← Walmart Labs Interview Insights
I started with advertiser-side metrics like ROAS and CPM, then tried to cover publisher-side fill rate and eCPM.
Start by clarifying the adtech platform's business model (e.g., demand-side, supply-side, or retail media) and then group KPIs into categories like revenue, operational efficiency, and user engagement. For each KPI, explain its importance and how it ties to business outcomes, emphasizing the engineering implications for tracking and optimizing them.
Pro tip: Tie KPIs to Walmart Labs' retail media context—e.g., ROAS for advertisers, fill rate for publishers—and mention how engineering decisions (like latency reduction) directly impact these metrics.
Ask or state assumptions about whether it's a DSP, SSP, ad exchange, or retail media network, as KPIs vary. Align KPIs with primary goals like revenue growth, advertiser retention, or user experience.
Group KPIs into revenue (e.g., eCPM, ARPU), operational (e.g., fill rate, latency), and engagement (e.g., CTR, viewability). This structure ensures comprehensive coverage.
Choose 3-5 KPIs that are critical for the platform's success, explaining why each matters. For example, fill rate indicates inventory monetization efficiency, while CTR reflects ad relevance.
Discuss how engineering can influence these KPIs—e.g., optimizing auction latency to improve fill rate, or implementing real-time bidding to boost eCPM. This shows technical depth.
Conclude by emphasizing that no single KPI tells the whole story; a balanced set covering revenue, operations, and user experience is essential for sustainable growth.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.