{"uid":"cap_h6cP-BZWbHar7XAZnub1V","slug":"ticket-escalations-date-by-category-pivot-468f7372","name":"Ticket Escalations Date-by-Category Pivot","description":"Ticket escalations - Date by category pivot: Date by category pivot for Ticket escalations. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded date by category pivot report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-ticket-escalations-pivot?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team","date","tickets","escalations"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"team":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"tickets":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"escalations":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","team":"group-a","row_id":"row-1","tickets":10,"escalations":1},{"date":"2026-10-02","team":"group-b","row_id":"row-2","tickets":20,"escalations":2},{"date":"2026-10-03","team":"group-a","row_id":"row-3","tickets":15,"escalations":3},{"date":"2026-10-04","team":"group-b","row_id":"row-4","tickets":30,"escalations":4}],"maxItems":200,"minItems":1},"field":{"enum":["tickets","escalations"],"type":"string","default":"tickets"}}},"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_MulzvB0O3ogiaP3-1mv5D","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 a date-by-category pivot table for ticket escalation data, summarizing tickets or escalations across teams over time.","exampleAgentPrompt":"Can you run a date-by-category pivot on my ticket escalation data — I have 4 rows for group-a and group-b from Oct 1–4 2026 with ticket and escalation counts — and pivot on the escalations field?","exampleUseCases":[{"title":"Weekly escalation summary by team","prompt":"I have daily ticket data for my support teams alpha and beta from this past week, with ticket counts and escalation counts per day. Can you pivot it by date and team so I can see how escalations broke down across the week?"},{"title":"Identifying high-escalation dates per group","prompt":"Here's my support data for the last month — team names, dates, and escalation counts. Can you create a pivot table showing escalations by date across each team so I can spot which days had the worst escalation spikes?"},{"title":"Comparing ticket volume vs escalation rate by team","prompt":"I want to compare raw ticket volumes versus escalations across my three support groups — can you generate a date-by-team pivot on the tickets field for the last 30 days of data I'm providing?"}],"resultDescription":"Returns a bounded date-by-category pivot report (up to 200 input rows) showing the selected metric (tickets or escalations) cross-tabulated by date (rows) and team/category (columns), with local descriptive analytics and no external enrichment or forecasting.","failureModes":["Input array is empty or missing required fields (row_id, team, date, tickets, escalations) — returns validation error","Date strings not matching YYYY-MM-DD pattern — rejected by schema validation","More than 200 rows supplied — exceeds maxItems limit","Invalid field enum value (not 'tickets' or 'escalations') — schema rejection","Payment failure or insufficient USDC balance — 402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 records of ticket and escalation data and need a quick local descriptive pivot — no ML, no forecasting, no external data enrichment. Ideal for support analytics dashboards where you already have structured per-team, per-date data and need a cross-tabulated summary in a single inexpensive call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T00:47:23.780Z","isFirstParty":false,"canonicalSlug":"ticket-escalations-date-by-category-pivot-468f7372"}