{"uid":"cap_uBCL96wJq1T5xjq_ZJlGm","slug":"brand-mention-inventories-string-normalisation-two-measure-correlation-a743758c","name":"Brand Mention Inventories — String Normalisation + Two-Measure Correlation","description":"Brand mention inventories — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied brand mention inventories records (mention_count, source_count). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-company-18-033?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","mention_count","source_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"mention_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_count":1,"company_group":"group-a","mention_count":10},{"date":"2026-10-02","row_id":"row-2","source_count":2,"company_group":"group-b","mention_count":20},{"date":"2026-10-03","row_id":"row-3","source_count":3,"company_group":"group-a","mention_count":15},{"date":"2026-10-04","row_id":"row-4","source_count":4,"company_group":"group-b","mention_count":30}],"maxItems":200,"minItems":1}}},"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_hknT0JW5l7HUrcGJZoxYi","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":"Normalises strings and computes two-measure correlation (mention_count vs source_count) for up to 200 rows of brand mention inventory data, producing 2 independent analytical reports.","exampleAgentPrompt":"Can you run string normalisation and a two-measure correlation on this brand mention data — I have up to 50 rows with columns for row_id, company_group, date, mention_count, and source_count — and give me 2 analytical reports?","exampleUseCases":[{"title":"Cross-brand mention vs source correlation","prompt":"I have 80 rows of brand mention inventory data with company groups 'Acme', 'Globex', and 'Initech', dated from 2025-01-01 to 2025-03-31, each with a mention_count and source_count. Can you normalise the strings and run a two-measure correlation to see if more sources mean more mentions, and give me 2 reports?"},{"title":"Weekly brand tracking report for one group","prompt":"Here are 30 rows of weekly brand mention records for 'BrandAlpha' from 2024-06-01 to 2024-12-30, with mention_count and source_count filled in. Can you clean up the strings and correlate mention volume against source diversity, producing two separate analytical summaries?"},{"title":"Multi-group competitive brand analysis","prompt":"I've got 150 rows covering four competitor brands — 'NovaCorp', 'PeakBrand', 'TerraMedia', and 'SwiftLabel' — all dated between 2025-07-01 and 2025-09-30, with mention_count and source_count per row. Please normalise the company group strings and run the two-measure correlation analysis with 2 reports."}],"resultDescription":"Returns 2 independent analytical reports covering: (1) string-normalised brand mention inventory records, and (2) a two-measure correlation analysis between mention_count and source_count across the supplied rows (up to 200). No external data is fetched; all computation is local.","failureModes":["Fewer than 1 or more than 200 rows supplied — request rejected","Missing required fields (row_id, company_group, date, mention_count, source_count) — validation error","Date field not matching YYYY-MM-DD pattern — schema validation failure","Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejection","All null values for mention_count or source_count — correlation cannot be computed"],"whenToPreferThis":"Choose this endpoint when you have brand mention inventory data (mention_count + source_count) for up to 200 rows across one or more company groups and need both string normalisation and a statistical two-measure correlation in a single low-cost call. Prefer it over general-purpose analytics services when you want a lightweight, no-external-lookup, paid-per-call computation with two bundled reports at $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T12:44:23.631Z","isFirstParty":false,"canonicalSlug":"brand-mention-inventories-string-normalisation-two-measure-correlation-a743758c"}