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Top 10 Excel Functions (2025) – One Real-Life Sales Use Case

Top 10 Excel Functions (2025) – One Real-Life Sales Use Case
Top 10 Excel Functions (2025) — One Real-Life Use Case

🏷️ The Scenario (one sheet)

You’re a sales analyst preparing a quick “actuals & issues” roll-up for the product team. You have transaction-level data: Date, Region, SalesRep, Product, Units, UnitPrice, Discount%, Returned (Yes/No)

📋 Sample Data

DateRegionSalesRepProductUnitsUnitPriceDisc%Returned
2025-10-01WestAmyProDesk34500.05No
2025-10-02EastRahulProMouse10250No
2025-10-02WestAmyProDesk14500.10Yes
2025-10-03NorthRitaProKey5700.02No
2025-10-04EastRahulProMouse4250.00No

🔢 Quick totals (what we want)

  • Total revenue (after discount, excluding returns)
  • Unique products sold
  • Top performing rep
  • Clean list of SKUs and units for dispatch
  • Small summary metric series created via LAMBDA for reuse

🚀 Top 10 functions used in this single workflow

1) XLOOKUP — flexible, modern lookup

Use: fetch product price or SKU details from a lookup table
=XLOOKUP(“ProDesk”, Products!A:A, Products!C:C, “Not found”)

Example: Pull unit price or category for ‘ProDesk’. XLOOKUP is robust against column order, supports not-found defaults, and exact or approximate matches.

Tip: Use XLOOKUP instead of VLOOKUP to avoid column-index maintenance.

2) FILTER — dynamic row filtering

Use: get only non-returned rows for revenue calculation
=FILTER(Table1, Table1[Returned]=”No”)

Example: Create an array of valid transactions (exclude returns). Useful for feeding downstream formulas (SUM, MAP, etc.).

3) UNIQUE – list unique SKUs or reps

Use: build the product dispatch list
=UNIQUE(FILTER(Table1[Product], Table1[Returned]=”No”))

Example: Returns a clean list of products sold (no duplicates) for packing lists.

4) LET – name intermediate calculations

Use: make complex formulas readable and efficient
=LET(net, Units*UnitPrice*(1-Disc%), IF(Returned=”No”, net, 0))

Example: name `net` and re-use it in SUM or other logic without recalculation. Great for clarity and performance.

5) LAMBDA – reusable custom metric

Use: create a named function for net revenue per row
=LAMBDA(units,price,disc,returned, IF(returned=”No”, units*price*(1-disc),0)) /* Saved as: NetRevenue */

Example: Define `NetRevenue` once and call it: =NetRevenue(3,450,0.05,"No"). Use in LET, MAP, REDUCE for consistent logic.

6) MAP – apply a LAMBDA across rows (vectorized)

Use: compute net revenue for every row and return an array
=MAP(Table1[Units],Table1[UnitPrice],Table1[Disc%],Table1[Returned], LAMBDA(u,p,d,r, NetRevenue(u,p,d,r)))

Example: returns a column of net revenues. Feed into SUM or REDUCE. It replaces the need for helper columns.

7) REDUCE – accumulate a single result (e.g., total revenue)

Use: sum an array produced by MAP with custom accumulation
=REDUCE(0, MAP(…), LAMBDA(acc,val, acc+val))

Example: combine MAP output into a single total revenue figure. REDUCE is useful when accumulation needs custom logic (taxes, thresholds).

8) SCAN – running totals / cumulative metrics

Use: get cumulative revenue across dates for a sparkline / trend
=SCAN(0, NetRevenuesArray, LAMBDA(acc,val, acc + val))

Example: show day-by-day running total for dashboard trend. Works with arrays without helper columns.

9) TEXTSPLIT – split composite text fields (e.g., “Region|City”)

Use: split a combined field into Region & City for grouping
=TEXTSPLIT(A2,”|”)

Example: If incoming data has “West|Pune”, TEXTSPLIT turns that into separate columns – useful for quick normalization.

10) SEQUENCE (with VSTACK/HSTACK) – build dynamic arrays

Use: build date series, index tables, or combine arrays
=SEQUENCE(7,1,DATE(2025,10,1),1) /* 7-day series */

Example: generate a week of dates for joining with sales totals. Pair with VSTACK/HSTACK to assemble multi-row outputs.

🧭 How these fit together (short flow)

  1. TEXTSPLIT to clean incoming fields.
  2. FILTER to select valid rows (exclude returns).
  3. MAP + LAMBDA to compute row-level net revenue.
  4. REDUCE to total revenue, SCAN for cumulative trend.
  5. UNIQUE to create dispatch lists, XLOOKUP to enrich with product metadata, SEQUENCE to create date scaffolding.

🛠️ Implementation snippet (compact)

/* NetRevenue LAMBDA saved as a name */ =LAMBDA(u,p,d,r, IF(r=”No”, u*p*(1-d), 0)) /* Total revenue in one formula (vectorized) */ =REDUCE(0, MAP(Table1[Units],Table1[UnitPrice],Table1[Disc%],Table1[Returned], LAMBDA(u,p,d,r, NetRevenue(u,p,d,r))), LAMBDA(acc,val, acc+val))
Pro tip: Use LET to name MAP result arrays (for reuse) – this avoids computing MAP multiple times in the same sheet.

⚠️ Common pitfalls

  • Remember Excel arrays spill – reference entire spill ranges (e.g., A2#) when reusing results.
  • Use exact match modes in XLOOKUP unless you intentionally want approximations.
  • When saving LAMBDA names, test with sample inputs first.

✅ Summary -Key takeaways

In 2025, Excel’s array-first functions (MAP, REDUCE, SCAN) plus reusable logic (LAMBDA, LET) let you build single-sheet, maintainable analytics without helper columns. Combine with FILTER, UNIQUE, and XLOOKUP to clean and enrich data quickly.

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