8 Must-Read E-Commerce Case Studies for 2024

It’s no secret that the world of e-commerce is booming. While brick-and-mortar retail is going through challenging times due to the COVID-19 pandemic, some e-commerce categories are seeing a surge in sales, including food and beverage, personal care, and home fitness. With that success comes a slew of employment opportunities in the e-commerce space.

These e-commerce case study questions are applicable to interviews for a variety of roles including marketing analytics, business intelligence, data science, and any type of strategic role that relates to attracting and retaining customers for an online brand.

E-commerce case studies are generally scenario-based questions that ask you to work through a solution to a proposed business or marketing problem for an e-commerce brand.

Your job is to ask the interviewer for more information, make assumptions about the case, propose a solution, and ultimately consider the trade-offs of your solution. Case study interview questions aim to assess five major qualities:

• Logical, structured thinking - Can you structure complex problems in a clear, simple way?
• Analytical problem solving - Can you read, interpret, and analyze data well?
• Business acumen - Do you have sound business judgment and intuition?
• Communication skills - Can you communicate clearly, concisely, and articulately?
• Personality and cultural fit - Are you coachable and easy to work with?

Case study interviews effectively screen candidates because they assess these qualities in just a 30- to 45-minute exercise.

Let’s take a look at some of the top answers to e-commerce case study interview questions:

An e-commerce company has experienced a reduction in revenue for the past 12 months. What would you investigate to understand exactly where the revenue loss is occurring?

To investigate the revenue decline, you have access to information like:

• Date of sale
• Amount paid by customers
• Profit margin per unit
• Quantity of item
• Item category
• Item subcategory
• Marketing attribution source
• Percent discount applied

An e-commerce case study like this is asked during marketing analytics interviews to determine if you can propose strong metrics to investigate a problem. You might start by investigating monthly revenue by marketing source, category/subcategory, or by the percent of the discount applied.

This analysis will help you understand if the decline is due to decreasing marketing efficiency, an overreliance on discounts, or if a particular category is declining. You could also investigate changes in profit margin per unit, which could help you identify if production costs are rising.

You work for a SAAS business. To catch up to end-of-quarter revenue goals, would you send an email blast to your entire customer list?

Broadly speaking, sending a mass email blast to a list of customers is generally not a good idea, especially when the objective of the email is to increase sales.

A better solution is to segment the audience and personalize the messaging by the audience. For example, if a customer was about to reach their licensing limit, you could send a personalized offer to add more licenses, whereas a win-back campaign could be used for recently churned users.

You work for a 14-month-old SAAS company. You’re asked to calculate the average customer lifetime value. How would you do it?

For more context, you know that the product costs $100, there’s an average 10% monthly churn, and the average customer’s lifetime is 3.5 months.

Average lifetime value is defined by the prediction of the net revenue attributed to the entire future relationship with all customers averaged. Given that you don’t know the future net revenue, you can estimate it by taking the total amount of revenue generated divided by the total number of customers acquired over the same period of time.

However, there’s a catch: it’s only a 14-month-old company. As a result, the average customer length is biased, because the company hasn’t existed long enough to correctly measure a sample average that is indicative of the mean.

How would you calculate this? Try to find the expected value of the customer at each month as a multiplier of retention times the product cost.

An e-commerce website’s pricing algorithm is underpricing products. What steps would you take to diagnose the problem?

See a full solution to this question on YouTube:

You want to remove duplicate product names from a very large e-commerce database. How would you go about doing this?

More context: the duplicates may be listed under different sellers, names, etc. For example, “iPhone X” and “Apple iPhone 10” are two names that refer to the same iPhone.

See a full mock interview solution for this e-commerce case study question on YouTube:

A revised new-user email journey boosts conversion rates for an e-commerce store from 40% to 43%. However, a few months prior, CVR was 45%. How would you investigate whether the new email journey caused the increase in CVR?

See a step-by-step solution to this problem on YouTube:

A company puts you in charge of designing its end-to-end architecture, so you need to know what significant factors you’ll need to consider. What clarifying questions would you ask, and what kind of end-to-end architecture would you design for this company (both for ETL and reporting)?

More context: Vendors can send products to the company’s warehouse to be listed on the website. Users are able to order any in-stock products and submit returns for refunds if they’re not satisfied.

The front end of the website includes a vendor portal that provides sales data in daily, weekly, monthly, quarterly, and yearly intervals.

This question evaluates a candidate’s understanding of aligning technical solutions with business goals, proficiency in data tools, and capability to build systems handling increasing data volumes. The question also examines their approach to data quality, integration, and compliance with privacy regulations.

What business health metrics would you care about tracking on a company dashboard that sells socks?

In this scenario, there are high-level metrics we’d want to consider, such as revenue and profitability. Still, since it is an e-commerce business, you also want to consider inventory and service levels.

You’d first want to ask the interviewer who is tracking the business’s health. If our analysts are looking at it, we would want things at a more granular level than if board members are looking at them, for example.

Secondly, to understand the business, we should spend more time thinking about the controllable inputs and see how we can weave that into our response during the interview.