Nasi Lemak vs Kopi O Preference

Ahmad owned a traditional Malaysian kopitiam in a busy neighborhood. He served Nasi Lemak, Roti Bakar, Char Kuey Teow, and classic drinks like Kopi O and Teh Tarik. Sales were steady, but he never knew which items actually drove his revenue or how much customers typically spent. He ordered inventory based on gut feeling, overstocked unpopular items, and ran out of bestsellers during peak hours. Ahmad needed data to optimize his menu, inventory, and promotions.

Ahmad hired a data analyst to track customer spending and ordering patterns for several weeks. The analyst examined which items were ordered most frequently, how much customers spent per visit, how many items they ordered per transaction, and which days saw the highest demand. The goal was to identify predictable patterns Ahmad could use for inventory planning, staffing, and targeted promotions.

Customer spending ranged mostly between RM12 and RM20, with a few outliers spending significantly more. Statistical tests confirmed spending didn't follow a normal distribution—most customers clustered in a typical range, while a small minority spent much more. Ahmad realized his core customers were budget-conscious, but he also had a small group of high spenders worth targeting with premium offerings or loyalty rewards.

Kopi O turned out to be a weak seller. Only 16% of customers ordered it. The probability of 3 out of 5 customers ordering Kopi O was just 2.74%—essentially rare. Despite being a kopitiam staple, Kopi O didn't have the universal appeal of Teh Tarik or Kopi C. Ahmad was overstocking it based on tradition, not demand. The data said stop wasting shelf space and ingredient money on an item that barely sold.

Most customers ordered 4 items per transaction on average, with the most common order size being 3 to 5 items. The standard deviation was 1.64, indicating slight variation but high consistency. Ahmad could now plan kitchen prep, portion sizes, and ingredient inventory around the typical 4-item order. He could also design set menus matching this natural purchasing behavior—making ordering easier for customers and operations more efficient.

Nasi Lemak was the king. It had an 82.6% order rate—the highest of any item—with minimal variation (standard deviation: 1.15). Roti Bakar and Char Kuey Teow also showed steady ordering patterns. These weren't seasonal items or trending dishes. They were reliable, predictable revenue drivers. Ahmad could forecast demand confidently, optimize inventory, and reduce waste by planning around these consistent sellers.

Spending thresholds revealed natural customer behavior patterns. 20% of customers spent under RM15, 75% spent under RM30, and 95% spent under RM50. These weren't random numbers—they represented psychological spending boundaries. Ahmad could design promotions around them: value meals at RM15 to capture budget-conscious customers, free drinks for purchases over RM30 to encourage upselling, and loyalty rewards or special offers for spending above RM50 to retain high-value customers.

Nasi Lemak sales peaked on Sundays. Daily demand patterns across other items also followed predictable trends. Ahmad realized he could use these patterns to schedule ingredient deliveries, prep food in advance, and adjust staffing levels. Sundays required more kitchen staff and higher Nasi Lemak inventory. Weekdays needed balanced prep across multiple items. Predictable demand meant operational efficiency—less waste, fewer stockouts, better customer experience.

Ahmad restructured his menu and promotions. He created a RM15 value meal targeting the 20% of customers who spent below that threshold—Roti Bakar with Kopi C, or Nasi Lemak with Teh Tarik. He introduced a "Spend RM30, Get Free Drink" promotion to nudge customers toward the next spending tier. He launched a loyalty card offering a free meal after spending RM50 three times, targeting his high-value customers.

He cut Kopi O inventory by 60% and stopped promoting it. If customers wanted it, they could still order it, but he wasn't pushing a low-demand item anymore. He used the freed-up resources to stock more Teh Tarik and Kopi C—the drinks people actually wanted. He also tested a "Kopi O Happy Hour" promotion during slow morning periods to see if discounting could revive interest. It didn't. Ahmad stopped wasting effort on an item the market didn't want.

He redesigned his Sunday operations. Knowing Nasi Lemak demand spiked on Sundays, Ahmad scheduled an extra cook, increased Nasi Lemak prep by 40%, and launched a Sunday combo deal: Nasi Lemak + Teh Tarik for RM12. The combo matched the typical spending range and the average 4-item order size (2 food items, 2 drinks for a couple or group). Sales increased, waste decreased, and customer satisfaction improved because popular items were always in stock.

Today, Ahmad runs his kopitiam on data, not tradition. Nasi Lemak remains his anchor product, and he plans inventory around predictable demand patterns. He targets promotions at natural spending thresholds instead of guessing what might work. He cut low-demand items and reinvested resources into proven sellers. His operations are more efficient, his customers are happier, and his margins are higher. The data didn't change what he sold—it changed how he sold it.