{"uid":"cap_FLh0IEg7r8iXBJFOusLV6","slug":"account-research-coverage-string-normalisation-two-measure-correlation-03bd6e81","name":"Account Research Coverage — String Normalisation + Two-Measure Correlation","description":"Account research coverage — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied account research coverage records (researched_accounts, target_accounts). 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-08-033?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","researched_accounts","target_accounts"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"target_accounts":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"researched_accounts":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","target_accounts":1,"researched_accounts":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","target_accounts":2,"researched_accounts":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","target_accounts":3,"researched_accounts":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","target_accounts":4,"researched_accounts":30}],"maxItems":200,"minItems":1}}},"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_0EAElU645V33_HCcC80YD","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":"Normalises strings and computes two-measure correlation analysis on account research coverage data (researched_accounts vs target_accounts) for up to 200 rows.","exampleAgentPrompt":"I have account research coverage records for two company groups — group-a and group-b — across four dates in October 2026. Can you normalise the string fields and run a two-measure correlation between researched_accounts and target_accounts for those rows?","exampleUseCases":[{"title":"Sales team coverage gap analysis","prompt":"Here are our account research coverage records for Q4 — rows for company groups EMEA and APAC from 2026-10-01 to 2026-10-30, each with researched_accounts and target_accounts counts. Can you normalise the company group strings and run a two-measure correlation to show how well our research is tracking against targets?"},{"title":"Multi-group pipeline research audit","prompt":"I've got 150 rows of account research data across five company groups, dated through November 2026, with researched_accounts and target_accounts for each row. Please normalise the string fields and give me a correlation report between the two measures so I can see which groups are underperforming."},{"title":"Weekly account coverage review","prompt":"Run string normalisation and a two-measure correlation on this week's account research coverage snapshot — I have 40 rows for group-north and group-south from 2026-11-04 to 2026-11-08, each with researched_accounts and target_accounts values."}],"resultDescription":"Two analytical reports: one string normalisation report (cleaned/standardised company_group and other string fields) and one two-measure correlation report quantifying the relationship between researched_accounts and target_accounts across the submitted rows. No external data is fetched; all analysis is performed on the supplied rows only.","failureModes":["Fewer than 1 row submitted — validation error","More than 200 rows submitted — exceeds batch limit","Missing required fields (row_id, date, researched_accounts, target_accounts) — schema validation failure","Date field not matching YYYY-MM-DD pattern — format validation error","Numeric values outside allowed range (±1,000,000,000,000) — value validation error","Insufficient numeric variance in one measure — correlation may be undefined or return NaN"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and two-measure correlation computed together on account research coverage data (researched_accounts and target_accounts) in a single low-cost call. It is ideal for sales ops, CRM analytics, or pipeline review workflows where you want to clean string fields and understand the statistical relationship between two numeric coverage metrics across up to 200 rows, without needing live lookups, predictions, or external integrations.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:53:28.774Z","isFirstParty":false,"canonicalSlug":"account-research-coverage-string-normalisation-two-measure-correlation-03bd6e81"}