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.

Server-side multi-touch attribution for Python. Flask middleware, framework-agnostic core, no ad-blocker blind spots

Server-side multi-touch attribution for PHP. Framework-agnostic core with Laravel and Symfony adapters.

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.

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.

End-to-end data warehouse (Bronze/Silver/Gold) with multi-touch attribution and Tableau dashboards

LSTM + Beam Search for multi-touch marketing optimization

Server-side multi-touch attribution for Node.js and TypeScript. Track journeys, attribute conversions, measure real ROAS.

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.

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.

Real-time probabilistic identity resolution engine for streaming platforms. Resolves multi-user attribution with 78% accuracy at <100ms latency. GDPR/CCPA compliant.

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.

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.

Bayesian marketing mix modeling, multi-touch attribution, and causal inference toolkit for unified marketing measurement and incrementality analysis.