{"uid":"cap_qpLqXK2K1OI--TOL7854c","slug":"web-traffic-date-by-category-pivot-ffb072c4","name":"Web Traffic Date-by-Category Pivot","description":"Web traffic - Date by category pivot: Date by category pivot for Web traffic. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded date by category pivot deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-analytics-web-traffic-pivot?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","channel","date","sessions","conversions"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"channel":{"type":"string","default":"","maxLength":80},"sessions":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"conversions":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","channel":"group-a","sessions":10,"conversions":1},{"date":"2026-10-02","row_id":"row-2","channel":"group-b","sessions":20,"conversions":2},{"date":"2026-10-03","row_id":"row-3","channel":"group-a","sessions":15,"conversions":3},{"date":"2026-10-04","row_id":"row-4","channel":"group-b","sessions":30,"conversions":4}],"maxItems":200,"minItems":1},"field":{"enum":["sessions","conversions"],"type":"string","default":"sessions"}}},"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_jYZYyDoxaUzTer4TIk2Xa","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 web traffic records into a date-by-category (channel) matrix for sessions or conversions.","exampleAgentPrompt":"Take my web traffic data — rows with dates, channels like 'organic' and 'paid-search', and session counts — and pivot it into a date-by-channel matrix showing sessions for each channel per day. I have about 50 rows covering October 2026.","exampleUseCases":[{"title":"Marketing channel performance matrix","prompt":"I have 120 rows of daily web traffic data with channels like 'email', 'paid-search', and 'direct', each with a date and session count. Can you pivot that into a table where each row is a date and each column is a channel, showing sessions?"},{"title":"Conversion rate analysis by channel","prompt":"I've got a month of web traffic rows with dates, channel names, and conversion counts. Please pivot them by date and channel so I can see how conversions break down across channels day by day — use conversions as the metric."},{"title":"A/B group traffic comparison over time","prompt":"I'm running an A/B test and have traffic rows tagged as 'group-a' or 'group-b' with daily session counts. Can you pivot the data by date and group so I can compare sessions side by side across the test period?"}],"resultDescription":"A pivoted table structure where dates are one axis and channel categories are the other, with the selected metric (sessions or conversions) as the cell values — derived entirely from local numeric processing of the supplied rows, with no external enrichment.","failureModes":["Fewer than 1 row supplied — minimum item validation fails","More than 200 rows supplied — maxItems limit exceeded","Date field not in YYYY-MM-DD format — pattern validation error","Missing required fields (row_id, channel, date, sessions, conversions) — schema validation error","Invalid field enum value (not 'sessions' or 'conversions') — enum validation error","Numeric values outside allowed range — min/maximum validation error"],"whenToPreferThis":"Choose this endpoint when you have raw, row-level web traffic data (up to 200 records) with dates and channel labels and need a quick local pivot computation — no external data sources, forecasting, or enrichment required. Ideal for reshaping analytics exports into cross-tabular summaries for sessions or conversions without spinning up a full BI tool.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:34.087Z","isFirstParty":false,"canonicalSlug":"web-traffic-date-by-category-pivot-ffb072c4"}