{"uid":"cap_yudYU2tJRVy1ji62hXltX","slug":"product-feature-telemetry-date-by-category-pivot-88342ae5","name":"Product Feature Telemetry – Date by Category Pivot","description":"Product feature telemetry - Date by category pivot: Date by category pivot for Product feature telemetry. 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-feature-telemetry-pivot?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","feature","date","events","unique_users"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"events":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"feature":{"type":"string","default":"","maxLength":80},"unique_users":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","events":10,"row_id":"row-1","feature":"group-a","unique_users":1},{"date":"2026-10-02","events":20,"row_id":"row-2","feature":"group-b","unique_users":2},{"date":"2026-10-03","events":15,"row_id":"row-3","feature":"group-a","unique_users":3},{"date":"2026-10-04","events":30,"row_id":"row-4","feature":"group-b","unique_users":4}],"maxItems":200,"minItems":1},"field":{"enum":["events","unique_users"],"type":"string","default":"events"}}},"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_lz7LPh50jmA_TI9_Ijtxo","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":"Pivots up to 200 product feature telemetry records by date and category, producing a local descriptive analytics report of events or unique users per feature over time.","exampleAgentPrompt":"I have daily telemetry rows for my product features — feature names like 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, and event counts — can you pivot them by date and category and give me a summary report using the 'events' field?","exampleUseCases":[{"title":"Daily feature usage comparison","prompt":"I've got telemetry records for three product features — 'search', 'export', and 'dashboard' — with event counts logged for each day in October 2026. Can you pivot these rows by date and feature so I can see which feature had the most events each day? Use the events field."},{"title":"Unique user reach per feature","prompt":"I want to see how many unique users hit each of our product features — 'onboarding', 'billing', and 'reporting' — per day last month. I have up to 150 rows with dates and unique_user counts. Can you create a date-by-category pivot using unique_users as the measure?"},{"title":"A/B test group telemetry breakdown","prompt":"We ran an A/B test with feature groups 'variant-a' and 'variant-b' and collected daily event telemetry for two weeks. Can you pivot the 120 telemetry rows by date and group using the events field so we can compare activity across the groups day by day?"}],"resultDescription":"A date-by-category pivot report where rows represent dates and columns represent feature categories, with aggregated values (events or unique_users) for each cell — delivered as a bounded, local descriptive analytics output with no forecasting or external enrichment.","failureModes":["Missing required fields (row_id, feature, date, events, unique_users) cause validation errors","Date strings not matching YYYY-MM-DD pattern are rejected","More than 200 rows submitted exceeds the maxItems limit and is rejected","Invalid field enum value (anything other than 'events' or 'unique_users') causes a schema error","Empty rows array (minItems: 1 violation) returns an error","Numeric values outside the allowed min/max range are rejected"],"whenToPreferThis":"Choose this endpoint when you have raw, flat telemetry rows for product features and need a quick descriptive pivot table by date and category — without needing forecasting, enrichment, or external data. Best for local analytics on up to 200 records where the goal is cross-tabulating events or unique users across features and dates.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T18:48:39.007Z","isFirstParty":false,"canonicalSlug":"product-feature-telemetry-date-by-category-pivot-88342ae5"}