Evaluate and recommend an attribution approach to quantify PR-driven impact on [ConversionEvent] for [CompanyName]’s [CampaignName] in [Market]. Compare first-touch, last-touch, time-decay, and position-based models against multi-touch heuristics using a [AttributionWindowDays]-day lookback. Define data requirements from [DataSources] and outline how earned mentions (quality-scored), referral traffic, and branded search uplift feed the model. Identify bias risks (e.g., channel over-crediting, collinearity with paid bursts) and propose controls.
Output requirements: (1) A comparison matrix (Model, Assumptions, Pros, Cons, Data Needs, When to Use). (2) A recommended model with parameter settings and a validation plan (holdout logic, stability checks). (3) A calculation spec for “PR-Influenced Pipeline” and “Marginal Cost per Incremental Conversion.” (4) A governance note on when to revisit or switch models.