User Journey Intelligence (MTA)

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What is MTA?

Multi-Touch Attribution (MTA) is a data-driven user journey analysis within the Intelligence Platform. By unifying Google Analytics 4 event data, Google Ad Manager, and first-party CRM user records in Google BigQuery, MTA maps the complete multi-touch path that users travel from initial discovery to conversion.

Driven by an 18-Question Library and a Dual-Core Performance Engine (Efficiency Core & Relevancy Core), MTA provides media, creative, and web teams with actionable operational outputs and strategic executive briefs to optimize media spend, audience targeting, creative messaging, and on-site user journeys.

How It Works & How to Use It

Step 1: Data Setup & Infrastructure Unification

GA4 event data exports, Google Ad Manager data, and first-party CRM user records are ingested, cleansed, and merged in Google BigQuery to establish a single unified user journey dataset.

Step 2: Continuous Dual-Core Optimization Engine

The Efficiency Core (Targeting & Conversion): Solves Who to target and Where to convert. It creates proprietary audience lists, calibrates budget from “assisters” to “drivers,” applies precision bid multipliers for incremental lift, and exports top-performing “Whale” profiles directly to Meta and Google ad platforms.

The Relevancy Core (Messaging & Discovery): Solves What to say and How to be found. It optimizes ad relevance based on behavioral needs, adjusts on-site journey architecture to bridge informational pages to form submits, and surfaces audience search questions for AI model indexing (“Share of Suggestion”).

Step 3: Quarterly Question Selection

Clients and agency teams align quarterly on specific deep-dive questions selected from MTA’s 18-Question Library across three strategic areas.

Step 4: Two-Layer Output Delivery

Layer 1 (Operational Outputs): Direct parameters, lists, and data files delivered directly to agency specialists for immediate deployment (e.g., 1P audience lists, DSP blacklists, creative rotations).

Layer 2 (Intelligence Reports): PDF decks delivered on a fixed cadence to C-suite, CMOs, SEO heads, and web dev leads.

Key Findings and Insights

  • Precision Bidding & Reduced Wasted Spend: Identifies non-incremental conversions and applies bid multipliers to stop overpaying for low-value touchpoints.
  • Faster Time-to-Convert: Corrects journey bottlenecks and optimizes landing page sequences to reduce overall conversion lag.
  • Future-Proofed 1st Party Signal: Builds an audience definition owned by the brand, preparing campaigns for the cookieless AI era and “Share of Suggestion” discovery.

What Do I Do Once I Have Access to My MTA Analysis?

Deploy First-Party Audience Exports and Precision Bidding

  • Export high-value "Whale" audience profiles directly to Google and Meta ad platforms to train targeting algorithms, while applying precision bid multipliers to maximize incremental lift.

Reallocate Budgets Across Winning Channel Sequences

  • Shift media spend from passive "assister" tactics to high-converting "driver" campaigns, adjusting creative rotations and retargeting windows based on top-performing user paths.

Execute On-Site UX and Content Fixes

  • Implement the page abandonment fix list, bridge content gaps, and re-architect site navigation to eliminate friction points along converting journey paths.

Present Executive Briefs and Align Next Quarter's Deep Dives

  • Deliver the C-suite intelligence report to stakeholders within 15 business days of quarter close, then select two new focus questions from the 18-Question Library for the upcoming cycle.

When Should I Use MTA?

Budget Reallocation & Waste Reduction

Use MTA when you need to identify over-credited “assister” channels and reallocate spend toward true conversion “drivers” using precision bid multipliers.

Defining Retargeting Windows & Conversion Lag

Deploy MTA when analyzing time-to-conversion and touchpoint frequency to determine the exact threshold for shifting campaigns from prospecting to retargeting.

First-Party Audience & Lookalike Expansion

Leverage MTA to extract high-value “Whale” profile paths and top-performing journey segments to feed proprietary first-party signals into Google and Meta targeting algorithms.

Multi-Touch Creative & Message Alignment

Apply MTA when evaluating which ad creative assets, messaging hooks, and channel combinations appear most frequently in successful multi-touch conversion journeys.

On-Site UX & Page Abandonment Diagnostics

Utilize MTA to isolate high-friction landing pages, broken navigation paths, and on-site drop-off points to prioritize page-level user experience fixes.

Executive Leadership & C-Suite Strategy

Turn to MTA prior to quarterly business reviews to deliver board-level briefs on overall sales cycle velocity, true channel ROI, and brand versus performance budget splits.

Ready To Get Started?

Contact the RADaR Analytics team at [email protected]

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