READ-ONLY WORKBOOK · 13 SHEETS

DiaMedical USA — E-commerce analysis workbook

Modeled, calculated and public-data sheets behind the DiaMedical USA case study. Values are shown exactly as calculated in the workbook; hover a calculated cell to read its formula. ← Back to the case study

DiaMedical Case Study — Workbook Guide
Supporting analysis file for an independent DiaMedical interview case study by Mousa Batarseh: the evidence, modeled data, calculations, operational recommendations, and measurement definitions used throughout the case study.
HOW TO EXPLORE THIS WORKBOOK
Use the worksheet tabs to move through the analysis. Start with this guide and Sources and Disclosures, then catalog QA, search terms, SEO, campaign planning, budget control, KPI definitions, pivot-ready data with its SUMIFS cross-tab and native PivotTable, and the data dictionary.
THE PROBLEM THIS WORKBOOK SUPPORTS
A nursing-program director needs four Med-Surg stations for 24 learners. The case asks how a commerce experience can translate that teaching goal into an explained product plan—and what catalog, search, SEO, QA, campaign, reporting, and implementation work is needed behind the journey.
DATA COLLECTION AND METHODOLOGY
The workbook uses publicly available DiaMedical pages and visible product/category content, a limited 16-URL public audit, bounded manual browser checks, a 65-record local public product sample, deterministic modeled demonstration data, inspectable Excel formulas, and proposed KPIs. It does not contain private analytics, revenue, margin, customer, advertising, or internal operational data. Those sources are required before production decisions or measured-result claims.
OrderWorksheetWhat it containsWhy it mattersData type
01Workbook GuidePurpose, method, navigation, index, and disclosuresExplains how to understand and use the workbookDocumentation
02Sources and DisclosuresPublic links, retrieval dates, methods, and limitationsShows where supporting evidence came fromPublic evidence + documentation
03Catalog Master65 public sample records plus quality and lookup fieldsShows the structured data feeding discovery and QAPublic + calculated
04Catalog QAField-level quality flags, severity, notes, and scopeTurns catalog gaps into a filterable work queueCalculated + human verification
05Search TermsModeled queries, zero-result terms, counts, and share formulasSupports search-relevance and recovery planningModeled + calculated
06SEO AuditPublic title observations and proposed keyword/title prioritiesConnects discovery intent to organic acquisition planningPublic + proposed
07Campaign PlanModeled campaign clusters, keywords, budgets, and quote-intent scenariosDemonstrates paid-search planning without a fake ad accountModeled + calculated
08Trade Show BudgetModeled cost plan, owner fields, actuals, variance, and notesDemonstrates campaign budget control and accountabilityModeled + calculated
09KPI SummaryProposed metrics, formulas, definitions, and validation needsDefines how the proposed solution would be measuredCalculated + requires internal data
10Pivot SourceNormalized category, severity, flag, and count-helper rowsProvides a clean source for a desktop Excel PivotTableCalculated from local sample
11Pivot SummaryCategory × severity and flag × severity cross-tabs built with live SUMIFS formulasShows the pivot logic in any viewer, with a reconciliation check against Catalog QACalculated from local sample
12PivotTableNative Excel PivotTable on the Pivot Source table (rows = category, columns = severity, values = flag count)The same summary as an interactive PivotTable; refresh after editing Pivot SourceCalculated from local sample
13Data DictionaryField definitions, classifications, calculation notes, and limitationsMakes the workbook understandable without the websiteDocumentation
KEY WORKBOOK CHECKS — CALCULATED, NOT CLAIMED RESULTS
CheckCalculated valueHow to interpret it
Public sample records65Size of the bounded local product sample; not the full DiaMedical catalog.
Catalog QA flags235Field-level flags generated from the documented local scoring rules.
Average local quality score88.1A completeness score for the local demonstration records, not product performance.
Modeled sessions3,864Fixed-seed demonstration volume used to test reporting behavior.
DISCLOSURE
Independent application case study prepared by Mousa Batarseh using publicly available information. This project was not commissioned, approved, or endorsed by DiaMedical USA. Operational data and performance scenarios are modeled demonstrations unless explicitly identified as public source data.
PIVOTTABLE AND CALCULATION NOTE
Pivot Source is a clean Excel table and named range (PivotSourceData). The PivotTable sheet holds a native PivotTable built on it (rows = Category, columns = Severity, values = Sum of Count helper); refresh it after editing Pivot Source. The Pivot Summary sheet shows the same cross-tabs as live SUMIFS formulas, visible in any viewer, and reconciles them to the Catalog QA row count. Formulas recalculate when the workbook opens in Excel.