{"uid":"cap_Tjt0ttcf7ZAKNLb7qX-Kn","slug":"customer-segment-observations-category-frequencies-trailing-mean-series-83c37cba","name":"Customer Segment Observations — Category Frequencies + Trailing Mean Series","description":"Customer segment observations — Category frequencies + Trailing mean series: Category frequencies + Trailing mean 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-16-103?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":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_KoPPb3JASHwPkEp8CDcR2","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":"Analyzes up to 200 customer segment observation rows to produce two reports: category frequency distribution and trailing mean time series for account_count or revenue_amount.","exampleAgentPrompt":"Run category frequency and trailing mean analysis on my customer segment data — I have rows with company_group, date, account_count, and revenue_amount fields. Use account_count as the metric and a window of 3. Here's the data: [{\"row_id\":\"r1\",\"company_group\":\"enterprise\",\"date\":\"2025-01-01\",\"account_count\":50,\"revenue_amount\":5000},{\"row_id\":\"r2\",\"company_group\":\"smb\",\"date\":\"2025-01-02\",\"account_count\":120,\"revenue_amount\":2000}].","exampleUseCases":[{"title":"Revenue trailing mean by segment","prompt":"I have 60 rows of daily customer segment observations with company_group, date, and revenue_amount. Can you run the category frequency and trailing mean reports using revenue_amount as the field with a window of 5?"},{"title":"Account count frequency analysis","prompt":"Analyze these 30 customer segment records for me — I want to see the category frequency breakdown and a trailing mean series for account_count using a window of 4. The rows include company_group labels like 'retail' and 'wholesale'."},{"title":"Monthly segment trend reporting","prompt":"I've got 90 rows of monthly customer segment data across three company groups. Run both the category frequency and trailing mean reports on account_count with a window size of 3 so I can spot trends."}],"resultDescription":"Returns two analytical reports derived from the supplied rows: (1) a category frequency report showing how often each company_group appears across observations, and (2) a trailing mean time series for the chosen numeric field (account_count or revenue_amount) using the specified rolling window size. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row supplied — validation error","More than 200 rows supplied — exceeds limit, request rejected","Invalid date format (not YYYY-MM-DD) — schema validation failure","Window size smaller than 2 or larger than 200 — validation error","Field not set to 'account_count' or 'revenue_amount' — enum validation failure","Numeric values outside ±1,000,000,000,000 range — validation error","Missing required fields (row_id, company_group, date) in any row — request rejected"],"whenToPreferThis":"Choose this endpoint when you need two complementary statistical views — category frequency counts and a rolling average trend — on customer segment data (account_count or revenue_amount) in a single low-cost call. Ideal for business analysts or agents that have already collected segment observation records and want quick descriptive statistics without building custom analytics. Best suited for datasets up to 200 rows where no external data enrichment or predictive modeling is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T12:44:56.072Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-category-frequencies-trailing-mean-series-83c37cba"}