{"uid":"cap_Ojx2gpVgbWt5ZLeRmFKnF","slug":"customer-segment-observations-string-normalisation-exact-row-1b49f19c","name":"Customer Segment Observations — String Normalisation + Exact Row Deduplication","description":"Customer segment observations — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication 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-16-020?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}}},"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_rCmYp5CcbmFvOBX6Sknja","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 deduplicates exact rows in customer segment observation records containing account counts and revenue amounts, producing two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you clean up my customer segment data? I have about 150 rows with fields like row_id, company_group, date, account_count, and revenue_amount — please run string normalisation and exact row deduplication on them and give me both reports.","exampleUseCases":[{"title":"Pre-analysis segment data cleanup","prompt":"I've got 120 rows of customer segment observations with company group names that have inconsistent capitalisation and some duplicate rows — can you normalise the strings and remove exact duplicates, then give me both reports?"},{"title":"Revenue data deduplication for quarterly review","prompt":"Before our quarterly review, I need to clean up our customer segment records — there are about 80 rows with account_count and revenue_amount per company group and date. Please deduplicate them and normalise the company group strings."},{"title":"Audit data quality across segment observations","prompt":"Run string normalisation and exact row deduplication on these 200 customer segment observation rows — I want both analytical reports so I can see what was cleaned up before I load the data into our dashboard."}],"resultDescription":"Two analytical reports: one covering string normalisation results (e.g. standardised company_group values) and one covering exact row deduplication results (identifying and removing duplicate records), applied to the supplied customer segment observation rows (up to 200 rows with account_count and revenue_amount fields).","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, company_group, date, account_count, revenue_amount) causes row rejection","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","account_count or revenue_amount outside [-1e12, 1e12] range rejected","Empty rows array returns an error","Payment failure or insufficient USDC balance prevents processing"],"whenToPreferThis":"Choose this endpoint when you need lightweight, offline data quality operations — specifically string normalisation and exact row deduplication — on customer segment observation data (account_count, revenue_amount per company_group and date) for up to 200 rows. It is ideal when you do not need live lookups, predictions, or external enrichment, and when you want two focused reports at low cost ($0.01 USDC). Prefer alternatives if you need fuzzy deduplication, probabilistic matching, or more than 200 rows processed at once.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T00:52:07.750Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-string-normalisation-exact-row-1b49f19c"}