{"uid":"cap_8n9w0c8e9-zyyrl0z0VZx","slug":"customer-segment-observations-daily-sum-series-date-by-category-pivot-5fe10f40","name":"Customer Segment Observations — Daily Sum Series + Date by Category Pivot","description":"Customer segment observations — Daily sum series + Date by category pivot: Daily sum series + Date by category pivot 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-16-143?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_tP_l4a4QkzLgDCucHU0vO","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":"Generates two analytical reports from customer segment data: a daily sum time series and a date-by-category pivot table, for up to 200 rows of account_count or revenue_amount data.","exampleAgentPrompt":"I have customer segment data with dates, company groups, account counts, and revenue amounts — can you run both a daily sum series and a date-by-category pivot on the account_count field? Here are the rows: group-a on 2026-10-01 had 10 accounts and $1 revenue, group-b on 2026-10-02 had 20 accounts and $2 revenue, group-a on 2026-10-03 had 15 accounts and $3 revenue, group-b on 2026-10-04 had 30 accounts and $4 revenue.","exampleUseCases":[{"title":"Monthly revenue pivot by segment","prompt":"I have our monthly customer segment observations across two groups — SaaS and Enterprise — with revenue amounts for each day in October. Can you produce both a daily sum series and a date-by-category pivot for the revenue_amount field so I can see how each segment contributed over time?"},{"title":"Daily account count trend report","prompt":"Here are 150 rows of customer segment data with dates and account counts across our three company groups. Please run a daily sum series and a pivot of date by company group on the account_count field so I can track how our customer base is growing each day."},{"title":"Segment performance comparison dashboard","prompt":"I need two quick reports from our Q4 segment data: a daily sum time series and a date-by-category pivot — both using the revenue_amount field — across our five customer groups. I'll give you up to 200 rows. Can you compute those for me?"}],"resultDescription":"Two analytical reports returned together: (1) a daily sum time series showing the selected metric (account_count or revenue_amount) aggregated by date, and (2) a date-by-category pivot table cross-tabulating dates against company_group values. Both reports are computed locally from the supplied rows with no external data lookup.","failureModes":["Input array is empty or missing (minItems: 1 not met)","More than 200 rows supplied (maxItems exceeded)","Invalid date format — must match YYYY-MM-DD pattern","Missing required fields: row_id, company_group, date, account_count, or revenue_amount","Invalid field enum value — must be 'account_count' or 'revenue_amount'","Numeric values out of allowed range (±1,000,000,000,000)","row_id exceeds 80 characters or is empty"],"whenToPreferThis":"Use this endpoint when you have up to 200 rows of customer segment observation data and need both a daily sum time series AND a date-by-category pivot in a single low-cost call ($0.01 USDC). It is ideal when your data is already structured with date, company_group, and one of account_count or revenue_amount, and you want local analytical computation with no external dependencies, live lookups, or predictions. Prefer this over building your own aggregation when you want packaged dual-report output for business intelligence or reporting workflows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T12:44:32.679Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-daily-sum-series-date-by-category-pivot-5fe10f40"}