Unify paid-channel ROI attribution — real-time cross-platform conversion tracking

Many mid and large advertisers (roughly 600,000 in the target segment) struggle to attribute paid-channel ROI accurately and in real time because the cookieless web, ATT, and siloed ad platforms break deterministic linkage, forcing reliance on noisy, delayed, or aggregated signals that lengthen optimization cycles and increase wasted spend. Performance and finance teams need channel-level marginal ROI rather than coarse lift tests, and that need is acute at scale. We could build a real-time cross-platform conversion tracking platform that ingests event-level APIs from Meta, Google, and TikTok plus server-side first-party signals, stitches identities in a privacy-first manner, and delivers deterministic and causal attribution outputs via an explainable model ensemble and APIs for automated budget reallocation. Targeting a $12.0B market (600,000 advertisers × $20K ACV), the product would prioritize mid and large advertisers with SLA-backed ingestion, near-real-time reporting, and integrations into bidding systems to close the loop. This moment is attractive because platform-level event APIs and a shift to first-party/server-side strategies make deterministic reconciliation technically feasible, and AI-driven causal models are reducing noise so attribution can be operationalized. Competition is medium—incumbent analytics vendors and platform-native tools exist but often lack real-time deterministic linkage or explainability—so differentiation should focus on customer-owned data flows, privacy-preserving identity stitching, clear uncertainty metrics from causal ensembles, and tight platform integrations; be honest that challenges include API instability, proving incrementality at scale, and a longer enterprise sales cycle, but the market score (92/100) and revenue potential (88/100) indicate a high-opportunity, execution-risk proposition worth further diligence.