Homework — Day 4 of 5

E-Commerce Returns Analysis

Analyse 25 Q1 return records using ARRAYFORMULA for return rates, QUERY for category patterns, risk flagging with nested IF, and a SUMIF/COUNTIF dashboard.

CourseData Analytics
InstructorPuneet Arora
PlatformAplly.xyz
DifficultyBeginner
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What You're Building

A returns analysis dashboard for ShopEase's Q1 data — automatically calculating return rates for 25 orders via ARRAYFORMULA, classifying risk levels with nested IF and conditional formatting, querying patterns by category, and building a summary dashboard using SUMIF/COUNTIF/AVERAGEIF.

Day4
Order IDCategorySale (₹)Return (₹)Return Rate%Risk Flag
R001Electronics32,00028,000=formulaHIGH RISK
R003Home950200=formulaLOW
R006Clothing1,8001,800=formulaHIGH RISK
… 22 more rows …
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Step-by-Step Guide
1
Build Your 25-Row Returns Dataset
Create tab Day4. Add these columns: Order ID, Product Name, Category (Electronics/Clothing/Home/Books), Sale Amount, Return Amount, Return Reason, Return Date, City, Customer Rating (1–5). Then add 25 rows. Ensure Return Amount is always <= Sale Amount for realistic data.
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Distribution TipFor interesting QUERY results, include at least 5-6 rows per category. Mix return reasons — "Damaged" for Electronics, "Not as Described" for Clothing, "Changed Mind" for Books.
2
Return Rate % — ARRAYFORMULA (Column J)
In cell J3, calculate return rate for all 25 rows at once:
Cell J3 — one formula for all rows
=ARRAYFORMULA( IF(E3:E27="", "", IFERROR((F3:F27 / E3:E27) * 100, 0)))
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IFERROR is EssentialIf any Sale Amount is 0, dividing by it causes #DIV/0! error. IFERROR(formula, 0) replaces the error with 0 instead — keeping your sheet clean.
3
Risk Flag with Conditional Formatting (Column K)
Cell K3 — Risk classification
=ARRAYFORMULA( IF(J3:J27="", "", IF(J3:J27>60, "HIGH RISK", IF(J3:J27>=30, "MEDIUM", "LOW"))))
Apply 3 Conditional Formatting Rules on K3:K27:
Rule 1: Formula =$K3="HIGH RISK" → Red fill (#FDECEA), bold red text
Rule 2: Formula =$K3="MEDIUM" → Yellow fill (#FFF8DC), dark gold text
Rule 3: Formula =$K3="LOW" → Green fill (#DCF5E8), dark green text
4
QUERY — Category Breakdown (Row 30)
Cell A30
=QUERY(A2:K27, "SELECT D, COUNT(A), AVG(J), SUM(F) GROUP BY D LABEL COUNT(A) 'Total Returns', AVG(J) 'Avg Return Rate %', SUM(F) 'Total Return Value'", 1)
5
QUERY — Electronics High-Return Filter (Row 50)
Cell A50
=QUERY(A2:K27, "SELECT A, B, E, F, J, K WHERE D = 'Electronics' AND J > 50 ORDER BY J DESC", 1)
6
Summary Dashboard — SUMIF, COUNTIF, AVERAGEIF (Column M)
Build a dashboard in column M–P that answers key questions per category:
// For "Electronics" — repeat for each category M4: =COUNTIF($D$3:$D$27, "Electronics") N4: =SUMIF($D$3:$D$27, "Electronics", $F$3:$F$27) O4: =AVERAGEIF($D$3:$D$27, "Electronics", $I$3:$I$27)
=SUMIF( range, criteria, sum_range )
$D$3:$D$27 — Column to check for the condition (Category)
"Electronics" — The condition to match
$F$3:$F$27 — Column to SUM when condition is matched (Return Amount)
Bonus — Version History Audit Trail

After completing each task, go to File → Version History → Name current version. Name them "Task 1 Complete", "Task 2 Complete", etc. Your instructor will verify at least 3 named versions with distinct timestamps in your history.