Blinkit Dashboard in Excel: Quick Commerce KPIs, 10-Minute Delivery, AOV and Cancellations
A quick commerce app promises groceries in about 10 minutes. The owner must see speed, basket size and cancellations every day. This page gives you a ready Excel dashboard for it. It has 1,800 example rows, 15 KPI cards, 6 charts and 3 drop-down filters.
What you'll learn on this page
- Why a Blinkit-style quick commerce business needs a dashboard
- What is inside each sheet of the workbook
- What the 15 KPIs mean and the formula behind each
- How the City, Month and Category drop-downs change every number
- How to add new data safely
- Common mistakes and how to avoid them
Download the template: blinkit-dashboard-template.xlsx (Excel workbook, 6 sheets, example data).
Example data only
Every number in this workbook is made up for practice. It is not real Blinkit data and not an official report. The colours are only inspired by the brand; there is no logo.

Figure 1. The Dashboard sheet with all filters set to All (example data)
In short
This Blinkit-style quick commerce dashboard shows 1,800 example rows on one screen. Pick a filter and all 15 KPI cards and 6 charts change at once. All data is made up for practice.
थोडक्यात
हा Blinkit-style quick commerce dashboard 1,800 example rows एका screen वर दाखवतो. पिवळ्या drop-down मधून filter निवडा, की सगळी 15 KPI cards आणि 6 charts लगेच बदलतात. सगळा data सरावासाठी काल्पनिक आहे.
संक्षेप में
यह Blinkit-style quick commerce dashboard 1,800 example rows एक screen पर दिखाता है. पीले drop-down से filter चुनें, तो सभी 15 KPI cards और 6 charts तुरंत बदल जाते हैं. सारा data अभ्यास के लिए काल्पनिक है.
1. Why this dashboard, what it shows, how to start
Why
A quick commerce app promises groceries in about 10 minutes. The owner must see speed, basket size and cancellations every day. Looking at 1,800 rows one by one is slow. A dashboard turns them into a few clear numbers.
What
The dashboard answers questions like these:
- Total orders: How many orders customers placed (delivered + cancelled).
- GMV (basket value): Gross Merchandise Value: total basket value of delivered orders, before discount.
- Avg order value: AOV: the average basket of one delivered order.
- Cancellation rate: Cancelled orders as a share of all orders.
How
- Download blinkit-dashboard-template.xlsx.
- Open it in Excel. Click Enable Editing if Excel asks.
- Stay on the first sheet, Dashboard.
- Read the 15 cards from left to right, top to bottom.
- Then change one drop-down in row 6 and watch the numbers move.
2. What is inside the workbook
Why
Each sheet has one job. When you know the job, you know where to look and what not to touch.
What
| Sheet | What it holds |
|---|---|
| Dashboard | 15 KPI cards, 3 yellow drop-down filters, 6 charts and a Top 5 table. |
| Data | The example rows, one row per order. The last column, Inc, is a formula. |
| Calc | Small helper tables (by month, by city and so on) that feed the charts. |
| Rules & Instructions | How to use it, what each KPI means, data rules, how to add data, do's and don'ts. |
| Formulas used | Every formula in the file, cell by cell, with what it does. |
| Lists | The values shown in each drop-down list. |
The Data sheet has these columns: OrderID, Date, Month, City, DarkStore, Slot, Category, Items, Basket, Discount, DeliveryFee, NetRevenue, Minutes, Status, Rider, Rating, Customer, Payment and Inc.
How
- Click each sheet tab at the bottom once.
- On Data, press Ctrl+Down to see the last row.
- On Rules & Instructions, read section 3 (data rules) before you type anything.
- On Formulas used, find any formula you want to learn.
3. The 15 KPIs: what each one means
Why
KPI means Key Performance Indicator: one number that tells you if the business is doing well. A KPI is useful only if everyone reads it the same way.
What
Example values are for all rows (every filter set to All). In the formulas, Data[Column] means that whole column on the Data sheet; in the workbook it is written as a range like Data!$B$2:$B$1801.
| KPI | What it means | Formula (Dashboard cell) | Example value |
|---|---|---|---|
| Total orders | How many orders customers placed (delivered + cancelled). | =COUNTIFS(Data[Inc],1)Dashboard!B9 |
1,800 |
| Delivered orders | Orders that reached the customer. | =COUNTIFS(Data[Inc],1,Data[Status],"Delivered")Dashboard!E9 |
1,713 |
| GMV (basket value) | Gross Merchandise Value: total basket value of delivered orders, before discount. | =SUMIFS(Data[Basket],Data[Inc],1,Data[Status],"Delivered")Dashboard!H9 |
₹5,37,560 |
| Net revenue | Money kept: basket minus discount plus delivery fee, delivered orders only. | =SUMIFS(Data[NetRevenue],Data[Inc],1)Dashboard!K9 |
₹5,19,544 |
| Avg order value | AOV: the average basket of one delivered order. Target rule: card turns green when the value is ≥ 300. | =IFERROR(SUMIFS(Data[Basket],Data[Inc],1,Data[Status],"Delivered")/COUNTIFS(Data[Inc],1,Data[Status],"Delivered"),0)Dashboard!N9 |
₹314 |
| Avg delivery time | Average minutes from order to doorstep. Target rule: card turns red when the value is > 12. | =IFERROR(AVERAGEIFS(Data[Minutes],Data[Inc],1,Data[Status],"Delivered"),0)Dashboard!B13 |
12.9 min |
| Delivered in ≤10 min | The quick-commerce promise: share of orders delivered in 10 minutes or less. Target rule: card turns green when the value is ≥ 0.4. | =IFERROR(COUNTIFS(Data[Inc],1,Data[Status],"Delivered",Data[Minutes],"<=10")/COUNTIFS(Data[Inc],1,Data[Status],"Delivered"),0)Dashboard!E13 |
23.6% |
| Late (>15 min) | Share of delivered orders that took more than 15 minutes. Target rule: card turns red when the value is > 0.15. | =IFERROR(COUNTIFS(Data[Inc],1,Data[Status],"Delivered",Data[Minutes],">15")/COUNTIFS(Data[Inc],1,Data[Status],"Delivered"),0)Dashboard!H13 |
22.5% |
| Cancellation rate | Cancelled orders as a share of all orders. Target rule: card turns red when the value is > 0.05. | =IFERROR(COUNTIFS(Data[Inc],1,Data[Status],"Cancelled")/COUNTIFS(Data[Inc],1),0)Dashboard!K13 |
4.8% |
| Avg rating | Average customer star rating for delivered orders. Target rule: card turns green when the value is ≥ 4.5. | =IFERROR(AVERAGEIFS(Data[Rating],Data[Inc],1,Data[Status],"Delivered"),0)Dashboard!N13 |
4.51 ★ |
| Discount % of GMV | How much of GMV was given away as discount. Target rule: card turns red when the value is > 0.08. | =IFERROR(SUMIFS(Data[Discount],Data[Inc],1,Data[Status],"Delivered")/SUMIFS(Data[Basket],Data[Inc],1,Data[Status],"Delivered"),0)Dashboard!B17 |
6.0% |
| Items per order | Average number of items in one delivered order. | =IFERROR(SUMIFS(Data[Items],Data[Inc],1,Data[Status],"Delivered")/COUNTIFS(Data[Inc],1,Data[Status],"Delivered"),0)Dashboard!E17 |
4.3 |
| Repeat customers | Orders from customers who ordered before. Target rule: card turns green when the value is ≥ 0.7. | =IFERROR(COUNTIFS(Data[Inc],1,Data[Customer],"Repeat")/COUNTIFS(Data[Inc],1),0)Dashboard!H17 |
70.9% |
| Peak-slot share | Share of orders in the busiest slot (18-22). | =IFERROR(COUNTIFS(Data[Inc],1,Data[Slot],"Peak 18-22")/COUNTIFS(Data[Inc],1),0)Dashboard!K17 |
33.9% |
| UPI share | Share of orders paid by UPI. | =IFERROR(COUNTIFS(Data[Inc],1,Data[Payment],"UPI")/COUNTIFS(Data[Inc],1),0)Dashboard!N17 |
69.1% |
How
- Read the small grey line under each card: it says what the card counts.
- A green card meets its target rule. A red card needs attention.
- Click a card and look at the formula bar to see the real formula.
- Change a filter, for example City = Pune, and see which cards turn red or green.
4. The drop-down filters
Why
A total for the whole business hides problems. Filters let you look at one City, one Month or one Category at a time.
What
Row 6 has three yellow cells with drop-down lists: City, Month and Category. Each list starts with All. The Data sheet has one extra column, Inc (include). Its formula gives 1 when the row matches all three filters, otherwise 0:
=IF(AND(OR(Dashboard!$C$6="All",D2=Dashboard!$C$6),OR(Dashboard!$F$6="All",C2=Dashboard!$F$6),OR(Dashboard!$I$6="All",G2=Dashboard!$I$6)),1,0)
Every KPI and chart uses Data[Inc],1 as its first condition, so only matching rows are counted.
How
- Click the yellow cell next to City.
- Click the small arrow and pick a value.
- Look at the line 'Rows in view' to see how many rows match.
- Pick All to remove that filter.
- Set all three back to All before you save.
5. The charts and the Top 5 table
Why
Numbers tell you how much. Charts show you where and when: which month dropped, which city leads.
What
- GMV and orders by month
- GMV share by category
- GMV by city
- Orders and avg minutes by slot
- How fast orders arrive
- Cancellation % by city
- Table: Top 5 dark stores by GMV (uses INDEX, MATCH and LARGE)
Each chart reads a small table on the Calc sheet. Those tables also use the Inc column, so the charts follow the filters.
How
- Point at a bar or line to see its exact value.
- To see where a chart's numbers come from, right-click it and choose Select Data.
- Open the Calc sheet and find the table with the same title.
- Do not type in Calc; it is all formulas.
6. How to add new data
Why
A dashboard is only useful if you keep feeding it. Adding rows the wrong way breaks totals without any error.
What
| Column | What it holds | Rule |
|---|---|---|
OrderID |
Unique order number | Never repeat an ID |
Date / Month |
Order date and its short month | Month must be Jan..Jun as in Lists |
City / DarkStore |
Where the order was packed | City from the allowed list; store as '<City> DS-<n>' |
Slot |
Time band of the order | One of the 5 slot names |
Category |
Main category of the basket | One of the 7 categories |
Items, Basket |
Item count and basket value in ₹ | Whole numbers, no text |
Discount, DeliveryFee |
₹ discount given and ₹ fee charged (₹25 below ₹199 in this example) | 0 when none |
NetRevenue |
Basket - Discount + DeliveryFee; 0 if cancelled | Typed value in this example data |
Minutes, Rating |
Delivery minutes and 1-5 star rating | Leave BLANK for cancelled orders (AVERAGEIFS skips blanks) |
Status |
Delivered or Cancelled | Exact spelling |
Rider, Customer, Payment |
Rider code, New/Repeat, UPI/Card/Cash | Exact spelling |
How
- Go to the first empty row under the Data table.
- Type or paste the new rows. Keep the same spelling as the lists (for example Pune).
- Check that Inc filled down by itself (it shows 1 or 0).
- The formulas read rows 2 to 1801. If your data goes past row 1801, use Find & Replace on the Dashboard and Calc sheets to change 1801 to your new last row.
- Press F9 if numbers do not update, then set the filters to All and compare totals.
Use it in 3 steps
1) Open the Dashboard sheet. 2) Pick a value in a yellow cell in row 6, like City = Pune. 3) Read the cards: green is good, red needs attention.
3 steps मध्ये वापरा
1) Dashboard sheet उघडा. 2) Row 6 मधल्या पिवळ्या cell मध्ये value निवडा, उदा. City = Pune. 3) Cards वाचा: हिरवा म्हणजे चांगलं, लाल म्हणजे लक्ष द्या.
3 steps में इस्तेमाल करें
1) Dashboard sheet खोलें. 2) Row 6 के पीले cell में value चुनें, जैसे City = Pune. 3) Cards पढ़ें: हरा मतलब अच्छा, लाल मतलब ध्यान दें.
7. Formulas used
This is the same list as the 'Formulas used' sheet. A formula marked 'copied down' is the same in the rows below it.
| Cell | Formula | What it does |
|---|---|---|
| Data!S2 | =IF(AND(OR(Dashboard!$C$6="All",D2=Dashboard!$C$6),OR(Dashboard!$F$6="All",C2=Dashboard!$F$6),OR(Dashboard!$I$6="All",G2=Dashboard!$I$6)),1,0) |
Inc flag: 1 when the row matches every Dashboard filter (copied down every row) |
| Dashboard!K6 | ="Rows in view: "&TEXT(SUM(Data!$S$2:$S$1801),"#,##0")&" of 1,800 | Yellow cells = drop-down filters" |
Counts rows in view |
| Dashboard!B9 | =COUNTIFS(Data!$S$2:$S$1801,1) |
KPI: Total orders |
| Dashboard!E9 | =COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered") |
KPI: Delivered orders |
| Dashboard!H9 | =SUMIFS(Data!$I$2:$I$1801,Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered") |
KPI: GMV (basket value) |
| Dashboard!K9 | =SUMIFS(Data!$L$2:$L$1801,Data!$S$2:$S$1801,1) |
KPI: Net revenue |
| Dashboard!N9 | =IFERROR(SUMIFS(Data!$I$2:$I$1801,Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered")/COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered"),0) |
KPI: Avg order value |
| Dashboard!B13 | =IFERROR(AVERAGEIFS(Data!$M$2:$M$1801,Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered"),0) |
KPI: Avg delivery time |
| Dashboard!E13 | =IFERROR(COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered",Data!$M$2:$M$1801,"<=10")/COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered"),0) |
KPI: Delivered in ≤10 min |
| Dashboard!H13 | =IFERROR(COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered",Data!$M$2:$M$1801,">15")/COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered"),0) |
KPI: Late (>15 min) |
| Dashboard!K13 | =IFERROR(COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Cancelled")/COUNTIFS(Data!$S$2:$S$1801,1),0) |
KPI: Cancellation rate |
| Dashboard!N13 | =IFERROR(AVERAGEIFS(Data!$P$2:$P$1801,Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered"),0) |
KPI: Avg rating |
| Dashboard!B17 | =IFERROR(SUMIFS(Data!$J$2:$J$1801,Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered")/SUMIFS(Data!$I$2:$I$1801,Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered"),0) |
KPI: Discount % of GMV |
| Dashboard!E17 | =IFERROR(SUMIFS(Data!$H$2:$H$1801,Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered")/COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered"),0) |
KPI: Items per order |
| Dashboard!H17 | =IFERROR(COUNTIFS(Data!$S$2:$S$1801,1,Data!$Q$2:$Q$1801,"Repeat")/COUNTIFS(Data!$S$2:$S$1801,1),0) |
KPI: Repeat customers |
| Dashboard!K17 | =IFERROR(COUNTIFS(Data!$S$2:$S$1801,1,Data!$F$2:$F$1801,"Peak 18-22")/COUNTIFS(Data!$S$2:$S$1801,1),0) |
KPI: Peak-slot share |
| Dashboard!N17 | =IFERROR(COUNTIFS(Data!$S$2:$S$1801,1,Data!$R$2:$R$1801,"UPI")/COUNTIFS(Data!$S$2:$S$1801,1),0) |
KPI: UPI share |
| Calc!B5 | =COUNTIFS(Data!$S$2:$S$1801,1,Data!$D$2:$D$1801,$A5) |
By city: Orders for Pune (copied down) |
| Calc!C5 | =SUMIFS(Data!$I$2:$I$1801,Data!$S$2:$S$1801,1,Data!$D$2:$D$1801,$A5,Data!$N$2:$N$1801,"Delivered") |
By city: GMV for Pune (copied down) |
| Calc!D5 | =IFERROR(AVERAGEIFS(Data!$M$2:$M$1801,Data!$S$2:$S$1801,1,Data!$D$2:$D$1801,$A5,Data!$N$2:$N$1801,"Delivered"),0) |
By city: Avg minutes for Pune (copied down) |
| Calc!E5 | =IFERROR(COUNTIFS(Data!$S$2:$S$1801,1,Data!$D$2:$D$1801,$A5,Data!$N$2:$N$1801,"Cancelled")/B5,0) |
By city: Cancel % for Pune (copied down) |
| Calc!B15 | =SUMIFS(Data!$I$2:$I$1801,Data!$S$2:$S$1801,1,Data!$C$2:$C$1801,$A15,Data!$N$2:$N$1801,"Delivered") |
By month: GMV for Jan (copied down) |
| Calc!C15 | =SUMIFS(Data!$L$2:$L$1801,Data!$S$2:$S$1801,1,Data!$C$2:$C$1801,$A15) |
By month: Net revenue for Jan (copied down) |
| Calc!D15 | =COUNTIFS(Data!$S$2:$S$1801,1,Data!$C$2:$C$1801,$A15) |
By month: Orders for Jan (copied down) |
| Calc!B25 | =SUMIFS(Data!$I$2:$I$1801,Data!$S$2:$S$1801,1,Data!$G$2:$G$1801,$A25,Data!$N$2:$N$1801,"Delivered") |
By category: GMV for Fruits & Veg (copied down) |
| Calc!C25 | =COUNTIFS(Data!$S$2:$S$1801,1,Data!$G$2:$G$1801,$A25) |
By category: Orders for Fruits & Veg (copied down) |
| Calc!D25 | =SUMIFS(Data!$J$2:$J$1801,Data!$S$2:$S$1801,1,Data!$G$2:$G$1801,$A25,Data!$N$2:$N$1801,"Delivered") |
By category: Discount for Fruits & Veg (copied down) |
| Calc!B36 | =COUNTIFS(Data!$S$2:$S$1801,1,Data!$F$2:$F$1801,$A36) |
By time slot: Orders for Morning 6-10 (copied down) |
| Calc!C36 | =IFERROR(AVERAGEIFS(Data!$M$2:$M$1801,Data!$S$2:$S$1801,1,Data!$F$2:$F$1801,$A36,Data!$N$2:$N$1801,"Delivered"),0) |
By time slot: Avg minutes for Morning 6-10 (copied down) |
| Calc!B45 | =CHOOSE(MATCH($A45,{"≤8 min","9-10 min","11-12 min","13-15 min",">15 min"},0),COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered",Data!$M$2:$M$1801,"<=8"),COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered",Data!$M$2:$M$1801,">=9",Data!$M$2:$M$1801,"<=10"),COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered",Data!$M$2:$M$1801,">=11",Data!$M$2:$M$1801,"<=12"),COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered",Data!$M$2:$M$1801,">=13",Data!$M$2:$M$1801,"<=15"),COUNTIFS(Data!$S$2:$S$1801,1,Data!$N$2:$N$1801,"Delivered",Data!$M$2:$M$1801,">15")) |
Delivery-time bands (delivered orders): Orders for ≤8 min (copied down) |
| Calc!B54 | =LEFT($A54,LEN($A54)-5) |
By dark store: City for Pune DS-1 (copied down) |
| Calc!C54 | =SUMIFS(Data!$I$2:$I$1801,Data!$S$2:$S$1801,1,Data!$E$2:$E$1801,$A54,Data!$N$2:$N$1801,"Delivered") |
By dark store: GMV for Pune DS-1 (copied down) |
| Calc!D54 | =COUNTIFS(Data!$S$2:$S$1801,1,Data!$E$2:$E$1801,$A54) |
By dark store: Orders for Pune DS-1 (copied down) |
| Calc!E54 | =IFERROR(AVERAGEIFS(Data!$M$2:$M$1801,Data!$S$2:$S$1801,1,Data!$E$2:$E$1801,$A54,Data!$N$2:$N$1801,"Delivered"),0) |
By dark store: Avg minutes for Pune DS-1 (copied down) |
| Calc!F54 | =IFERROR(AVERAGEIFS(Data!$P$2:$P$1801,Data!$S$2:$S$1801,1,Data!$E$2:$E$1801,$A54,Data!$N$2:$N$1801,"Delivered"),0) |
By dark store: Avg rating for Pune DS-1 (copied down) |
| Calc!G54 | =C54+ROW()/100000 |
By dark store: Rank key for Pune DS-1 (copied down) |
| Dashboard!D55 | =IFERROR(INDEX(Calc!$A$54:$A$71,MATCH(LARGE(Calc!$G$54:$G$71,$B55),Calc!$G$54:$G$71,0)),"-") |
Top 5 dark stores by GMV: column 'Dark store' (copied down) |
| Dashboard!F55 | =IFERROR(INDEX(Calc!$B$54:$B$71,MATCH(LARGE(Calc!$G$54:$G$71,$B55),Calc!$G$54:$G$71,0)),"-") |
Top 5 dark stores by GMV: column 'City' (copied down) |
| Dashboard!H55 | =IFERROR(INDEX(Calc!$C$54:$C$71,MATCH(LARGE(Calc!$G$54:$G$71,$B55),Calc!$G$54:$G$71,0)),"-") |
Top 5 dark stores by GMV: column 'GMV' (copied down) |
| Dashboard!J55 | =IFERROR(INDEX(Calc!$D$54:$D$71,MATCH(LARGE(Calc!$G$54:$G$71,$B55),Calc!$G$54:$G$71,0)),"-") |
Top 5 dark stores by GMV: column 'Orders' (copied down) |
| Dashboard!L55 | =IFERROR(INDEX(Calc!$E$54:$E$71,MATCH(LARGE(Calc!$G$54:$G$71,$B55),Calc!$G$54:$G$71,0)),"-") |
Top 5 dark stores by GMV: column 'Avg minutes' (copied down) |
| Dashboard!N55 | =IFERROR(INDEX(Calc!$F$54:$F$71,MATCH(LARGE(Calc!$G$54:$G$71,$B55),Calc!$G$54:$G$71,0)),"-") |
Top 5 dark stores by GMV: column 'Avg rating' (copied down) |
8. Common mistakes
| Mistake | What goes wrong | Fix |
|---|---|---|
| Typing ₹ or a comma as text in a number cell | SUMIFS and AVERAGEIFS skip text, so totals become too small. | Type only the number. The cell format adds ₹. |
| A different spelling, like an extra space after a name | The row never matches the City filter or the Calc tables. | Copy values from the Lists sheet, or use Data Validation. |
| Averaging the per-row values to get Avg order value | An average of averages gives the wrong answer. | Divide totals, as the KPI formula does: =IFERROR(SUMIFS(Data[Basket],Data[Inc],1,Data[Status],"Delivered")/COUNTIFS(Data[Inc],1,Data[Status],"Delivered"),0) |
| Adding rows below row 1801 and not updating the ranges | New rows are left out of every KPI. | Update the last row number in the formulas (see step 4 above). |
| Typing over a KPI card or the Inc column | The formula is lost and the card stops changing. | Press Ctrl+Z, or copy the formula back from the 'Formulas used' sheet. |
| Showing these numbers as real company results | This is example data, not Blinkit data. | Always say 'example data' when you share a screenshot. |
9. FAQ
How do I calculate Avg order value in Excel?
AOV: the average basket of one delivered order. The workbook uses =IFERROR(SUMIFS(Data[Basket],Data[Inc],1,Data[Status],"Delivered")/COUNTIFS(Data[Inc],1,Data[Status],"Delivered"),0) in Dashboard!N9.
How do I calculate Discount % of GMV in Excel?
How much of GMV was given away as discount. Formula: =IFERROR(SUMIFS(Data[Discount],Data[Inc],1,Data[Status],"Delivered")/SUMIFS(Data[Basket],Data[Inc],1,Data[Status],"Delivered"),0).
How do the drop-down filters change every KPI?
Each Data row has an Inc formula. It gives 1 when the row matches all three drop-downs (City, Month, Category), or the drop-down says All. Every KPI counts only rows where Inc = 1.
Is this real Blinkit data?
No. All 1,800 rows are made up for practice. The colours are only inspired by the brand. It is not an official Blinkit report.
Which Excel version do I need?
Excel 2010 or newer works, because the file uses COUNTIFS, SUMIFS, AVERAGEIFS, IFERROR, INDEX and MATCH. We checked it in LibreOffice Calc with zero errors.
10. Practice tasks
- Set City = Pune. Write down the new value of GMV (basket value).
- Which month is highest in the chart 'GMV and orders by month'?
- Add one new row to the Data sheet and check that Total orders changes.
- Change one target rule in Conditional Formatting (Home › Conditional Formatting › Manage Rules) and watch the card colour.
Remember
KPI cards, the Calc sheet and the Inc column hold formulas, so never type on them. Add new data only under the Data table, with the same spellings.
लक्षात ठेवा
KPI cards, Calc sheet आणि Inc column मध्ये formulas आहेत, त्यावर काही type करू नका. नवीन data फक्त Data table च्या खाली, त्याच spelling ने जोडा.
याद रखें
KPI cards, Calc sheet और Inc column में formulas हैं, उन पर कुछ type न करें. नया data सिर्फ Data table के नीचे, उसी spelling के साथ जोड़ें.
Related: all Excel dashboards · Excel dashboards chapter · SUMIFS, COUNTIFS and AVERAGEIFS · KPI cards in Excel
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- Total parcels (Easy): Add up Parcels in D2:D11.
- Average cost (Easy): Average of E2:E11, rounded to 2 decimals.
- Rows in Royal Mail (Easy): How many rows have Carrier "Royal Mail"?
- Largest parcels (Easy): The largest value in D2:D11.
- Parcels for Royal Mail (Medium): Total of D2:D11 where B is "Royal Mail".
- Royal Mail in Glasgow (Medium): Total of D2:D11 where B is "Royal Mail" and C is "Glasgow".
- Best in Royal Mail (Medium): Largest E2:E11 value where B is "Royal Mail".
- Value of row 2 (Medium): D2 times E2.
- Look up Priya Kulkarni (Medium): The Parcels for "Priya Kulkarni" (use a lookup on column A).
- Total value (Hard): Sum of D times E for all rows.
- Share of Royal Mail (Hard): Share of D2:D11 that is "Royal Mail", rounded to 3 decimals.
- Rank of row 2 (Hard): Rank of D2 among D2:D11 (largest = 1).
- Above average? (Hard): "Above" if E2 is above the average of E2:E11, else "Below".