{"uid":"cap_NIaRfZs7Keaa6z6ZLbDFl","slug":"customer-segment-observations-string-normalisation-numeric-interval-c4cd86c7","name":"Customer Segment Observations — String Normalisation + Numeric Interval Filter","description":"Customer segment observations — String normalisation + Numeric interval filter: String normalisation + Numeric interval filter 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-16-026?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_6pdF6zCD2Yor4R-9GmK97","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":"Applies string normalisation and numeric interval filtering to customer segment observation records (account_count, revenue_amount), producing 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you normalise the company group strings and filter rows where account_count is between 5 and 50 across these customer segment records? Here are 4 rows: row-1 on 2026-10-01 for group-a with account_count 10 and revenue_amount 1, row-2 on 2026-10-02 for group-b with account_count 20 and revenue_amount 2, row-3 on 2026-10-03 for group-a with account_count 15 and revenue_amount 3, row-4 on 2026-10-04 for group-b with account_count 30 and revenue_amount 4.","exampleUseCases":[{"title":"Filter segments by account count range","prompt":"Take these 10 customer segment rows and give me a report showing only the ones where account_count falls between 100 and 500, with the company group strings normalised — the field I want filtered is account_count, minimum 100, maximum 500."},{"title":"Revenue range audit across company groups","prompt":"I have 50 customer segment observation records across several company groups and I need two reports: one with string-normalised company labels and one filtering revenue_amount to only rows between 1000 and 50000 — can you run both at once?"},{"title":"Data quality check before segment reporting","prompt":"Before I send this customer segment data to my finance team, can you normalise the company_group strings and filter out any rows where account_count is outside the range of 0 to 200? I have about 80 rows to process."}],"resultDescription":"Two analytical reports based on the supplied customer segment rows: one covering string normalisation of the company_group field and one applying a numeric interval filter to the chosen field (account_count or revenue_amount), returning only rows within the specified minimum/maximum range. All processing uses local analytical engines with no external lookups.","failureModes":["Rows array exceeds 200 items — request rejected","Missing required fields (row_id, company_group, date, account_count, revenue_amount) on any row — validation error","Invalid date format (must match YYYY-MM-DD) — schema validation failure","Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejection","Invalid field enum value (must be 'account_count' or 'revenue_amount') — error","Payment of 0.01 USDC not provided or declined — 402 response"],"whenToPreferThis":"Choose this endpoint when you have up to 200 customer segment observation rows and need both string normalisation on company group labels and a numeric range filter on either account_count or revenue_amount in a single call. It is ideal for lightweight, self-contained data cleaning and filtering tasks that do not require external lookups, predictions, or live data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T06:58:27.467Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-string-normalisation-numeric-interval-c4cd86c7"}