How Rahim Saved His Coffee Shop with Statistics (Yes, Really!)

Meet Rahim, the proud owner of Coffee Adda, a charming little café nestled in the heart of Gulshan, Dhaka. A year ago, he opened this café with passion, dreams, and a killer latte recipe. At first, things went great—lines out the door, social media buzz, and the hum of happy customers. But recently, something changed. Sales started to dip. Customers seemed fewer. The cozy café vibes were still there—but the revenue wasn’t. Instead of panicking, Rahim did something many small business owners shy away from—he turned to data. ☕ When the Beans Don’t Lie: Starting with Descriptive Statistics Armed with a notebook, spreadsheet, and a little curiosity, Rahim sat down to analyze his past month's sales. His mission? To understand what was really going on in his shop, beyond the guesswork. He started by organizing the data by time of day: Time Slot | Avg. Cups Sold Morning (8–12) | 70 Afternoon (12–4) | 45 Evening (4–8) | 90 Rahim didn’t stop there. He broke down the sales even further: Most popular coffee: Latte (40% of total sales) Least popular: Espresso (just 10%) Weekly sales trend: Sales spike by 60% on Fridays and Saturdays Peak hour: Evening rush, especially 6 PM to 7:30 PM This part of Rahim’s journey is all about descriptive statistics—the art of summarizing raw data in meaningful ways. He now had answers to questions like: When are customers most active? What are they buying? Are there weekly patterns? Descriptive stats don’t predict the future. But they give you a crystal-clear snapshot of the present. And for Rahim, this was the beginning of a turnaround.

Apr 19, 2025 - 16:42

How Rahim Saved His Coffee Shop with Statistics (Yes, Really!)

Meet Rahim, the proud owner of Coffee Adda, a charming little café nestled in the heart of Gulshan, Dhaka. A year ago, he opened this café with passion, dreams, and a killer latte recipe. At first, things went great—lines out the door, social media buzz, and the hum of happy customers.

But recently, something changed.

Sales started to dip. Customers seemed fewer. The cozy café vibes were still there—but the revenue wasn’t.

Instead of panicking, Rahim did something many small business owners shy away from—he turned to data.

☕ When the Beans Don’t Lie: Starting with Descriptive Statistics

Armed with a notebook, spreadsheet, and a little curiosity, Rahim sat down to analyze his past month's sales. His mission? To understand what was really going on in his shop, beyond the guesswork.

He started by organizing the data by time of day:
Time Slot | Avg. Cups Sold
Morning (8–12) | 70
Afternoon (12–4) | 45
Evening (4–8) | 90

Rahim didn’t stop there. He broke down the sales even further:

Most popular coffee: Latte (40% of total sales)

Least popular: Espresso (just 10%)

Weekly sales trend: Sales spike by 60% on Fridays and Saturdays

Peak hour: Evening rush, especially 6 PM to 7:30 PM

This part of Rahim’s journey is all about descriptive statistics—the art of summarizing raw data in meaningful ways.

He now had answers to questions like:

When are customers most active?

What are they buying?

Are there weekly patterns?

Descriptive stats don’t predict the future. But they give you a crystal-clear snapshot of the present. And for Rahim, this was the beginning of a turnaround.

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