Problem
Last-click attribution was systematically over-crediting paid search while starving profitable upper-funnel channels of budget. The business was optimising the wrong signal entirely.
Data
6 months of campaign data from Google Analytics, Meta Ads Manager, and an email platform. 140,000 sessions and 4,200 tracked conversions across four channels.
Solution
Data-driven multi-touch attribution model built in Python using Markov chain analysis. Each channel's true marginal contribution to conversion was isolated independently of the others.
Recommendation
Reallocate 22% of paid search spend to content marketing and email retargeting. Projected payback period of 6 weeks based on observed historical conversion rates per channel.
Impact
Simulated model projected a 27% improvement in blended ROAS. A controlled A/B test validated a 19% real-world conversion rate uplift, statistically significant at p < 0.05.
Method
Markov chain attribution, cohort comparison, two-tailed significance testing. Power BI executive dashboard built for senior stakeholder communication without technical jargon.