{"uid":"cap_nqEYK5gXwrV9BJLo3AQ14","slug":"customer-segment-observations-string-normalisation-daily-sum-series-82a205f1","name":"Customer Segment Observations — String Normalisation + Daily Sum Series","description":"Customer segment observations — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied customer segment observations records (account_count, revenue_amount). 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-16-027?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","account_count","revenue_amount"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"account_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"revenue_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","account_count":10,"company_group":"group-a","revenue_amount":1},{"date":"2026-10-02","row_id":"row-2","account_count":20,"company_group":"group-b","revenue_amount":2},{"date":"2026-10-03","row_id":"row-3","account_count":15,"company_group":"group-a","revenue_amount":3},{"date":"2026-10-04","row_id":"row-4","account_count":30,"company_group":"group-b","revenue_amount":4}],"maxItems":200,"minItems":1},"field":{"enum":["account_count","revenue_amount"],"type":"string","default":"account_count"}}},"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_D1Fo_61LA5tRnsygev0uS","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":"Performs string normalisation and computes daily sum series for customer segment observation data (account_count or revenue_amount) across up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"Normalize the company group strings and compute a daily sum series for account_count using my customer segment rows: [{\"row_id\":\"r1\",\"company_group\":\"Group A\",\"date\":\"2026-10-01\",\"account_count\":10,\"revenue_amount\":500},{\"row_id\":\"r2\",\"company_group\":\"group-a\",\"date\":\"2026-10-01\",\"account_count\":15,\"revenue_amount\":300}] — give me both the string normalisation and daily sum reports.","exampleUseCases":[{"title":"Daily revenue rollup by segment","prompt":"I have 150 rows of customer segment observations with company groups and dates — can you normalize the group name strings and compute the daily sum series for revenue_amount so I can see total daily revenue per segment?"},{"title":"Account count aggregation audit","prompt":"Run string normalisation and a daily sum series on these customer segment records for the account_count field — I want to make sure group labels are consistent and see how account counts total up each day across my 80 rows."},{"title":"Multi-segment time series prep","prompt":"Take my customer segment observation data (up to 200 rows with row_id, company_group, date, and revenue_amount) and give me the two reports: string normalisation of the group names and the daily sum series for revenue_amount so I can feed clean aggregates into my dashboard."}],"resultDescription":"Two analytical reports delivered from local analytical engines: (1) a string normalisation report for the company_group field across the supplied rows, and (2) a daily sum series report aggregating either account_count or revenue_amount by date. Covers up to 200 input rows per call.","failureModes":["More than 200 rows supplied — request rejected due to maxItems constraint","Missing required fields (row_id, company_group, date, account_count, or revenue_amount) — validation error","Invalid date format (not YYYY-MM-DD pattern) — schema validation failure","Field selector not one of 'account_count' or 'revenue_amount' — enum validation error","Empty rows array — minItems:1 constraint violation","Numeric values outside allowed range (±1,000,000,000,000) — validation error"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation of categorical segment identifiers and a daily sum aggregation on a numeric metric (account_count or revenue_amount) in a single API call at low cost ($0.01 USDC for both reports). Ideal for lightweight, offline analytical pre-processing of customer segment observation data without requiring a live database, prediction engine, or external data lookup. Best suited for batch sizes up to 200 rows where two bundled local reports add efficiency over separate calls.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T06:58:54.970Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-string-normalisation-daily-sum-series-82a205f1"}