Optimising Performance and Privacy in a Multi-Platform World

Client: Intuit QuickBooks

The Digital Effectiveness Modelling (DEM) project revolutionised digital attribution and marketing effectiveness for Intuit QuickBooks by implementing a privacy-first, data-driven approach. Traditional attribution models, such as Google’s Data-Driven Attribution (DDA), failed to accurately account for non-Google platforms such as Meta and Display, leading to inefficiencies in marketing spend allocation. To address these shortcomings, the project introduced Bayesian Calibration and Markov Chains, enabling precise measurement of the incremental impact across all digital touchpoints.

By leveraging Ads Data Hub (ADH) for secure, privacy-compliant data ingestion, the project achieved a 52% increase in attributed conversions for Display and a 78% uplift for YouTube, demonstrating that these channels had been significantly undervalued. Additionally, 28% of attribution was reallocated away from Brand PPC to higher-funnel channels, improving media spend efficiency. Meta’s role in the marketing funnel was also redefined, shifting focus from direct-response purchases towards top and mid-funnel placements to drive sustained engagement and brand-building.

By eliminating reliance on third-party cookies, this initiative enabled data-driven media allocation and real-time decision-making, ensuring cross-platform efficiency, improved budget allocation, and a more accurate understanding of consumer behaviour. This project has set a new industry benchmark for privacy-first marketing attribution, ensuring long-term scalability and adaptability in an evolving digital landscape.