Boost Sales and Restocking Efficiency

Carlos operated 12 coffee vending machines across office buildings. Sales were decent, but he restocked on a fixed schedule—every machine, every other day, same inventory levels. He was wasting money on products that didn't sell and running out of popular items too early. His machines offered 15 drink options, but he had no idea which drinks sold when. He needed data to optimize restocking and maximize revenue per machine.

Carlos hired a data analyst to study sales patterns by time of day. The analyst divided the day into morning (6am-12pm), afternoon (12pm-6pm), and evening (6pm-10pm) and tracked revenue, transaction volume, and drink preferences for each period. The goal was to identify when customers bought most and what they bought, so Carlos could restock smarter.

The data showed afternoon was king. Afternoon generated $50,108 in revenue—the highest of any time block. Morning brought in $39,106, and evening $33,107. Afternoon was prime time for volume-based promotions and heavy restocking. Morning had fewer transactions but higher average order value, meaning customers bought premium drinks. Evening was the slowest period overall.

Drink preferences shifted by time. In the morning, Americano dominated with 350 sales, followed by an Americano variant (232) and Café Latte (145). Customers wanted strong, straightforward coffee to start the day. In the afternoon, Latte took the lead with 335 sales, Americano dropped to second (313), and Café Latte came third (213). Afternoon buyers preferred creamier, milder drinks. Evening followed the afternoon pattern: Latte (233), Americano (205), Café Latte (172).

Some drinks barely sold at all. Irish whiskey, chocolate, mocha chip, caramel with chocolate, and double latte had very low frequencies across all time periods—especially in the evening. These drinks were taking up machine space and inventory dollars without delivering returns. Carlos needed to decide: promote them heavily, reformulate them, or cut them entirely.

Carlos changed his restocking strategy. For morning, he loaded machines heavily with Americano and Americano variants—the proven bestsellers. For afternoon and evening, he shifted the mix toward Lattes and Café Lattes, which dominated those periods. He stopped restocking all 15 drinks equally and started matching inventory to actual demand patterns.

He cut inventory on underperformers. Irish whiskey, chocolate, and double latte got reduced to minimal stock levels. If they didn't start selling within two weeks, he'd remove them completely and free up space for drinks people actually wanted. Mocha chip and caramel with chocolate got one last chance—limited-time promotion during the slowest evening hours to test if marketing could revive them.

Carlos introduced time-specific promotions. "Morning Espresso Kick"—discounted Americano from 6am-10am to capture the early rush. "Latte Lounge Hour"—afternoon combo deals (Latte + snack) from 12pm-3pm when volume was highest. "Smooth Latte Wind-Down"—evening promotion for lighter drinks from 6pm-8pm to boost the slowest period.

He adjusted his restocking schedule. High-traffic afternoon locations got restocked twice daily to avoid sellouts of Latte and Café Latte. Low-traffic evening-only machines got restocked every three days instead of two, reducing unnecessary trips and labor costs. Morning-heavy offices got extra Americano stock but fewer specialty drinks that didn't move.

Carlos didn't know yet if these changes would work—he was implementing them based on the data patterns. The afternoon period generated $50,108, morning $39,106, and evening $33,107. He now had a strategy: match inventory to proven demand instead of stocking everything equally. Heavy Americano inventory for mornings, heavy Latte inventory for afternoons, and reduced overall stock for slow evening locations.

The low-performing drinks posed a decision point. Irish whiskey, chocolate, double latte, mocha chip, and caramel with chocolate sold poorly across all time periods. Carlos planned to test promotions for two weeks. If they still didn't move, he'd remove them and replace those slots with variants of proven sellers—more Americano options for morning, more Latte options for afternoon.

Today, Carlos restocks based on data, not guesswork. Each machine has a custom profile—morning-heavy offices get Americano-focused inventory, afternoon-heavy locations stock Lattes. He tracks which drinks sell when and adjusts accordingly. The goal isn't perfection—it's reducing waste on slow movers and avoiding stockouts on bestsellers. He doesn't know the exact revenue impact yet, but he knows he's ordering smarter and throwing away less unsold product.