π Without you.
Google launches AI-powered ad formats and autonomous campaign tools, LinkedIn restricts AI content while becoming top cited source, how to test Google Ads bid strategies, and more.
In this issue
Good morning.
Somewhere between your last meeting and right now, Friday snuck up and tapped you on the shoulder.
The weekendβs almost here. And the best way to kick it off is showing up already knowing everything that happened in marketing this week. Consider this your briefing.
Google comes a step closer to running ads without you

Google Marketing Live. The Coachella for marketing nerds. Weβve brought the roundup.
The Sabrina Carpenter: Google rebuilt its ad formats for AI-first Search with Conversational Discovery ads, Highlighted Answers, and AI-powered Shopping ads.
This makes ads more a part of the conversation rather than interruptors. And connect a shopperβs first question to their final purchase. Sounds powerful.
Meet Ask Advisor: One AI agent that spans Google Ads, Analytics, Merchant Center, and Google Marketing Platform.
It builds campaigns, surfaces recommendations, and handles the operational busywork that eats up your afternoon.
Asset Studio helps with creative: Feed it a natural language prompt, and it generates images, video assets, and text variations that fit your brand guidelines.
YouTube and Demand Gen picked up some new tricks:
- New creator tools make it faster to find and brief creators who fit your brand.
- You can now run Demand Gen ads on Maps.
- Dynamic product feeds now run across YouTube, with advertisers averaging a 33% lift in conversions.
Reading between the lines, Google is getting ready for agentic commerce.
Universal Cart, Agent Payments Protocol, and Universal Commerce Protocol are the behind-the-scenes wiring that put your products in front of shoppers.
The bottom line: Googleβs ad ecosystem now is AI-first. Campaigns run themselves more, creative ships faster, and the shopping journey is more like a chat.
Time to get comfortable with these tools now. Make sure to take a look at Googleβs full breakdown of everything new here.
LinkedIn wants less AI, gets cited by AI anyway, and checks your ad receipts
Weβre going to give you a cake, but donβt even think about eating it.
The platform is pulling in two directions: Restricting AI-generated content that lacks a human perspective while building AI writing tools directly into its composer.
Global Editorial VP Laura Lorenzetti says: βWhen AI is overused, especially at scale, it dilutes the valuable insights that real human conversations can spark.β Hmβ¦
This means AI-heavy LinkedIn content will reach fewer people, so your organic strategy needs a real human voice behind it, or it wonβt travel.
AI loves LinkedIn, however: According to a Meltwater study of 9.5M citations, LinkedIn is the second-most-cited domain among major AI chatbots, particularly for B2B queries.
So, when a potential customer asks a chatbot about your industry, thereβs a real chance LinkedIn content shows up in the answer. Yours could be one of them.
What gets cited:
- Expert-led individual posts over company page updates.
- Articles and plain text (83% of all citations).
- Clear headings, numbered lists, and specific data points.
Push your internal experts to post. Structure everything with headers and bullets. Generic brand content wonβt get cited.
Follow the paper trail: LinkedIn has added post-bid measurement for Audience Network campaigns through DoubleVerify.
Meaning, after your ads run, you get independent reporting on viewability, brand safety, fake clicks, and whether your ads actually showed up in the right places.
LinkedIn already filters placements before bids. Now it checks the receipts after.
If youβre spending outside the core feed, that means you can see exactly where your budget went and cut anything that isnβt pulling its weight.
Broken data breaks AI

CAC is rising. Loyalty is slipping.
Most teams know their data strategy isnβt keeping up but they canβt pinpoint where itβs breaking.
Youβre investing in tools, teams, and campaigns, yet results arenβt compounding the way they should.
The problem usually isnβt effort. Itβs hidden gaps in your data foundation.
The 5-minute Data Maturity Assessment shows exactly where your strategy is falling short across readiness, activation, decisioning, and governance so you know what to fix first.
Quick. Insightful. Actionable.
How to test your Google Ads bid strategy this year

Automation is only as smart as the goals you give it.
Even high-performing campaigns plateau. When manual optimizations stop moving the needle itβs the bidding model itself that needs re-evaluation.
Sarah Stemenβs breakdown of bid strategy gives insight into how to do exactly that.
Phase 1: Identifying the need for a change: Contrary to popular belief, you shouldnβt test for the sake of testing.
Instead, there are data-driven signals that can tell you a change is necessary:
- Performance plateaus hit when CPA or ROAS stalls despite tight creative, deliberate match types, and optimized landing pages.
- Disconnected goals appear when the platform chases lead volume while the business cares about closed revenue.
- Critical mass matters because Smart Bidding needs data liquidity. At 30β50 conversions in a 30-day window, a campaign is ready to support tCPA or tROAS.
- Strategic shifts also warrant a re-evaluation of the current bid strategy.
Phase 2: Choosing your testing method: Native Google Ads experiments are the most scientific option.
But splitting your budget in half starves Smart Bidding of the conversion volume it needs to exit the learning phase.
For B2B or high-ticket B2C accounts with 60β90 day sales cycles, Googleβs default columns attribute value to the click date, not the conversion date.
An experiment can look like a failure in the UI while itβs actually working. The sequential framework exists precisely for this scenario.
Phase 3: Implement the following 4-step bid strategy testing framework.
- Define a North Star metric that lives outside the Google Ads UI.
- Audit conversion tracking. Offline conversion tracking is a best practice here.
- Respect the βwait and seeβ period. The learning phase runs 7β14 days. Conversion lag means early data can look worse, or better, than it truly is.
- Pull Conversion Value (By Time) in the Report Editor. This attributes revenue to when the conversion occurred, not the click.
AI handles real-time decisions well. It still has no idea what your business actually values. Providing that context is the human strategistβs job. And thatβs you, of course.
The AI marketing newsletter read by marketers at Google, Kalvyio and Morningstar

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What do your agency clients hate the most?
They say patience is a virtue, but in the agency world, itβs apparently nonexistent.
If you want to keep your clients happy, you need to be fast, furious⦠and accurate:

Clients want it done, and they want it done yesterday and for cheaper:
- Speed of delivery annoys clients the most (37%)
- Budged overruns are a bit behind with 36%
- Ineffective communication is at third with 33%
Interestingly, poor creativity is low on the list (18%). So clients like the work agencies do, including yours, but they hate how long it takes and how much extra it costs.
What annoys clients the most? Speed of delivery, cited by 37% as the biggest challenge.
The modern client is impatient and budget-conscious. They will forgive a slightly less βperfectβ creative output if it arrives on time and on budget.
Operational efficiency beats perfectionism here.
Fix it now: Review your internal approval processes. If a deliverable sits in βinternal reviewβ for 3 days, you are creating your own churn. Cut the red tape.
Budget overruns and slow delivery kill more agency relationships than bad ideas.
AI EDUCATION: ChatGPT, Claude, Gemini, Midjourneyβ¦ So many names, but whatβs actually useful for you in your work? Thereβs a newsletter called The Deep View that exists to sift through all the noise and get you up to speed on whatβs actionable with AI products, and itβs free. Join 512,000+ subscribers with one click and let AI empower you.*
TIKTOK: 89% of US small businesses are reporting sales increases after promoting on TikTok. Also, 57% of Shop users are buying from a new brand within days of discovery. That sounds more like a sales funnel than a social app. You might want to treat it like one.
SNAPCHAT: The new Unified Attribution tool, now in beta, pulls Snapchat metrics and Mobile Measurement Partners cross-channel data into a single view inside Ads Manager. If youβre tired of tab-switching to check performance, this sync could sharpen your optimization decisions.
CHATGPT: Bigger images, customisable CTAs like βshop nowβ and βbook now,β plus a dedicated e-commerce unit with pricing and review data, are all part of OpenAIβs new ad format in testing. A carousel placement is also comingβ¦ Itβs moving quickly.
*This is a sponsored post.
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