INSIGHTS FROM EXPERTS ON LINKEDIN
Thomas Eccel shares that Google is phasing out Dynamic Search Ads and moving everything to AI Max by September 2026. He explains this shift comes from how search is evolving with AI, making older systems less effective. Advertisers can already start upgrading before the automatic transition.
Barry Hott highlights a Meta issue where editing an ad can automatically add related media without clear notice. These changes don’t publish immediately but can go live with the next update and distort performance data. He suggests carefully reviewing edits and checking what’s being published every time.
Brice Maniranzi outlines recurring LinkedIn Ads mistakes he sees in audits, including poor targeting settings, generic creatives, and missing conversion tracking. He also points out that many advertisers rely too much on clicks instead of looking at metrics like frequency, audience quality, and dwell time. Fixing these basics can improve performance and reduce wasted spend.
Eric Linssen shares a strategy where AEs record video ads targeting specific account lists, paired with outbound from the same reps. The content is based on real sales conversations and refreshed weekly, making it highly relevant. It’s driving strong pipeline results while also boosting collaboration between sales and marketing.
JD Garcia explains how he built an AI system with multiple specialized agents that handle different GTM tasks and work together automatically. Instead of doing everything manually, he sets tasks while the system routes and executes them. This setup helps him scale output and manage more work without losing control.
Emilia Korczynska shares her experience automating reporting with AI and expecting it to replace higher-level decision making. While the data analysis worked, the insights often lacked context and led to weak or incorrect conclusions. She highlights that numbers alone aren’t enough, and real understanding still depends on broader business context.
Barrie Flink shows how he uses Clay and Lovable to generate fully personalized landing pages for each prospect. The setup pulls in data like name and company, then creates tailored follow-up pages with relevant content and booking options. It’s quick to build and opens up new ways to scale ABM and outbound campaigns.
Dave Gerhardt shares how Ramp is adopting AI across its marketing team, from analyzing sales calls to improving attribution and measurement. The team combines incrementality testing with a 70/30 split between proven channels and experiments. The conversation also explores how marketers can stay valuable in an AI-heavy environment.
Vladimir Blagojević breaks down how to implement full-funnel marketing without major disruption by focusing on strong foundations, shared goals, and better measurement. He outlines the full buying journey and emphasizes moving beyond siloed teams and last-click metrics. The approach is built on small, structured pilots that can scale over time.
Liam Moroney explains that being visible or showing up in search and AI results doesn’t guarantee buyers will choose your brand. Familiarity and prior exposure play a much bigger role in decision-making, especially in B2B. Brands need consistent, proactive efforts to build awareness before buyers even start looking.
Matthew Sciannella argues that the rise of AI roles is as much about shaping behavior as it is about technology. He suggests companies are pushing adoption in a way that pressures professionals to follow along. Instead of reacting, he encourages building a personal way of working with AI that aligns with individual strengths and values.
WHAT'S NEW IN THE INDUSTRY
Salesforce is rolling out Headless 360, an API-first layer that lets AI agents access data and run workflows without relying on dashboards. This marks a move toward systems that operate in the background, where agents handle tasks instead of users clicking through tools. It also brings new challenges around control and predictability as automation takes on a bigger role.
Google is reintroducing Data Studio as a simpler way to analyze and act on data across its ecosystem. It will come in a free version for smaller teams and a Pro version with advanced features for larger organizations. The goal is to make reporting and decision-making faster without relying heavily on analysts.
Google is simplifying how consent works by making ad_storage the main control for how Ads collects and uses data. From June, this will directly impact tracking, attribution and audience targeting depending on whether users give consent. The change makes the rules clearer but puts more pressure on getting consent setup right.
Advertisers are reporting widespread Google Ads disapprovals caused by DNS and server errors, even when their sites are working fine. This is pausing campaigns and impacting traffic, leads, and revenue without clear cause. It highlights how platform issues can disrupt performance and why close monitoring is critical.
More buyers are researching on Reddit before clicking ads, which is skewing the data PPC campaigns rely on. This hidden journey can make high-intent keywords look like they’re underperforming, causing automation to pull back spend incorrectly. Strong content and offline conversion tracking can help close the gap.
Meta is projected to surpass Google in global ad revenue for the first time, driven by its strength in automation and performance-focused tools. Advertisers are shifting budgets toward platforms that make it easier to scale and prove ROI. The change signals a broader shift in how digital ad spend is being allocated.
Google is phasing out Dynamic Search Ads and moving advertisers to AI Max as the new default for Search campaigns. Existing campaigns will be automatically upgraded by September, whether advertisers act or not. The shift reflects a move toward more automated, AI-driven campaign management.
Microsoft is adding features that let advertisers easily import Google Performance Max campaigns, including new customer acquisition goals, without rebuilding them. It also brings more visibility with the landing page and search term reporting. The updates make it simpler to test and scale campaigns across platforms.
Search generated $114.2 billion in U.S. ad revenue in 2025, remaining the largest channel but growing more slowly than video, social, and programmatic. More budget is moving toward formats powered by automation and AI. The shift shows how discovery and media buying are changing across platforms.
Adobe and Canva are both rolling out AI tools that turn design into a prompt-driven process. Adobe is focusing on helping professionals move faster, while Canva is making creation more accessible to everyone. This is speeding up production but shifting the challenge toward strategy and consistency.
A new CMO shares how the role is becoming more complex with pressure on budgets, changing buying behavior, and the rise of AI. The job requires balancing creativity, analytics, and leadership while navigating constant scrutiny. It reflects how expectations for marketing leaders are evolving. A full video of the conversation is available in the link.
AI is evolving from a simple tool into a system that can store knowledge, work securely with sensitive data, and validate insights across multiple models. This is helping teams generate insights faster and connect research over time. It’s shifting the focus from manual analysis to deeper thinking and better decision-making.
That’s the scoop for this week! If you found this valuable and any useful insights caught your eye, feel free to share them with your network.
Until next week!
