Billy Grace

What is Billy Grace?

Billy Grace is an Agentic Marketing Orchestration and Marketing Attribution platform designed for digital marketing teams and agencies. The system unifies first-party data capture, multi-touch attribution modeling, cross-channel analytics, and AI-driven campaign optimization, featuring an autonomous AI marketing agent named Quin to orchestrate growth workflows.

Key Capabilities

First-Party Data & Session Tracking: Implements a privacy-compliant tracking pixel utilizing machine learning models for session stitching and cookieless customer journey resolution across web and ad channels.
Unified Marketing Measurement (UMM): Combines Marketing Mix Modeling (MMM) algorithms with Multi-Touch Attribution (MTA) to evaluate view-through and click-through conversions across full-funnel ad spend.
Cross-Channel Performance Analytics: Consolidates ad network, analytics, and conversion data into custom dashboards to analyze performance at the channel, campaign, ad creative, keyword, and product levels.
Automated Budget & ROAS Optimization: Executes automated ad spend reallocations and return on ad spend (ROAS) targeting based on real-time attribution data.
Autonomous AI Marketing Agent (Quin): Integrates a native AI agent (Quin) that queries the platform's attributed first-party dataset and company-specific knowledge (brand positioning, product catalogs, messaging rules) to generate natural-language recommendations, cross-channel diagnostic reports, and prioritized execution to-do lists.

Audience & Use Cases

Audience: Digital marketing managers, performance marketing leads, e-commerce directors, and media agencies.
Use Case: Centralizing multi-channel ad attribution, eliminating cookieless tracking blind spots, optimizing cross-channel ad spend, and utilizing autonomous AI agents for growth analysis and campaign planning.

Technical Specifications

Supported Channels: Google Ads, Meta Ads, TikTok Ads, Snapchat Ads, and major digital advertising networks.
Data Architecture: In-browser first-party tracking pixel paired with machine learning session stitching engines; GDPR compliant.
Deployment Model: Cloud-hosted software-as-a-service (SaaS) platform.
Vendor Claims: According to the vendor, client agencies report up to an 80% reduction in manual analytics reporting workloads and 12 hours saved per user per week through Quin's automated workflow execution.