Data driven multi-touch attribution modeling with Markov chains
[Research] Transformer 기반 광고 기여도 모델 제안
In this research paper, we used Google and Facebook conversion lift studies to calibrate our Multi-Touch Attribution results from Google Ads Data Hub (ADH). We assessed the feasibility of these conversion lift calibrations and the impact of using conversion lift results in the calibration adjustment.
A curated list of attribution, measurement, and marketing analytics resources. Open-source libraries, commercial platforms, research papers, datasets, and the people thinking hard about which marketing dollar caused which revenue dollar.
Multi-touch attribution for Shopify stores. First-click to purchase tracking via Theme App Extension and Remix admin.
Server-side multi-touch attribution for Ruby and Rails. Track customer journeys, attribute conversions, know what works.
Server-side multi-touch attribution for Python. Flask middleware, framework-agnostic core, no ad-blocker blind spots
Server-side multi-touch attribution for Node.js and TypeScript. Track journeys, attribute conversions, measure real ROAS.
Server-side multi-touch attribution for PHP. Framework-agnostic core with Laravel and Symfony adapters.
Real-time probabilistic identity resolution engine for streaming platforms. Resolves multi-user attribution with 78% accuracy at <100ms latency. GDPR/CCPA compliant.
A B2B SaaS company runs campaigns across 10+ marketing channels (Organic Search, Paid Search, LinkedIn, Webinars, Referrals, etc.). Leads flow through a 10-stage funnel — from Website Visit to Opportunity Won — touching multiple channels along the way.
Multi-touch attribution + funnel + CAC/ROAS Streamlit dashboard. Synthetic 75k users / 1,143 paid / $172k spend / 5 channels — finds paid_social structurally unprofitable (ROAS 0.83x).
The Attribution Modeling for ETL project offers a comprehensive suite of tools and methodologies for implementing various marketing attribution models, including first-touch, last-touch, linear, time decay, and U-shaped models. These models are essential for understanding the impact of different marketing channels on customer conversions.
Complete pipeline for Multi-Touch Attribution (MTA) and Marketing Mix Modeling (MMM) analysis. Includes customer journey analysis, channel attribution, ROI optimization, and budget allocation recommendations for data-driven marketing decisions.
End-to-end data warehouse (Bronze/Silver/Gold) with multi-touch attribution and Tableau dashboards
LSTM + Beam Search for multi-touch marketing optimization
Multi-touch attribution modeling comparing Last-Click, First-Click, Linear, Time-Decay, and Position-Based models on a digital marketing dataset — quantifying how channel credit shifts across attribution rules.
Bayesian marketing mix modeling, multi-touch attribution, and causal inference toolkit for unified marketing measurement and incrementality analysis.
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