Analyze Subscription, Insurance, App, and Card Cases

You are in a data science and product analytics power-day interview. The following four subcases are independent. For each one, state your assumptions, define the metric or objective, show the formula, compute the answer where data is provided, and make a recommendation. ## 1. Streaming subscription break-even A media company is launching a new paid streaming service. Assume the following year-1 economics: - Fixed product and engineering launch cost: $12,000,000 - Annual content licensing cost: $8,000,000 - Fixed launch marketing cost: $5,000,000 - Subscription price: $12 per paid user per month - App store and payment processing fee: 10% of subscription revenue - Variable streaming and support cost: $2.50 per active paid subscriber-month - Customer acquisition cost: $18 per converted paid subscriber - Monthly paid subscriber churn: 4% - Free-trial-to-paid conversion rate: 60% Tasks: 1. Compute the number of converted paid subscribers needed to break even over the first 12 months. 2. Compute the number of free-trial starts needed to generate that many paid subscribers. 3. Discuss whether the break-even subscriber count is reasonable. 4. If it is not reasonable, propose ways to make the launch economically viable. ## 2. Weather insurance profitability An insurance company is considering a weather insurance product. A customer prepays for 12 months. If a defined weather failure occurs during the year, the customer receives a benefit payment. Product economics: - Premium: $30 per month, prepaid for 12 months - Servicing cost: $3 per customer per month - Benefit paid if weather failure occurs: $8,000 - Regulatory expense: $4 per quarter per policy - Additional regulatory and administrative cost if a benefit is paid: $300 Prospect segments: | Segment | Prospects | Estimated annual weather failure probability | |---|---:|---:| | A | 20,000 | 1.0% | | B | 15,000 | 2.5% | | C | 8,000 | 5.0% | | D | 5,000 | 8.0% | Tasks: 1. What factors would you consider when defining the target customer? 2. What is the maximum annual weather failure probability that still gives nonnegative expected profit per policy? 3. Compute expected profit per policy and total expected profit by segment. 4. Which segments should the company target to maximize expected profit? 5. Explain how you would present the cumulative risk and cumulative profit chart. 6. How could the company responsibly offer a product to high-risk segments C and D? ## 3. Digital app product strategy Choose a digital app you know well. Analyze it as if you were a product manager or product data scientist. Tasks: 1. Describe the app, the core user need, and why users like it. 2. List its major revenue streams. 3. Identify key competitors and the app's competitive advantages. 4. Propose one North Star metric and three supporting key metrics. 5. Discuss tradeoffs and guardrail metrics. 6. Propose six product optimization ideas and explain how you would prioritize and test them. ## 4. Co-branded credit card partnership A bank is considering a co-branded credit card partnership with a retail partner. The bank expects the partnership to increase spending among existing cardholders and acquire new cardholders. Existing cardholder data: | Segment | Existing users | Monthly partner spend before partnership | Monthly partner spend after partnership | |---|---:|---:|---:| | Students | 100,000 | $40 | $55 | | Urban professionals | 60,000 | $120 | $180 | | Travelers | 20,000 | $300 | $420 | Assumptions: - Bank contribution revenue on incremental partner spend: 25% - Bank-funded discount cost on incremental partner spend: 20% - One-time partnership launch cost: $6,000,000 - Each newly acquired cardholder contributes $300 in annual profit before marketing cost Tasks: 1. What patterns do you observe across the three existing-user segments? 2. Compute annual expected profit from incremental spending by existing users. 3. Compute how many new users are needed to break even after accounting for existing-user profit. The bank is also considering a $200,000 marketing campaign that reaches 100,000 eligible prospects. Campaign options: - Option A: Keep the 20% discount. Expected acquisition rate is 12%. - Option B: Reduce the discount to 10%. Expected acquisition rate is 7%. For campaign analysis, assume each acquired user has $300 annual gross contribution before discount cost and $600 annual discount-eligible spend. Tasks: 1. Compare the two campaign options on expected year-1 profit. 2. Which option would you recommend? 3. What assumptions or risks could invalidate the comparison?