Decide whether a proposed new grocery store location is worth opening

A grocery delivery and pickup marketplace is weighing whether a proposed new store location is worth opening. In a case study run by two interviewers, you are asked to analyze the question from both the data side and the business side: frame the decision, say which data you would use, estimate whether the location would pay off, and make a recommendation. The report describes the case only as a new-store siting or store-expansion problem in which the candidate judges, from data and business angles, whether a new store location is worth opening. It does not say whose store it is, where the site is, or which data the interviewers provided, so settle those with the clarifying questions below instead of assuming them. ```hint Incremental, not total Not every order the new store receives is a new order. Ask where each of those orders would have gone if the store had never opened. ``` ```hint Learn from past openings If stores have opened in comparable areas before, they are the closest thing you have to an experiment. Think about what they can tell you and what would make the comparison unfair. ``` ```hint Distance changes the cost A store closer to customers changes how far shoppers travel and how many orders each one can handle. Think about which costs scale with distance. ``` ### Clarifying Questions - Whose decision is this: a retail partner choosing where to open a physical store, or the marketplace deciding whether to add, support or prioritize a new partner location? - What is the objective: incremental orders, gross profit, faster delivery in an underserved area, or market share against competitors? - Which data is available: order history of nearby existing stores, customer delivery addresses or zones, demand signals from the area such as searches or sign-ups, shopper supply, and cost data? - Over what horizon is the decision judged, and what return or payback period counts as "worth it"? - Is the decision reversible, for example a short lease or a pilot, or a long commitment? ### What a Strong Answer Covers - A precise decision statement with an objective and a success threshold agreed before any analysis - A demand estimate for the site's catchment that combines existing customers, unmet-demand signals and comparable stores - Cannibalization of nearby stores, and the difference between total and incremental volume from each party's point of view - Unit economics: basket size, margin, fulfilment and delivery costs, fixed costs, break-even volume and sensitivity to the uncertain inputs - Operational effects such as delivery time, shopper supply and coverage - The tables and metrics the analysis needs, with their grain and data-quality caveats - A recommendation with its risks, and a plan to measure the real effect after opening ### Follow-up Questions - Two candidate sites show similar demand, but one overlaps heavily with an existing store's delivery area. How do you compare them? - After the store opens, how would you measure its true incremental impact when you cannot randomize which areas get a store? - The recommendation hinges on one uncertain input, such as the cannibalization rate. How do you present it to decision-makers? - Which tables and metrics would you build so this analysis can be rerun for every future candidate site?