I went straight for a top-down approach and started throwing out population numbers, which felt okay at first.
Start by clarifying the scope and assumptions (e.g., city, target segment, timeframe) and then use a structured top-down or bottom-up estimation approach. Break the market into addressable segments, estimate demand and supply factors, and conclude with a range and key sensitivities.
Pro tip: Acknowledge that as a software engineer, you'd leverage data and experimentation to refine estimates, and mention that the initial estimate is a hypothesis to be validated with a pilot or MVP.
Ask clarifying questions to define the city, target customer segments, timeframe, and whether we're estimating total addressable market (TAM), serviceable addressable market (SAM), or serviceable obtainable market (SOM). State your assumptions explicitly.
Use a bottom-up approach: estimate the number of potential customers (e.g., households or individuals) in the city, the percentage likely to use grocery delivery, average order frequency, and average order value. Alternatively, use a top-down approach based on total grocery spend and online penetration.
Consider the number of existing competitors, their market share, and the capacity of delivery infrastructure. Factor in barriers to entry and potential adoption rates.
Multiply demand factors to get annual revenue potential. For example: (Number of households × adoption rate × orders per month × average order value × 12). Present a range (low, medium, high) based on different assumptions.
Suggest ways to validate the estimate, such as running a pilot in a small area, analyzing search trends, or using A/B tests. Emphasize that the estimate is a starting point and should be refined with real data.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.