Premise of Test: Hot Air Balloon Tours in Cappadocia/Turkey

Hot air ballooning is a major tourist attraction in Cappadocia, Turkey. Groups of 8 to 15 people gather early each morning to board hot air balloons that float over the region’s unique landscape. These balloons use propane gas to heat air and lift off, providing passengers with a bird’s eye view of nature’s beauty.

This lesson presents an analytical test scenario based on the 2014 customer and flight data of a travel agency that organizes daily balloon trips. The agency operates a website where customers book their rides. Each balloon is managed by an operator who partners with the agency to make their balloons available for booking.

The dataset includes daily records with the following key columns:

• Date: The date of the record.
• Day: The day of the week for the date.
• Visitors: Number of visitors to the agency’s booking website that day.
• Balloons available: Number of balloons made available by operators on that day.
• Reservations: Number of bookings made for balloon rides that day. Each balloon can make multiple flights daily.
• Actualized: Number of customers who paid and took the flight. Some reservations are canceled.
• Capacity: Total passenger capacity available across all balloons that day.
• Color: Dominant color of the balloons available on that day.

Your task is to analyze this data to answer operational and business questions that simulate real product management challenges in a marketplace setting.

Understanding the Business Context and Data Signals

The travel agency’s business depends on matching supply (balloons and operators) with demand (customers booking rides). The data shows daily fluctuations in website traffic, balloon availability, reservations, and actual rides completed.

Visitors to the website indicate the potential demand funnel. Not all website visitors convert to bookings, but this number sets an upper bound on interest.

Balloons available and capacity represent the supply side. Capacity is the sum of all balloons’ passenger limits. Since balloons can fly multiple times per day, capacity is a flexible but finite resource.

Reservations reflect demand converted to intent to purchase. However, some reservations do not convert to actual flights — cancellations or no-shows lower the actualized count.

The color attribute, while seemingly cosmetic, can be used to segment data and identify patterns related to balloon fleets or operator groups.

Your analytical approach should consider these relationships and how they affect key business decisions: pricing, operator management, demand forecasting, and customer satisfaction.

The Demand-Supply Relationship and Capacity Constraints

A core question is: how well does supply meet demand on any given day?

You will see that demand spikes on weekends and holidays. Operators can increase the number of flights per day to meet demand, but their capacity and operational constraints limit total supply.

Understanding cancellation rates (the ratio of actualized to reservations) helps forecast true demand and optimize balloon availability.

Analyzing capacity per visitor ratios can reveal days when supply is scarce relative to interest, signaling opportunities for adding balloons or adjusting pricing.

Pricing Strategy: Surge Pricing on Peak Demand Days

The agency considers implementing a 25% price increase on weekends and holidays to balance supply and demand — similar to surge pricing used by ride-hailing platforms like Uber.

This pricing leverages demand elasticity: higher prices reduce demand but increase revenue per unit.

To decide whether to increase prices, the agency must analyze:

• Reservation volumes and conversion rates on peak days.
• Total passenger capacity available.
• External factors like weather forecasts affecting flight feasibility.
• Flight duration and operator capacity utilization.

Price increases should not discourage bookings excessively, or they risk losing customers to competitors.

Seasonal Effects and Operational Planning

Winter is the low season due to poor weather conditions. Data shows declines in flights, earnings, and website visitors during winter months.

However, the ratio of actualizations to reservations does not necessarily drop. This means cancellations may not increase even when demand falls.

Operators often take months off during winter, impacting annual capacity and revenue.

Planning staffing and maintenance schedules around these seasonal trends is critical for cost optimization.

Operator Performance and Customer Service Considerations

When deciding whether to continue working with an operator who receives complaints, the agency must weigh multiple factors:

• Total revenue generated by the operator.
• Number of flights completed daily.
• Number of days worked weekly.
• Total passengers served.
• Details and severity of customer complaints.

From a customer service perspective, complaint details are the most important. Revenue figures are less relevant if complaints indicate poor safety or experience.

Balancing operator earnings with service quality ensures sustainable business growth.

Weekend and Holiday Demand Patterns

On weekends and holidays, the data consistently shows:

• Increase in the number of reservations.
• Increase in the number of flights performed.
• Potential changes in customer satisfaction, often under pressure due to higher volumes.

Understanding these patterns helps in resource planning, pricing, and customer communication strategies.

Sample Analytical Questions and Reasoning

Here are examples of typical analytical questions you may encounter, along with the reasoning approach.

Question: Average Reservations Per Month

Calculate the average number of reservations per month from the dataset.

• Sum the daily reservations for each month.
• Divide by the number of days in that month.
• Compare across months to identify seasonality.

Question: Dominant Balloon Color Frequency

Identify which balloon color appears most frequently as the dominant color throughout the year.

• Count occurrences of each color in the dataset.
• The color with the highest count indicates the most common fleet color.

Question: Best Day to Add Balloons in May

To increase capacity in May, determine which day of the week would benefit most from adding 5 balloons.

• Analyze reservations and capacity by day of the week.
• Identify the day with the highest ratio of reservations to capacity.
• Adding balloons on that day maximizes incremental revenue.

Question: Impact of Price Reductions on Revenue

Given two balloons with different price reductions and expected flight increases, calculate the net revenue change.

• Compute original revenue: price × flights.
• Compute post-promotion revenue: discounted price × increased flights.
• Compare totals to find net gain or loss.

Question: Flight Duration and Propane Gas Cost

Estimate which operator spends more on propane gas weekly.

• Propane cost depends on flight duration and number of flights.
• Days worked per week affect total weekly use.
• Passenger age does not significantly impact propane consumption.

Question: Operator Annual Earnings

Calculate net annual earnings for an operator given:

• Price per flight.
• Operating costs (propane, amenities).
• Work schedule (flights per day, days per week).
• Seasonal breaks (months off).

Multiply net profit per flight by total flights per year to get annual earnings.

Question: Investment Payback for New Balloon

Determine the gross earnings per flight needed to recover the cost of a new balloon in one year.

• Calculate total flights per year.
• Divide investment cost by total flights to find required additional earnings per flight.
• Add operating expenses per flight to get total gross earnings target.

Test Yourself: Analyzing Weekend Demand and Pricing

Imagine you are the product manager for this travel agency. A holiday is approaching, and demand is expected to spike.

• How would you decide whether to implement a 25% price increase on balloon flights?
• Which data points would you prioritize for this decision?
• What external factors might influence your recommendation?

Use the dataset to analyze reservation trends, capacity, and historical pricing effects on weekends and holidays.

Field Exercise: Exploring the Balloon Data

Take 20 minutes to explore the 2014 dataset using Excel or your preferred tool.

1. Calculate monthly averages for visitors, reservations, and actualized flights.
2. Identify the day of the week with the lowest actualized reservations for potential weekly closure.
3. Analyze cancellation rates by month and season.
4. Evaluate how dominant balloon colors correlate with demand or capacity.
5. Model the impact of adding balloons on different days to optimize revenue.

This hands-on practice builds the analytical muscle needed to interpret marketplace data and make operational decisions.

From the Field

When I have presented this test scenario to PM candidates, I see a consistent pattern: they focus heavily on raw numbers but miss the operational context behind them. The actual job is to use data to tell a story about supply, demand, and customer behavior — then make recommendations that balance business goals with customer satisfaction.

This is what week one looks like for most new PMs facing marketplace data. Your actual job is to cut through noise and make decisions that keep the operation profitable and customers happy.

Test yourself: Balloon Operator Promotion Scenario

PL alumni have used this test scenario to sharpen their analytical thinking and marketplace intuition.

Where to go next

• Develop your data storytelling skills: Data-Driven Product Decisions
• Master pricing strategy fundamentals: Pricing and Monetization
• Learn to analyze marketplace operations: Marketplace Product Management
• Build your Excel and SQL expertise: Data Skills for PMs
• Prepare for PM interviews with case studies: Interview Case Studies