Propose a multi-touch attribution model and its data pipeline
Tests your grasp of attribution models and their data engineering needs. Propose a rule-based model (e.g., time-decay), outline the data pipeline for it, and acknowledge privacy-driven signal loss. A red flag is ignoring the challenge of identity resolution.
This tests connecting business needs to a specific attribution model and its data pipeline. Start by proposing a rule-based model like time-decay, justifying it for a long sales cycle. Then, detail the data engineering: ingesting touchpoints, resolving user identities, and applying the model. Acknowledge limitations like signal loss. A red flag is pitching a complex ML model without mentioning its high data requirements (2,000+ conversions/month) or implementation costs.
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