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Most advertisers optimize campaigns one by one. That’s not needed Because Google doesn’t learn in silos. It learns from data. That’s where Portfolio Bid Strategies come in. Instead of optimizing each campaign separately… You let multiple campaigns learn together. What it actually does You group campaigns under one goal: Same CPA Same ROAS Same objective

Watch out for these fake Claude ads mail! Found by Andy Hendricks

After 7+ years managing Google Ads accounts, here’s the simplest truth about Quality Score: It’s a feedback signal. Quality Score shows how Google estimates the relevance and usefulness of your ad and landing page for a specific keyword based on historical performance. It mainly comes down to three things: • Expected click-through rate• Ad relevance

Google Ads appears to be testing a new “Set up in Google Tag Manager” button directly within the conversion setup flow, thanks for sharing Natasha Kaurra & Hana Kobzová!

Most people still think Meta Ads is simple. 👉 Create an ad👉 Get likes & clicks👉 Make sales That might have worked years ago. But in 2026… Meta Ads is a completely different game. Winning advertisers are focused on: ✅ Data & tracking (Pixel + Conversion API + attribution)✅ Smart audience strategy (broad, lookalikes, first-party

If you’re running Meta ads and still feel like results are unpredictable… You’re not alone… Most businesses don’t have a traffic problem. They have a measurement problem. Here’s what I see every week: 👉 Campaigns showing “great ROAS” but margins are shrinking👉 Retargeting is doing most of the work while new customer growth stalls👉 Missing

If you want smarter, faster, more relevant answers, don’t just type “Remember me or my tone” Instead, try this: ❌ Bad prompt:“Remember me.” ✅ Better prompt:“Remember that I’m a digital marketer.” 🏆 Best prompt:“Remember that I’m a B2B marketer focused on SaaS lead gen. I prefer concise answers, and I work mostly in Google Ads.”

In 2026, performance is no longer about “finding the right interests.” It’s about feeding the algorithm the right signals. After auditing and restructuring multiple accounts, the pattern is clear: • Weak event prioritisation• Pixel-only tracking (no proper CAPI depth)• Creative testing without structured signal analysis• Scaling before data velocity is stable So I rebuilt the