Data Visualization

Blog of the Data Visualization & Communication Course at OSB-AUB

This is my favorite part about analytics: Taking boring flat data and bringing it to life through visualization” John Tukey

Consumer Segment Suffers the Sharpest Profit Drop as Discounts Increase

Consumer Segment Suffers the Sharpest Profit Drop as Discounts Increase

Most businesses offer discounts to boost sales and expect profits to follow.
And discounting does increase purchase likelihood for some customers.
But our analysis of sales data from 2019–2023 shows a surprising pattern: as discounts grow, average profit can collapse; especially for the Home office segment.
Therefore, discount strategy needs to be segment-specific and evidence-based to avoid large financial losses.

    • Data: Sales transactions and profit per order, 2019–2023 (segmented: Consumer, Corporate, Home Office).

    • Question: How does average profit change as discount levels increase for each customer segment?

  • X axis: Discount level (0–85%).

  • Y axis: Average profit per order.

  • Each line = a customer segment (Consumer, Corporate, Home Office).

  • At low discounts the segments have stable profits. But past ~50% discount, profits decline. The Consumer line falls the fastest and deepest; at ~85% discount the Consumer segment reaches nearly –$2,000 average profit.

    Insight: Deep discounts have a non-linear, highly negative impact on average profit for the Home office segment. Corporate and Consumer also decline but less steeply.

    Home office often buy lower volumes and purchase lower-margin items; extreme discounts remove the margin buffer and flip the transaction into a loss. Corporate buyers may purchase higher volume or negotiate different terms that preserve margins.

  • Implications:

  • Avoid blanket deep discounts. Limit very large discounts for home office retail segments.

  • Segmented discount rules. Use smaller, controlled discounts for home office; allow negotiated or volume discounts for Corporate accounts where margins hold.

  • Test discount thresholds. Implement A/B tests and monitor profit by segment (use alerts when average profit crosses a risk threshold).

  • Revise loyalty incentives. Consider non-price incentives (bundles, loyalty points) for consumers rather than steep discounts. Discounts drive behavior, but beyond certain thresholds they destroy profit. A segment-aware pricing policy protects margins and keeps promotions profitable.

 

Uneven Outbreaks: Mapping Lebanon’s Waterborne and Foodborne Diseases

Uneven Outbreaks: Mapping Lebanon’s Waterborne and Foodborne Diseases

 

How would you feel if a loved one fell ill from something as preventable as contaminated water or food? For thousands of Lebanese families, this isn’t a hypothetical question. It’s a reality repeated every year.

Between 2015 and 2023, Lebanon has battled three persistent infectious diseases: Food Poisoning, Typhoid Fever, and Viral Hepatitis A. But what the data reveals is not just infection. It’s inequality. Some regions, especially the North and Beqaa, report recurring outbreaks, while others seem untouched. The truth is not that these diseases vanish across borders, but that our systems fail to capture them equally.

Our team’s dashboard brings these hidden patterns to light. By combining national surveillance data across time, region, and age, we uncovered how outbreaks intensified after 2020–particularly Hepatitis A, which surged sharply in the North. Children and teenagers (0–19 years) bear the greatest burden, showing that the threat targets Lebanon’s youngest and most vulnerable. 

But this isn’t just a story of data; it’s a call to action. Interactive (and more sophisticated dashboards) can serve as early-warning systems, alerting public-health officers when abnormal spikes occur and guiding timely interventions such as water testing, vaccination campaigns, or food-safety inspections. When paired with awareness programs in schools and clinics, data becomes protection.

Lebanon has the expertise. What it needs now is integration. A living, public, and transparent system that keeps health information flowing as fast as disease itself, in hopes that, in those times when everyone can see the pattern, everyone will be able to act on it.