDC includes one bounded iqr outlier flags report.","url":"https://market.datapackvibe.com/x402/assistant-finance-marketing-return-outliers?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["attributed_contribution","marketing_spend"],"properties":{"marketing_spend":{"type":"number","default":5000,"maximum":1000000000000,"minimum":0,"description":"Amount in a consistent supplied currency and reporting period","exclusiveMinimum":0},"attributed_contribution":{"type":"number","default":8000,"maximum":1000000000000,"minimum":-1000000000000,"description":"Amount in a consistent supplied currency and reporting period"}},"additionalProperties":false},"default":[{"marketing_spend":5000,"attributed_contribution":8000},{"marketing_spend":5500,"attributed_contribution":8800},{"marketing_spend":5000,"attributed_contribution":8000},{"marketing_spend":5500,"attributed_contribution":8800}],"maxItems":200,"minItems":2}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_Mj8tzwG2OBJzTjj3oStHU","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Flags observations in marketing contribution return data that fall beyond 1.5× the interquartile range, returning a JSON report with the statistical formula, units, and limitations.","exampleAgentPrompt":"Flag any IQR outliers in my marketing contribution return data — I have four rows: spend $5000/contribution $8000, spend $5500/contribution $8800, spend $5000/contribution $8000, and spend $5500/contribution $8800. Give me the outlier flags with the formula and units used.","exampleUseCases":[{"title":"Marketing campaign data quality check","prompt":"I have a batch of 10 marketing campaign records with their spend and attributed contribution figures — can you run IQR outlier detection on them and flag which rows fall outside 1.5 times the interquartile range? Here are the rows: spend $3000/contribution $4500, spend $5000/contribution $8000, spend $200/contribution $50000, spend $4800/contribution $7600, spend $5100/contribution $8200, spend $4900/contribution $7900, spend $5200/contribution $8300, spend $5000/contribution $8100, spend $4950/contribution $7800, spend $5050/contribution $8050."},{"title":"Analyst pre-reporting outlier review","prompt":"Before I finalize my quarterly marketing report, flag any statistical outliers in these contribution return rows using IQR — I want to know which observations go beyond 1.5x the IQR so I can note them: spend $10000/contribution $15000, spend $10500/contribution $16000, spend $9800/contribution $14800, spend $10200/contribution $15200, spend $500/contribution $100."},{"title":"Automated marketing data pipeline anomaly detection","prompt":"As part of my weekly marketing data pipeline, scan these six rows of marketing spend and attributed contribution for IQR-based outlier flags and return the formula and limitations in the result: spend $7000/contribution $11000, spend $7200/contribution $11400, spend $6900/contribution $10800, spend $7100/contribution $11200, spend $7050/contribution $11100, spend $100/contribution $95000."}],"resultDescription":"A JSON object containing outlier flag status for each submitted row (indicating whether the observation falls beyond 1.5× the IQR), plus the statistical formula used, units, and limitations of the analysis.","failureModes":["Fewer than 2 rows submitted — minimum input not met","marketing_spend is zero or negative — exclusiveMinimum constraint violated","Row count exceeds 200 — maxItems limit breached","Missing required fields (marketing_spend or attributed_contribution) in one or more rows","Values outside allowed numeric range (±1,000,000,000,000) rejected","Malformed JSON body returns validation error"],"whenToPreferThis":"Choose this endpoint when you need fast, bounded IQR-based outlier flagging specifically on marketing contribution return data (spend vs. attributed contribution pairs) and want the formula, units, and limitations documented in the response. It is not a fraud-detection or financial-advice tool — use it for statistical data quality review of up to 200 marketing records per call at low cost ($0.01 USDC).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:39.644Z","isFirstParty":false,"canonicalSlug":"marketing-contribution-return-iqr-outlier-flags-588fb7a6"}