OpenAI confirmed today that it’s rolling out its first live test of ads in ChatGPT, showing sponsored messages directly inside the app for select users.
The details. The ads will appear in a clearly labeled section beneath the chat interface, not inside responses, keeping them visually separate from ChatGPT’s answers.
OpenAI will show ads to logged-in users on the free tier and its lower-cost Go subscription.
Advertisers won’t see user conversations or influence ChatGPT’s responses, even though ads will be tailored based on what OpenAI believes will be helpful to each user, the company said.
How ads are selected. During the test, OpenAI matches ads to conversation topics, past chats, and prior ad interactions.
For example: A user researching recipes might see ads for meal kits or grocery delivery. If multiple advertisers qualify, OpenAI shows the most relevant option first.
User controls. Users get granular controls over the experience. They can dismiss ads, view and delete separate ad history and interest data, and toggle personalization on or off.
Turning personalization off limits ads to the current chat.
Free users can also opt out of ads in exchange for fewer daily messages or upgrade to a paid plan.
Why we care. ChatGPT is one of the world’s largest consumer AI platforms. Even a limited ad rollout could mark a major shift in how conversational AI gets monetized — and how brands reach users.
Bottom line. OpenAI is officially moving into ads inside ChatGPT, testing how sponsored content can coexist with conversational AI at massive scale.
A newly discovered settings panel offers a first detailed look at how ads could work inside ChatGPT, including how personalization and privacy controls are designed.
Driving the news. Entrepreneur Juozas Kaziukėnas found a way to trigger ChatGPT’s upcoming ad settings interface. The panel repeatedly stresses that advertisers won’t see user chats, history, memories, personal details, or IP addresses.
What the settings reveal. The interface lays out a structured ad system with dedicated controls:
A history tab logs ads users have seen in ChatGPT.
An interests tab stores inferred preferences based on ad interactions and feedback.
Each ad includes options to hide or report it.
Users can delete ad history and interests separately from their general ChatGPT data.
Personalization options. Users can turn ad personalization on or off. When it’s on, ChatGPT uses saved ad history and interest signals to tailor ads. When it’s off, ads still appear but rely only on the current conversation for context.
There’s also an option to personalize ads using past conversations and memory features, though the interface stresses that chat content isn’t shared with advertisers. Accounts with memory disabled won’t see this option active.
Why we care. This settings panel offers the clearest view yet of how ad personalization and privacy controls could work with ChatGPT ads. It points to a system built on strict privacy boundaries. The controls suggest ads will rely on contextual signals and opt-in personalization, not deep user tracking. That shift makes creative relevance and in-conversation intent more important than traditional audience profiling for brands preparing for conversational ad environments.
The bigger picture. The discovery suggests OpenAI is building an ad system that mirrors familiar controls from major ad platforms while prioritizing clear privacy boundaries and user choice.
Bottom line. ChatGPT ads aren’t live yet, but the framework is coming into focus — pointing to a future where conversational ads come with granular privacy and personalization controls.
First seen. Kaziukėnas shared the preview of the platform on LinkedIn.
On episode 340 of PPC Live The Podcast, I speak to Amanda Farley, CMO of Aimclear and a multi-award-winning marketing leader, brings a mix of honesty and expertise to the PPC Live conversation. A self-described T-shaped marketer, she combines deep PPC knowledge with broad experience across social, programmatic, PR, and integrated strategy. Her journey — from owning an gallery and tattoo studio to leading award-winning global campaigns — reflects a career built on curiosity, resilience, and continuous learning.
Overcoming limiting beliefs and embracing creativity
Amanda once ran an gallery and tattoo parlor while believing she wasn’t an artist herself. Surrounded by creatives, she eventually realized her only barrier was a limiting belief. After embracing painting, she created hundreds of artworks and discovered a powerful outlet for expression.
This mindset shift mirrors marketing growth. Success isn’t just technical — it’s mental. By challenging internal doubts, marketers can unlock new skills and opportunities.
When campaign infrastructure breaks: A high-stakes lesson
Amanda recalls a global campaign where tracking infrastructure failed across every channel mid-flight. Pixels broke, data vanished, and campaigns were running blind. Multiple siloed teams and a third-party vendor slowed resolution while budgets continued to spend.
Instead of assigning blame, Amanda focused on collaboration. Her team helped rebuild tracking and uncovered deeper data architecture issues. The crisis led to stronger onboarding processes, earlier validation checks, and clearer expectations around data hygiene. In modern PPC, clean infrastructure is essential for machine learning success.
The hidden importance of PPC hygiene
Many account audits reveal the same problem: neglected fundamentals. Basic settings errors and poorly maintained audience data often hurt performance before strategy even begins.
Outdated lists and disconnected data systems weaken automation. In an machine-learning environment, strong data hygiene ensures campaigns have the quality signals they need to perform.
Why integrated marketing is no longer optional
Amanda’s background in psychology and SEO shaped her integrated approach. PPC touches landing pages, user experience, and sales processes. When conversions drop, the issue may lie outside the ad account.
Understanding the full customer journey allows marketers to diagnose problems holistically. For Amanda, integration is a practical necessity, not a buzzword.
AI, automation, and the human factor
While AI dominates industry conversations, Amanda stresses balance. Some tools are promising, but not all are ready for full deployment. Testing is essential, but human oversight remains critical.
Machines optimize patterns, but humans judge emotion, messaging, and brand fit. Marketers who study changing customer journeys can also find new opportunities to intercept audiences across channels.
Building a culture that welcomes mistakes
Amanda believes leaders act as emotional barometers. Calm investigation beats reactive blame when issues arise. Many PPC problems stem from external changes, not individual failure.
By acknowledging stress and focusing on solutions, leaders create psychological safety. This environment encourages experimentation and turns mistakes into learning opportunities.
Testing without fear in an changing landscape
Marketing is entering another experimental era with no clear rulebook. Amanda encourages teams to dedicate budget to testing and lean on professional communities for insight.
Not every experiment will succeed, but each provides data that informs smarter future decisions.
The tasmanian devil who practices yoga
Amanda describes her career as If the Tasmanian Devil Could Do Yoga — a blend of fast-paced chaos and intentional calm. It reflects modern marketing: demanding, unpredictable, and balanced by thoughtful leadership.
Looking to take the next step in your search marketing career?
Below, you will find the latest SEO, PPC, and digital marketing jobs at brands and agencies. We also include positions from previous weeks that are still open.
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Responsibilities: Execute full on-page SEO optimization (titles, meta, internal linking, structure) Deliver Local SEO improvements (Google Business Profile optimization, citations) Perform technical SEO audits and implement clear action plans Conduct keyword research for competitive local markets Build and manage SEO content plans focused on ranking and leads Provide monthly reporting with measurable ranking + traffic […]
Job/Role Overview: We’re hiring a modern digital marketer who understands that today’s marketing is AI-assisted, data-driven, and constantly evolving. This role is ideal for a recent college graduate or early-career professional trained in today’s digital and AI-focused programs – not outdated marketing playbooks. If you actively use AI tools, enjoy testing ideas, and think in […]
Job Description Job Title: Graphic Design & Digital Marketing Specialist Location: Hybrid / Remote (Huntersville, NC preferred) Employment Type: Full Time About Everblue Everblue is a mission-driven company dedicated to transforming careers and improving organizational efficiency. We provide training, certifications, and technology-driven solutions for contractors, government agencies, and nonprofits. Our work modernizes outdated processes, enhances […]
Job Title: On-Page SEO Specialist Experience: 5+ Years Schedule: 8 AM – 5 PM CST Compensation: $10-$15/hour (based on experience) Fully Remote | Full-time Contract Position Job Overview We’re looking for a seasoned On-Page SEO Specialist to optimize and enhance our website’s on-page SEO performance while driving multi-location performance […]
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About the Role We’re looking for a data-driven Marketing Strategist to support leadership and assist with optimizing our paid and organic growth efforts. This role sits at the intersection of PPC strategy, SEO execution, and performance analysis—ideal for someone who loves turning insights into measurable results. You’ll be responsible for documenting, executing, and optimizing campaigns […]
Job Description Salary: $75,000-$90,000 Hanson is seeking a data-driven strategist to join our team as a Digital Marketing Strategist. This role bridges the gap between marketing strategy, analytics and technology to help ensure our clients websites and digital tools perform at their highest potential. Youll work closely with cross-functional teams to optimize digital experiences, drive […]
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Type: Remote (Full-Time) Salary: Up to $1,500/month (MAX) Start: Immediate Responsibilities Launch and manage Meta Ads campaigns (Facebook/Instagram) Launch and manage Google Ads Search campaigns Build retargeting + conversion tracking systems Daily optimization focused on ROI and lead quality Manage multiple client accounts under performance expectations Weekly reporting with clear actions and next steps Requirements […]
Job Description At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain Data Unification, and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud delivers interoperable data where and when it’s needed, empowering data and analytics leaders with unparalleled […]
Job Description Paid Media Manager Location: Dallas, TX (In-Office) Compensation: $60,000–$65,000 base salary (commensurate with experience) About the Opportunity Symbiotic Services is partnering with a growing digital marketing agency to identify a Paid Media Manager for an in-office role in Dallas. This position is hands-on and execution-focused, supporting multiple client accounts while collaborating closely with […]
Strategic Leadership: Define and lead the strategy for SEO, AEO, and LLMs, ensuring alignment with overall business and product goals.
Roadmap Execution: Develop and implement the SEO/AEO/LLM roadmap, prioritizing performance-based initiatives and driving authoritative content at scale.
Google is rolling out a beta feature that lets advertisers run structured A/B tests on creative assets within a single Performance Max asset group. Advertisers can split traffic between two asset sets and measure performance in a controlled experiment.
Why we care.Creative testing inside Performance Max has mostly relied on guesswork. Google’s new native A/B asset experiments bring controlled testing directly into PMax — without spinning up separate campaigns.
How it works. Advertisers choose one Performance Max campaign and asset group, then define a control asset set (existing creatives) and a treatment set (new alternatives). Shared assets can run across both versions. After setting a traffic split — such as 50/50 — the experiment runs for several weeks before advertisers apply the winning assets.
Why this helps. Running tests inside the same asset group isolates creative impact and reduces noise from structural campaign changes. The controlled split gives clearer reporting and helps teams make rollout decisions based on performance data rather than assumptions.
Early lessons. Initial testing suggests short experiments — especially under three weeks — often produce unstable results, particularly in lower-volume accounts. Longer runs and avoiding simultaneous campaign changes improve reliability.
Bottom line. Performance Max is becoming more testable. Advertisers can now validate creative decisions with built-in experiments instead of relying on trial and error.
First seen. Google Ads expert spotted the update and shared his view on LinkedIn.
Google Ads rolled out a new data source diagnostics feature in Data Manager that lets advertisers track the health of their data connections. The tool flags problems with offline conversions, CRM imports, and tagging mismatches.
How it works. A centralized dashboard assigns clear connection status labels — Excellent, Good, Needs attention, or Urgent — and surfaces actionable alerts. Advertisers can spot issues like refused credentials, formatting errors, and failed imports, alongside a run history that shows recent sync attempts and error counts.
Why we care. When conversion data breaks, campaign optimization breaks with it. Even small connection failures can quietly skew conversion tracking and weaken automated bidding. This diagnostic tool helps teams catch and fix issues early, protecting performance and reporting accuracy. If you rely on CRM imports or offline conversions, this provides a much-needed safety net.
Who benefits most. The feature is especially useful for advertisers running complex conversion pipelines, including Salesforce integrations and offline attribution setups, where small disruptions can quickly cascade into bidding and reporting issues.
The bigger picture. As automated bidding leans more heavily on accurate first-party data, visibility into data pipelines is becoming just as critical as campaign settings themselves.
Bottom line. Google Ads is giving advertisers an early warning system for data failures, helping teams fix broken connections before performance takes a hit.
First seen. The update was first spotted by digital marketer Georgi Zayakov, who shared the new option on LinkedIn.
Performance Max has come a long way since its rocky launch. Many advertisers once dismissed it as a half-baked product, but Google has spent the past 18 months fixing real issues around transparency and control. If you wrote Performance Max off before, it’s time to take another look.
Mike Ryan, head of ecommerce insights at Smarter Ecommerce, explained why at the latest SMX Next.
Taking a fresh look at Performance Max
Performance Max traces its roots to Smart Shopping campaigns, which Google rolled out with red carpet fanfare at Google Marketing Live in 2019.
Even then, industry experts warned that transparency and control would become serious issues. They were right — and only now has Google begun to address those concerns openly.
Smart Shopping marked the low point of black-box advertising in Google Ads, at least for ecommerce. It stripped away nearly every control advertisers relied on in Standard Shopping:
Promotional controls.
Modifiers.
Negative keywords.
Search terms reporting.
Placement reporting.
Channel visibility.
Over the past 18 months, Performance Max has brought most of that functionality back, either partially or in full.
Understanding Performance Max search terms
Search terms are a core signal for understanding the traffic you’re actually buying. In Performance Max, most spend typically flows to the search network, which makes search term reporting essential for meaningful optimization.
Google even introduced a Performance Max match type — something few of us ever expected to see. That’s a big deal. It delivers properly reportable data that works with the API, should be scriptable, and finally includes cost and time dimensions that were completely missing before.
Search term insights vs. campaign search term view
Google’s first move to crack open the black box was search term insights. These insights group queries into search categories — essentially prebuilt n-grams — that roll up data at a mid-level and automatically account for typos, misspellings, and variants.
The problem? The metrics are thin. There’s no cost data, which means no CPC, no ROAS, and no real way to evaluate performance.
The real breakthrough is the new campaign-level search term view, now available in both the API and the UI.
Historically, search term reporting lived at the ad group level. Since Performance Max doesn’t use ad groups, that data had nowhere to go.
Google fixed this by anchoring search terms at the campaign level instead. The result is access to far more segments and metrics — and, finally, proper reporting we can actually use.
The main limitation: this data is available only at the search network level, without separating search from shopping. That means a single search term may reflect blended performance from both formats, rather than a clean view of how each one performed.
Search theme reporting
Search themes act as a form of positive targeting in Performance Max. You can evaluate how they’re performing through the search term insights report, which includes a Source column showing whether traffic came from your URLs, your assets, or the search themes you provided.
By totaling conversion value and conversions, you can see whether your search themes are actually driving results — or just sitting idle.
There’s more good news ahead. Google appears to be working on bringing Dynamic Search Ads and AI Max reports into Performance Max. That would unlock visibility into headlines, landing pages, and the search terms triggering ads.
Search term controls and optimization
Negative keywords
Negative keywords are now fully supported in Performance Max. At launch, Google capped campaigns at 100 negatives, offered no API access, and blocked negative keyword lists—clearly positioning the feature for brand safety, not performance.
These negatives apply across the entire search network, including both search and shopping. Brand exclusions are the exception — you can choose to apply those only to search campaigns if needed.
Brand exclusions
Performance Max doesn’t separate brand from generic traffic, and it often favors brand queries because they’re high intent and tend to perform well. Brand exclusions exist, but they can be leaky, with some brand traffic still slipping through. If you need strict control, negative keywords are the more reliable option.
Also, Performance Max — and AI Max — may aggressively bid on competitor terms. That makes brand and competitor exclusions important tools for protecting spend and shaping intent.
Optimization strategy
Here’s a simple heuristic for spotting search terms that need attention:
Calculate the average number of clicks it takes to generate a conversion.
Identify search terms with more clicks than that average but zero conversions.
Those terms have had a fair chance to perform and didn’t. They’re strong candidates for negative keywords.
That said, don’t overcorrect.
Long-tail dynamics mean a search term that doesn’t convert this month may matter next month. You’re also working with a finite set of negative keywords, so use them deliberately and prioritize the highest-impact exclusions.
Modern optimization approaches
It’s not 2018 anymore — you shouldn’t spend hours manually reviewing search terms. Automate the work instead.
Use the API for high-volume accounts, scripts for medium volume, and automated reports from the Report Editor for smaller accounts (though it still doesn’t support Performance Max).
Layer in AI for semantic review to flag irrelevant terms based on meaning and intent, then step in only for final approval. Search term reporting can be tedious, but with Google’s prebuilt n-grams and modern AI tools, there’s a smarter way to handle it.
Channels and placements reporting
Channel performance report
The channel performance report — not just for Performance Max — breaks performance out by network, including Discover, Display, Gmail, and more. It’s useful for channel visibility and understanding view-through versus click-through conversions, as well as how feed-based delivery compares to asset-driven performance.
The report includes a Sankey diagram, but it isn’t especially intuitive. The labeling is confusing and takes some decoding:
Google also announced that Search Partner Network data is coming, which should add another layer of useful performance visibility.
Channel and placement controls
Unlike Demand Gen, where you can choose exactly which channels to run on, Performance Max doesn’t give you that control. You can try to influence the channel mix through your ROAS target and budget, but it’s a blunt instrument — and a slippery one at best.
Placement exclusions
The strongest control you have is excluding specific placements. Placement data is now available through the API — limited to impressions and date segments — and can also be reviewed in the Report Editor. Use this data alongside the content suitability view to spot questionable domains and spammy placements.
For YouTube, pay close attention to political and children’s content. If a placement feels irrelevant or unsafe for your brand, there’s a good chance it isn’t driving meaningful performance either.
Tools for placement review
If you run into YouTube videos in languages you don’t speak, use Google Sheets’ built-in GOOGLETRANSLATE function. It’s faster and more reliable than AI for quick translation.
You can also use AI-powered formulas in Sheets to do semantic triage on placements, not just search terms. These tools are just formulas, which means this kind of analysis is accessible to anyone.
Search Partner Network
Unfortunately, there’s no way to opt out of the Search Partner Network in Performance Max. You can exclude individual search partners, but there are limits.
Prioritize exclusions based on how questionable the placement looks and how much volume it’s receiving. Also note that Google-owned properties like YouTube and Gmail can’t be excluded.
Based on Standard Shopping data, the Search Partner Network consistently performs meaningfully worse than the Google Search Network. Excluding poor performers is recommended.
Device reporting and targeting
Creating a device report is easy — just add device as a segment in the “when and where ads showed” view. The tricky part is making decisions.
Device analysis
For deeper insight, dig into item-level performance in the Report Editor. Add device as a segment alongside item ID and product titles to see how individual products behave across devices. Also, compare competitor performance by device — you may spot meaningful differences that inform your strategy.
For example, you may perform far better on desktop than on mobile compared to competitors like Amazon, signaling either an opportunity or a risk.
Device targeting considerations
Device targeting is available in Performance Max and is easy to use, much like channel targeting in Demand Gen. But when you split campaigns by device, you also split your conversion data and volume—and that can hurt results.
Before you separate campaigns by device, consider:
How competition differs by device
Performance at the item and retail category level
The impact on overall data volume
Performance Max performs best with more data. Campaigns with low monthly conversion volume often miss their targets and rarely stay on pace. As more data flows through a campaign, Performance Max gets better at hitting goals and less likely to fall short.
Any gains from splitting by device can disappear if the algorithm doesn’t have enough data to learn. Only split when both resulting campaigns have enough volume to support effective machine learning.
Conclusion
Performance Max has changed dramatically since launch. With search term reporting, negative keywords, channel visibility, placement controls, and device targeting now available, advertisers have far more transparency and control than ever before.
It’s still not perfect — channel targeting limits and data fragmentation remain — but Performance Max is fundamentally different and far more manageable.
Success comes down to knowing what data you have, how to access it efficiently using modern tools like AI and automation, and when to apply controls based on performance insights and data volume needs.
Watch: PMax reporting for ecommerce: What Google is (and isn’t) showing you
As AI-driven bidding and automation transform paid media, first-party data has become the most powerful lever advertisers control.
In this conversation with Search Engine Land, Julie Warneke, founder and CEO of Found Search Marketing, explained why first-party data now underpins profitable advertising — no matter how Google’s position on third-party cookies evolves.
What first-party data really is — and isn’t
First-party data is customer information that an advertiser owns directly, usually housed in a CRM. It includes:
Lead details.
Purchase history.
Revenue.
Customer value collected through websites, forms, or physical locations.
It doesn’t include platform-owned or browser-based data that advertisers can’t fully control.
Why first-party data matters more than ever
Digital advertising has moved from paying for impressions, to clicks, to actions — and now to outcomes. The real goal is no longer conversions alone, but profitable conversions, according to Warneke.
As AI systems process far more signals than humans can handle, advertisers who supply high-quality customer data gain a clear advantage.
CPCs may rise — but profitability can too
Rising cost-per-clicks are a fact of paid media. First-party data doesn’t always reduce CPCs, but it improves what matters more: conversion quality, revenue, and return on ad spend.
By optimizing for downstream business outcomes instead of surface-level metrics, advertisers can justify higher costs with stronger results.
How first-party data improves ROAS
When advertisers feed Google data tied to revenue and customer value, AI bidding systems can prioritize users who resemble high-value customers — often using signals far beyond demographics or geography.
The result is traffic that converts better, even if advertisers never see or control the underlying signals.
Performance Max leads the way
Among campaign types, Performance Max (PMax) currently benefits the most from first-party data activation.
PMax performs best when advertisers move away from manual optimizations and instead focus on supplying accurate, consistent data, then let the system learn, Warneke noted.
SMBs aren’t locked out — but they need the right setup
Small and mid-sized businesses aren’t disadvantaged by limited first-party data volume. Warneke shared examples of success with customer lists as small as 100 records.
The real hurdle for SMBs is infrastructure — specifically proper tracking, consent management, and reliable data pipelines.
The biggest mistakes advertisers are making
Two issues stand out:
Weak data capture: Many brands still depend on browser-side tracking, which increasingly fails — especially on iOS.
Broken feedback loops: Others upload CRM data sporadically instead of building continuous data flows that let AI systems learn and improve over time.
What marketers should do next
Warneke’s advice: Step back and audit how data is captured, stored, and sent back to platforms, then improve it incrementally.
There’s no need to overhaul everything at once or risk the entire budget. Even testing with 5–7% of spend can create a learning roadmap that delivers long-term gains.
Bottom line
AI optimizes toward the signals it receives — good or bad. Advertisers who own and refine their first-party data can shape outcomes in their favor, while those who don’t risk being optimized into inefficiency.
Google Ads introduced multi-party approval, a security feature that requires a second administrator to approve high-risk account actions. These actions include adding or removing users and changing user roles.
Why we care. As ad accounts grow in size and value, access control becomes a serious risk. One unauthorized, malicious, or accidental change can disrupt campaigns, permissions, or billing in minutes. Multi-party approval reduces that risk by requiring a second admin to approve high-impact actions. It adds strong protection without slowing daily work. For agencies and large teams, it prevents costly mistakes and significantly improves account security.
How it works. When an admin initiates a sensitive change, Google Ads automatically creates an approval request. Other eligible admins receive an in-product notification. One of them must approve or deny the request within 20 days. If no one responds, the request expires, and the change is blocked.
Status tracking. Each request is clearly labeled as Complete, Denied, or Expired. This makes it easy to see what was approved and what didn’t go through.
Where to find it. You can view and manage approval requests from Access and security within the Admin menu.
The bigger picture. The update reflects growing concern around account security, especially for agencies and large advertisers managing multiple users, partners, and permissions. With advertisers recently reporting costly hacks, this is a welcome update.
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Job Overview We’re looking for a seasoned On-Page SEO Specialist to optimize and enhance our website’s on-page SEO performance while driving multi-location performance […]
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