Weekly channel performance — self-initiated Excel demo with fictional campaign data.
For the week starting 12 October 2026, six valid records produce USD 245 spend, 13 leads and USD 18.85 cost per lead. Two source rows require review. These figures are sample data, not real campaign results.
The reporting date is editable. Cost per lead is calculated from matching totals. Week boundaries, zero leads, zero spend and missing values are handled explicitly.
Date changes, input changes and zero-versus-blank behavior were checked. AI-assisted implementation. Formula and visual checks passed; native Excel application testing was not performed.
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Order and shipment reconciliation — self-initiated Excel demo using fictional data.
Five orders are matched to eight shipment records. The sample shows 12 units remaining, 2 excess units and 3 held shipment rows. Split shipments are aggregated; duplicate shipment IDs and unknown orders are held.
Remaining and excess quantities are shown separately so over-shipments do not hide shortfalls. Editable order and shipment inputs update the results.
Checks covered split shipments, zero quantities, negative inputs, duplicate order keys and input changes. AI-assisted implementation. This is a demonstration, not client work. Native Excel application testing was not performed.
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Inventory replenishment — self-initiated Excel demo with fictional data.
Eight SKUs: six ready and two flagged for review. The valid rows propose 45 units across two items. Available stock accounts for reservations and inbound quantities. Missing, negative, fractional and duplicate-key inputs remain visible for review.
Editable workbook with formula-driven reorder quantities. Checks covered input changes, zero versus blank, duplicate keys and restoration of the sample values.
AI-assisted implementation. This is a working demonstration, not client work. Formula and visual checks passed; native Excel application testing was not performed.
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Sales Data Cleanup — self-initiated demo using fictional data.
27 inputs = 18 clean records + 2 removed duplicates + 7 held exceptions. Accepted sample sales: USD 658.50 (fictional data, not income).
Deliverables: editable Excel workbook with Result, Raw and Exceptions sheets; repeatable Python cleaner; clean, exception and change-log CSVs.
Rules preserve the original, remove exact normalized duplicates, hold all conflicting IDs, and flag missing or ambiguous values.
Seven automated checks passed; formula recalculation and rendered workbook views checked. Native Excel application testing was not performed.
AI-assisted implementation. This is a demonstration, not a previous client engagement.
Service: https://contra.com/s/PbUmRmcE-excel-and-csv-cleanup-with-editable-summary
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