You’re working with a luxury car brand that wants to optimize their digital advertising spend across multiple channels (Google Ads, Facebook, YouTube, programmatic display). They’ve been running campaigns for 6 months and have the following data: impressions, clicks, conversions, cost data by channel, customer lifetime value, and post-purchase survey data indicating how customers first heard about the brand. However, there’s a complication: their attribution window shows that customers typically interact with 4-5 different touchpoints before converting, and there’s a significant lag between initial awareness and purchase (average 45 days). The CMO believes their current last-click attribution model is severely under-crediting upper-funnel channels like YouTube and over-crediting Google Search. Design an end-to-end solution to build a data-driven attribution model that accurately measures each channel’s contribution to conversions. Walk me through your methodology, what statistical approaches you’d use, how you’d validate your model, and how you’d present actionable insights to stakeholders who need to make budget allocation decision.