← Pinterest Interview Insights
I went straight to traffic volume and kind of forgot to think about segmentation for a while.
Break the problem into two parts: estimating the number of people who pass the billboard (traffic volume) and then estimating the proportion who actually see it (visibility). Use a combination of public data (e.g., traffic counts), assumptions, and a model to calculate total impressions. Acknowledge uncertainty and suggest validation methods like eye-tracking studies or mobile location data.
Pro tip: Mention that impressions should account for frequency (multiple exposures per person) and that you'd calibrate your model with ground truth from a small-scale study. Also, tie it back to Pinterest's visual nature and how OOH could drive brand awareness or app installs.
Clarify what 'reach' and 'impressions' mean in this context: unique people vs. total exposures, and the time frame (e.g., daily, weekly).
Use public data (e.g., DOT traffic counts, Google Maps API) or partner with data providers to get the number of vehicles passing the billboard location.
Determine the percentage of passengers who actually notice the billboard, considering factors like billboard size, angle, traffic speed, and time of day. Use industry benchmarks or conduct a small-scale eye-tracking study.
Multiply traffic volume by average occupancy per vehicle and visibility rate to get total impressions. Adjust for frequency if estimating unique reach.
Validate assumptions with A/B tests, mobile location data, or surveys. Iterate on the model to improve accuracy.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.