Tag: AI Ads

Is Your Ad Spend on ChatGPT Working? Here’s the Uncertain Truth
As I explore the burgeoning ad platform of ChatGPT, it’s clear that its potential isn’t quite ready to fulfill the demands of performance marketing just yet. Many early adopters, myself included, are facing challenges with proving the impact of our advertising dollars.

The big picture. According to insights from The Information, ChatGPT’s advertising options offer scant data and are devoid of automated purchasing tools. This severely limits our ability to determine if the money we’re spending is making any significant difference.

What advertisers are dealing with. I found digital marketer Glenn Gabe’s breakdown of the issues particularly telling:
- No easy, automated method for buying ad space — everything from deals to negotiations still happens through traditional means like phone calls, emails, and spreadsheets.
- Lack of substantial performance data to properly assess our campaigns.
- Feedback from two agency executives mirrors my experience — there’s no measurable proof that these ads translate into business results for our clients.
Why I care. Delving into ChatGPT as an advertising channel means leaping without a safety net. The absence of performance metrics leaves us in the dark when it comes to ROI validation. Although OpenAI plans to scale ads to all US free users soon, the essential measurement tools are sadly lagging behind.

Jumping in at this stage requires one to manage expectations clearly — treating any foray as an experimental budget rather than a reliable performance avenue.

What’s on the horizon. I’m informed that OpenAI intends to display ads to all US users on the free and affordable ChatGPT versions in the coming weeks — marking a notable expansion from its current pilot. Advertisers are also advised to boost performance by offering more text and visual creative variations.

The irony. OpenAI, known for developing cutting-edge AI, still relies on basic tools akin to spreadsheets for ad reporting. It’s quite ironic and frustrating.

The bottom line. Despite the soon-to-be-expanded audience reach of ChatGPT ads, the infrastructure necessary to prove their value remains lacking. Those of us currently involved are spending with limited insight — essentially paying to float in the unknown.

Credit. Much appreciation to Gabe for sharing key points from The Information’s article on X.

Dig deeper. For those eager for more detail, the full article ‘OpenAI’s First Advertisers Can’t Prove ChatGPT Ads Work’ is available (subscription needed) at The Information.

Inspired by this post on Search Engine Land.
March 23, 2026
Google’s AI Mode: Revolutionizing Ad Monetization

As I explore the ever-evolving landscape of Google’s AI Mode, it’s fascinating to witness how ad formats, reporting, and control are taking shape. Google seems to have a master plan in place that competitors just can’t keep up with.

I find myself intrigued by Google’s entry into this next phase of conversational search. It’s not just about user numbers but who can effectively monetize them. Google’s mature ad systems and extensive advertiser base offer a significant edge.

The initial panic surrounding Google’s position is over. Google’s long-standing advantages and huge investments have leveled the playing field with ChatGPT in LLM search.

Back in December 2025, when Google declared code red, it became clear that they were serious. Apple’s decision to partner with Google for its AI needs is indeed telling.

Initially, it seemed plausible that Google would struggle against ChatGPT, but the market has since adjusted its views. The company’s valuation reflects renewed confidence, rivaling even Apple at a substantial $3.6 trillion.

As I dive deeper into how monetization will shape this race, I’m struck by how Google’s recent advances have significantly boosted its valuation.

It’s clear that the visibility of financial projections plays a massive role in how the company is perceived financially. Google’s approach to shifts in user behavior is crucial in maintaining its robust business model.

From my perspective, much of your digital advertising budget likely goes to Google. Its prominence demands attention, not just in search but also in emerging AI platforms like ChatGPT and Claude.

The competition in LLM conversations is intriguing. Google and ChatGPT are vying for different monetization models, a fascinating case study of differing strategies.

For those of us in advertising, it’s essential to monitor developments like ad formats, rollout pace, and public reception to ads within these platforms.

OpenAI’s current monetization model is intriguing but still nascent, reliant on a small group of major advertisers. We’ll see how they expand and fine-tune this model over time.

Outsourcing inventory to programmatic partners is a smart move for OpenAI but highlights their early stage in building an ads business.

For Google advertisers, the shift to AI Mode need not be alarming. I’m watching for the ways these LLM sessions are shaping user experiences and ad placements.

One thing is for sure; the enhancements in AI Mode continue, promising more seamless and user-friendly interactions. The potential for ads remains, though their form is still evolving.

Monitoring key areas like the extent of monetization, advertiser control, and campaign types becomes more important as we navigate this new landscape.

Ultimately, the future of advertising in AI-driven search is one of adaptability and strategic planning, aligning closely with user and advertiser behaviors in this exciting yet challenging era.

Inspired by this post on Search Engine Land.

March 19, 2026
Unlocking the Future: OpenAI’s New Ads Manager for ChatGPT

As someone who’s been following OpenAI’s journey, I’m excited to share that they’re laying the groundwork for ChatGPT’s advertising business. These early steps reveal that OpenAI has more work to do to measure up against major players like Google when it comes to performance and ROI.
What’s happening. OpenAI has started testing an Ads Manager dashboard with a select group of partners, confirmed by sources at ADWEEK. This tool, aimed at marketers, allows for real-time campaign launching, monitoring, and optimization, drawing parallels with the established digital advertising management platforms.
Why it matters to me. OpenAI is building a self-serve advertising ecosystem around ChatGPT with the Ads Manager, in preparation for AI assistants becoming a significant channel. As conversational search becomes more prevalent, I believe it’s crucial for marketers like us to consider visibility in AI-driven responses, expanding beyond traditional platforms like Google Search.
Getting in on this early means we could gain unique insights into performance, formats, and optimization strategies within this fresh advertising landscape.
How it works now. For now, early testers are receiving weekly CSV performance reports, which include metrics like impressions and clicks. It’s evident that the ads product is in its initial stages, and more advanced analytics and tools are likely as the program matures.
The challenge: Initial tests indicate click-through rates for ChatGPT ads are lagging behind those of Google Search, marking a significant hurdle for OpenAI as they strive to showcase the value of advertising within conversational AI.
The cost of entry. Reports suggest that some early advertisers are being asked to commit a minimum of $200,000 in spend, significantly raising the stakes for OpenAI to deliver demonstrable performance and ROI.
Between the lines. Building an effective ad ecosystem entails more than just ad inventory. As marketers, we expect comprehensive reporting, optimization tools, and reliable performance — areas where established platforms like Google have a considerable head start.
The bottom line. OpenAI is laying the foundation for a revolutionary advertising platform within ChatGPT. The challenge is whether they can persuade brands to reallocate budgets by proving that conversational ads can compete with traditional search results.

Inspired by this post on Search Engine Land.

March 16, 2026
Master Google Ads Audits: Navigate the Changes in 2026

I recently tuned into an episode of Google’s Ads Decoded podcast where Brandon Ervin, Director of Product Management for Google Search Ads, shared insights on campaign consolidation, AI Max, and the future of advertiser control as we approach 2026. It was enlightening to hear a product team so in tune with advertiser concerns.

However, I felt the podcast left some gaps. There’s a significant disconnect between Google’s narrative and what advertisers truly experience on the ground. While Ervin’s team is making strides, the fast-evolving platform presents new challenges, shifting performance measurement onto economic standards. This change fundamentally alters how we should approach search ad audits.

As I reflect on recent improvements, it’s clear that enhancements like brand exclusions in Performance Max and Demand Gen, exclusion of site visitors in PMax campaigns, and improved search term visibility are crucial. These are responses to issues caused by bundling and aggressive automation. It’s worth noting that these controls arrived after advertisers were already knee-deep in implementation.

In an era where Google’s product team pushes for advancement, it’s vital for us to audit whether these new tools genuinely expand control or simply restore baseline transparency lost with earlier automation efforts.

In building the foundation for a 2026 search audit, we need to start with the basics, ensuring full ad extensions, strategic automated bidding, and maintaining negative keyword lists, among others. These are undeniable essentials that set the stage for deeper audits.

Focusing on the intricacies of signal architecture, I realize that while traditional controls like exact match and manual bids gave us direct oversight, the new controls shift focus to data quality, density, and selectivity. These influence the algorithm, which ultimately makes the decisions.

An effective audit in this context addresses three core aspects: the quality of the data imported, the density of high-quality data available for modeling, and the selectivity of the data shared with Google. These elements are pivotal in shaping campaign success.

Being mindful of incrementality is another key consideration. Google optimizes towards reported conversions, often encompassing brand search and retargeting signals that may not truly reflect incremental gains.

It’s critical to analyze marginal returns as Google’s system operates on a blended cost-per-action model. Without understanding the incremental cost at each spend tier, advertisers risk overspending without realizing diminishing returns.

Furthermore, as Ervin acknowledged, AI-driven campaigns sometimes misalign with intended targets. Query mapping has deteriorated over time, and AI Max exacerbates irrelevant matches, underlining the need to rigorously classify queries by intent to maintain high-value engagements.

Lastly, the economics of network performance in bundled campaigns like Performance Max and Demand Gen need thorough examination as they obscure valuable insight into actual network-driven outcomes.

By focusing on value redistribution through audits, we can ensure that the surplus value generated by high-intent searches isn’t misallocated into Google’s weaker inventory, thereby optimizing ad spend efficiency and accountability.

Inspired by this post on Search Engine Land.

March 13, 2026
Google Hints at Ads in Gemini: A Shift in Strategy
I recently came across some interesting news about Google and its potential plans to incorporate ads into its Gemini AI app. A senior executive at the company shared with WIRED that ads in Gemini are not out of the question — a stark contrast to previous denials just a few months ago.

What’s changed: Back in January, Google DeepMind CEO Demis Hassabis assured reporters at Davos that there were no plans to introduce ads in Gemini. However, now Google’s SVP Nick Fox has hinted otherwise, mentioning that insights gained from ads in AI Mode could eventually be applied to Gemini.

The current strategy. Instead of rushing into ads within Gemini, Google is leveraging AI Mode — a search product powered by Gemini — as a testing ground for advertising formats in AI settings.

Here’s how they’re currently managing it:
- Ads are distinct from organic results and clearly labeled.
- Only relevant ads are displayed — if there’s nothing that fits, no ads are shown.
- Google’s extensive experience in search ads informs this approach.
Why we care. Advertising is at the core of Google’s business model. How they introduce ads into AI products like Gemini will have a significant impact on the industry and influence how AI companies monetize their free services. Brands that can position themselves effectively within these conversational AI platforms now will gain a crucial advantage.

The bigger picture. Google, with its strong financial backing, is in a comfortable position to proceed at a steady pace, having surpassed $400 billion in revenue in 2025. In contrast, OpenAI is under pressure to more than double its $30 billion revenue target this year and has already begun testing ads in ChatGPT’s free tier.

Between the lines: Fox’s remarks are strategically cautious but enlightening. By framing Gemini ads as a “prioritization question” rather than a debate of values, Google hints that it’s more about when the ads will appear, not if.

What to watch: There’s an intriguing aspect of Gemini called Personal Intelligence, which extracts data from a user’s Gmail, Photos, and Calendar. Fox considers personalization to be critical for search, and it may eventually integrate into the broader Search experience. If that occurs, advertisers could tap into a new realm of contextual targeting, though user data will strictly remain unsold and unshared.

What’s next. Advertisers should start preparing now. As Google fine-tunes AI ad formats in AI Mode, these insights will make their way to Gemini. Brands that master the art of being relevant in context-driven, conversational AI environments will be well ahead when the opportunity for advertising in Gemini fully materializes.

Dig deeper. For a more detailed exploration of Google’s advertising strategy in Gemini, check out the full article on WIRED.

Inspired by this post on Search Engine Land.
March 12, 2026
Get Ready for ChatGPT Ads: A New Era in Demand Capture
I’ve been keeping an eye on the latest developments in AI advertising, and it’s time to prepare for something big: ChatGPT ads are on the horizon. As consumers shift towards shopping through AI prompts, ChatGPT could potentially rival search as a powerful demand-capture channel, leading to a redirection of ad budgets.

Recently, OpenAI began testing ads in ChatGPT for a limited group of U.S. users, clearly marking these placements as sponsored content. Based on the platform’s internal dynamics, it won’t be long before this feature becomes widely available.

As advertisers, we have a unique opportunity to tap into a fresh demand-capture channel. However, it’s crucial to approach this space with clear expectations and understanding.

For ChatGPT advertising to truly succeed, consumer behaviors will need to evolve. And even if they do, remember that ChatGPT won’t expand the market but rather, redistribute it.

Why ChatGPT is Embracing Ads

It’s no shock that ChatGPT is moving towards advertising. Running an LLM query is estimated to be ten times the cost of a simple search query. With users generating 2.5 billion prompts daily, expenses pile up swiftly.

The core difference here isn’t just a model shift; it’s the data landscape. Over the years, users have fed personal information into ChatGPT, giving it insights unmatched by traditional advertising tools. The burning question is how ChatGPT will use this data to target its users effectively.

Advertisements have traditionally relied on repetition to generate demand, whereas search meets buyers with intent. ChatGPT might forge a similar path, equipped with more user context.

Imagine this: asking which security camera works with a certain system and receiving an informed answer and purchase link because the platform already knows about your existing setup.

Should this happen, ChatGPT could be the first new demand-capture channel since Google’s PPC ads launched two decades ago. Yet, obstacles remain.

Today’s AI queries largely lack buying intent, serving more informational needs. When buying happens, the conversion tracking might fall short due to users completing purchases on platforms like Amazon or Google after doing their research on ChatGPT.

Don’t be discouraged; such challenges are surmountable. Google’s journey from a homework help tool to shopping powerhouse wasn’t overnight. Likewise, ChatGPT will need time to educate consumers about shopping through AI.

While a brand-new demand-capture platform is exciting, have realistic expectations about its potential.

Market Share Reality Check

Despite the capabilities of AI, it won’t expand the advertising marketplace. ChatGPT ads won’t magically bring a wave of new consumers.

Instead, it will capture pieces of the existing market shared by Google, Meta, and Amazon. It’s more about shifting budgets rather than expanding them.

Competition will be fierce, particularly with Google’s AI platform, Gemini, presenting a formidable challenge. Market consolidation seems inevitable as AI races towards profitability.

The Differentiator: Hyper-Personalization

AI’s true edge might be in hyper-personalization. With their vast knowledge of user preferences, these platforms can deliver perfectly tailored recommendations.

This feature could make AI incomparable, offering personalized results seamlessly. However, this comes with risk, as hyper-personalization might feel invasive to some users.

If AI can maintain trust and avoid crossing privacy boundaries, its personalized convenience will likely be favored by most.

Steps to Take Now

While widespread ChatGPT advertising is still on the horizon, preparation is key. Here’s how to get ahead:
- Align on Measurement: Consider research-heavy metrics and assisted conversions.
- Optimize Mobile UX: Ensure a smooth, fast purchasing experience to avoid loss in demand capture.
- Plan Early Tests: Testing carries risks but can provide an early competitive edge.
Being strategic now will set the stage for success when ChatGPT advertising becomes fully operational.

Inspired by this post on Search Engine Land.
March 9, 2026