{"uid":"cap_YrzKRz_OxmhODbQ1BQTyy","slug":"customer-followups-string-normalisation-date-by-category-pivot-90fb8e31","name":"Customer Followups — String Normalisation + Date by Category Pivot","description":"Customer followups — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied customer followups records (completed_followups, due_followups). 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-operations-19-035?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team_group","date","completed_followups","due_followups"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"team_group":{"type":"string","default":"","maxLength":80},"due_followups":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"completed_followups":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","team_group":"group-a","due_followups":1,"completed_followups":10},{"date":"2026-10-02","row_id":"row-2","team_group":"group-b","due_followups":2,"completed_followups":20},{"date":"2026-10-03","row_id":"row-3","team_group":"group-a","due_followups":3,"completed_followups":15},{"date":"2026-10-04","row_id":"row-4","team_group":"group-b","due_followups":4,"completed_followups":30}],"maxItems":200,"minItems":1},"field":{"enum":["completed_followups","due_followups"],"type":"string","default":"completed_followups"}}},"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_PnsdtabAjZC40F_hpiTAh","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":"Runs two local analytical reports (string normalisation and date-by-category pivot) on up to 200 rows of customer followup data (completed_followups, due_followups) for $0.01 USDC.","exampleAgentPrompt":"Can you run string normalisation and a date-by-category pivot on these customer followup records for my team groups? I have up to 50 rows with completed_followups and due_followups values — use the completed_followups field for the pivot.","exampleUseCases":[{"title":"Team followup completion audit","prompt":"I have a CSV of 120 customer followup records with team_group, date, completed_followups, and due_followups columns — can you normalize the string fields and give me a pivot of completed_followups broken down by date and team group?"},{"title":"Due followups backlog by group","prompt":"Run an analysis on my due_followups data — I have about 80 rows tagged with team groups and dates. I need the strings normalized and a pivot table showing due_followups by date and category."},{"title":"Sales ops weekly followup report","prompt":"Here are this week's followup records for our sales team, about 30 rows, each with a row_id, team_group, date, and both completed and due followup counts — please normalize the labels and pivot the completed_followups by date and team group so I can see who's on track."}],"resultDescription":"Returns two independent analytical reports: (1) a string normalisation report cleaning team_group and other text fields, and (2) a date-by-category pivot table aggregating the selected followup metric (completed_followups or due_followups) across team groups and dates — all computed locally on the supplied data with no external lookups.","failureModes":["Exceeds 200-row limit — request rejected","Missing required fields (row_id, team_group, date, completed_followups, due_followups) — validation error","Invalid date format (must match YYYY-MM-DD) — schema validation failure","Numeric values outside allowed range (±1,000,000,000,000) — rejected","Empty rows array — minimum 1 item required","Invalid field enum value — must be 'completed_followups' or 'due_followups'"],"whenToPreferThis":"Choose this endpoint when you need two lightweight analytical transformations — string normalisation and a date-by-category pivot — on a batch of customer followup records (up to 200 rows) in a single cheap call ($0.01 USDC). Ideal when you already have the data in hand and need local computation rather than live CRM lookups or predictions. Best suited for CRM operations, sales team reporting, or followup tracking dashboards where you want clean labels and a grouped date pivot without standing up your own analytics pipeline.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:33:55.737Z","isFirstParty":false,"canonicalSlug":"customer-followups-string-normalisation-date-by-category-pivot-90fb8e31"}