Originally published on The Searchless Journal
OpenAI's ChatGPT ad pilot reached $100 million annualized revenue within six weeks of launch. Over 600 advertisers have signed up, including major brands like Williams-Sonoma, Target, The Knot, DSW, and BEHR.
But early ROI data is mixed: brands cite FOMO rather than proven returns as their primary motivation. CPC prices dropped from $60 CPM at launch to as low as $25 within ten weeks, and minimum spend commitments collapsed from $250,000 to $50,000. Now OpenAI has flipped the entire model to cost-per-click at $3-$5 per bid.
Meanwhile, agency experts say GEO (generative engine optimization) may deliver more value than buying ChatGPT inventory right now. Georgia-Pacific is prioritizing GEO over paid ChatGPT ads, and agency CEOs say the ad product is "not an absolute must" at current prices.
Here is the first comprehensive look at who is spending, what the data shows, and whether brands should buy ChatGPT ads or invest in GEO first.
Six Weeks to $100 Million: Faster Than Google, Slower Than It Looks
According to Reuters, OpenAI's ChatGPT ad pilot crossed $100 million in annualized revenue within six weeks of its February 9 launch. That number sounds impressive. It is, in isolation. But context matters.
Google AdWords took roughly two years to reach $100 million in annual revenue after its 2000 launch. Facebook Ads, which launched in 2007, took about 18 months to hit a comparable milestone. By that standard, ChatGPT's pace is remarkable.
But the comparison is misleading. Google and Facebook had to invent the demand. OpenAI is walking into an industry where $600 billion is already spent annually on digital advertising, and brands are desperate for new channels as Google and Meta fatigue sets in. The $100 million was not pulled from thin air. It was redirected from budgets that would have gone somewhere else.
More important than the headline number is what it tells us about the composition of early demand. The 600+ advertisers include Williams-Sonoma, Target, The Knot Worldwide, Ford, Adobe, Expedia, DSW, and BEHR. Those are not scrappy startups gambling on a new channel. They are Fortune 500 brands with $250,000 minimum commitments. Simple math: 600 advertisers at a $250,000 entry point gets you to $150 million in committed spend before a single ad runs. The $100 million annualized run rate is not proof of performance. It is proof of FOMO.
The real test comes in Q3 and Q4. When renewal conversations happen and early movers have twelve weeks of performance data to evaluate, will they scale up or pull back? If CPC prices continue falling and conversion tracking remains incomplete, that $100 million run rate could contract as fast as it expanded.
The Pricing Collapse: A Timeline in Three Acts
The pricing trajectory of ChatGPT ads tells the real story of this market. It has moved faster than almost anyone predicted, and not in the direction OpenAI wanted.
Act 1: The Premium Launch (February 9)
OpenAI launched with CPM pricing at $60 per thousand impressions and a $250,000 minimum spend commitment. The initial roster included Target, Ford, Adobe, Mrs. Meyer's, and Expedia. This was brand money: CPM pricing with no conversion tracking, six-figure commitments, and no self-serve dashboard. The pitch was access to ChatGPT's 900 million weekly active users and 50 million consumer subscribers during high-intent research moments. For brand marketers, that is a compelling story. For performance marketers, it was unusable.
Act 2: The Slide (March-April)
Within ten weeks, CPMs had eroded from $60 to as low as $25. A leaked StackAdapt deck shared with select buyers on March 27 offered CPMs as low as $15, a quarter of the launch rate. Minimum spend was quietly reduced from $250,000 to $50,000. OpenAI launched a self-serve ads manager to a subset of advertisers on April 13, giving them real-time visibility into impressions and clicks for the first time.
The speed of this erosion is unusual. When Google launched YouTube ads, CPMs took over a year to compress meaningfully. Meta's Instagram ads maintained premium pricing for two years before normalizing. ChatGPT's 58% CPM decline in ten weeks signals that early advertisers were not seeing value proportional to the price.
Act 3: The CPC Pivot (April 22)
OpenAI turned on cost-per-click pricing inside ChatGPT, with bids between $3 and $5 per click. This is not an incremental change. It is a fundamental repositioning of the product from a brand awareness play to a performance marketing channel. The shift puts ChatGPT ads in direct competition with Google Ads (where average CPC across industries is $2.69 for search and $0.63 for display) and Meta Ads (average CPC around $1.72).
At $3-$5 CPC, ChatGPT is pricing itself at a premium to Google search, which is defensible only if the clicks convert at a higher rate. Early data on that front is thin.
| Metric | Launch (Feb 9) | Current (Apr 28) | Change |
|---|---|---|---|
| Pricing model | CPM | CPC | Complete pivot |
| CPM rate | $60 | $25 (some at $15) | -58% to -75% |
| CPC rate | N/A | $3-$5 | New |
| Minimum spend | $250,000 | $50,000 | -80% |
| Advertisers | ~10 (launch) | 600+ | 60x growth |
| Ad manager | None | Self-serve (limited) | Launched |
| Conversion pixel | None | In development | Building |
| International | U.S. only | +AU, NZ, CA | Expanding |
The trajectory is clear: OpenAI is trading margin for scale. Every pricing reduction and feature launch is designed to widen the advertiser base beyond the initial FOMO cohort. The question is whether scale alone creates a sustainable business, or whether the platform needs proof of performance to retain advertisers past the honeymoon phase.
Who Is Spending: Three Profiles, One Emotion
Digiday's April 27 report reveals the early adopter landscape. The brands spending on ChatGPT ads fall into three distinct profiles, but they share a single motivation: anxiety about being late.
Profile 1: The Offensive Positioners
BEHR Paint and Williams-Sonoma. These brands are explicit about their rationale. Andy Lopez, head of marketing at BEHR, told Digiday: "We want to be able to build some of those capabilities now so that when it is here, we're ready to be proactive, we're on the offense of it and we're not trying to catch up."
Translation: we don't know if this works, but we can't afford to find out late. This is the same logic that drove brands onto Facebook in 2009, Instagram in 2013, and TikTok in 2020. Sometimes it pays off. Sometimes it doesn't. The difference with ChatGPT is the speed: Facebook and Instagram had years of organic reach before ads became pay-to-play. ChatGPT went from zero to $250,000 minimums in six weeks.
Profile 2: The Learning Investors
DSW represents the experimental budget approach. Kelly Ballou, VP of brand and creative for North American retail at Designer Brands Inc, put it plainly: "Maybe it won't work for us, and maybe it won't be right, but I bet we'll learn something that we can apply somewhere."
This is R&D spending, not marketing spending. DSW is buying data, not customers. The risk is that "learning" becomes a permanent justification for spend that never graduates to performance accountability.
Profile 3: The Silent Watchers
The Knot Worldwide declined to share specifics. Target and Ford have not disclosed results. This silence is itself a signal. When ads perform well, brands talk about it. When brands go quiet for ten weeks after launch, it usually means the numbers don't support a victory lap.
What is conspicuously absent from the early adopter list: direct-to-consumer brands with sophisticated performance marketing operations. No Shopify darlings. No programmatic-first performance advertisers. No one whose primary metric is ROAS. The absence of performance brands tells you everything about the maturity of the platform. When DTC brands start piling in, the channel has proven itself. Until then, it is brand money buying positioning.
The Altman Pivot: From "Last Resort" to $100 Billion Bet
The speed of OpenAI's advertising about-face deserves attention, because it tells you something about the financial pressures driving these decisions.
In 2024, Sam Altman called advertising a "momentary industry." At Harvard, he described ads as a "last resort." He told interviewers that "ads-plus-AI is sort of uniquely unsettling to me" and that he liked "that people pay for ChatGPT and know the answers they're getting are not influenced by advertisers."
In a Stratechery interview, Altman said Instagram changed his mind, arguing that its ads "added value" to him.
On February 9, 2026, as ads went live, Altman posted on X: "We are starting to test ads in ChatGPT free and Go tiers. Most importantly, we will not accept money to influence the answer ChatGPT gives you, and we keep your conversations private from advertisers."
Chris Lehane, OpenAI's VP of global affairs, defended the move by arguing that advertising helps "expand democratic access" to ChatGPT. In response to Anthropic's Super Bowl commercials, which ran spots titled "Deception," "Betrayal," "Treachery," and "Violation" with the tagline "Ads are coming to AI. But not to Claude," Altman argued that Anthropic "serves an expensive product to rich people" while OpenAI needs to bring AI to "billions of people who can't pay for subscriptions."
The framing is strategic, but the economics are blunt. OpenAI faces projected losses of $14 billion this year against an $852 billion valuation. The company projects $2.5 billion in ad revenue for 2026, scaling to $11 billion by 2027 and $100 billion by 2030. Advertising is no longer a last resort. It is a financial necessity.
The competitive landscape is splitting accordingly. Google is weaving advertising into 25.5% of AI-generated search results through AI Overviews. OpenAI is building an ad platform from scratch. Perplexity and Anthropic have positioned themselves as explicitly ad-free alternatives. For the first time, the major AI companies are pursuing fundamentally different monetization strategies, which means advertisers face not just a channel decision but a philosophical one: do you buy into an ad-supported AI future, or do you bet on organic visibility in ad-free environments?
The Platform Infrastructure: What Exists, What's Missing
OpenAI has built ad infrastructure at a pace that suggests urgency rather than patience. Here is what the platform looks like as of late April.
What exists:
- Self-serve ads manager with real-time performance monitoring (impressions, clicks, spend)
- CPC pricing at $3-$5 per click
- Contextual targeting matched to conversation topic (no demographic or behavioral targeting)
- Criteo and StackAdapt as programmatic partners, with Criteo's network of 17,000 advertisers connected
- Smartly partnership for conversational ad formats beyond static placements
- International availability in U.S., Australia, New Zealand, and Canada
- Ads appear at the bottom of ChatGPT responses, labeled "sponsored" and visually separated from the answer
- Product-led queries include sponsored product cards similar to Google Shopping
- Ads shown only on free tier and $8/month Go plan. Plus, Pro, Business, Enterprise, and Education tiers are ad-free
- Advertisers cannot see user conversations, chat history, names, email addresses, or IP addresses
What's missing:
- Conversion tracking pixel is "in development" but not live. Without it, advertisers cannot measure post-click actions (purchases, sign-ups, bookings). This is the single biggest gap in the platform.
- No demographic, behavioral, or lookalike audience targeting. Contextual only.
- No retargeting capabilities.
- No A/B testing framework for ad creative.
- No API for programmatic campaign management.
- No third-party verification or brand safety reporting.
The conversion pixel is the critical missing piece. Digiday reports that the pixel will be a lightweight JavaScript snippet similar to what marketers already use with Google and Meta. When a user clicks an ad inside ChatGPT and completes an action on the advertiser's site (purchase, sign-up, booking), the pixel fires and sends data back. This closes the loop between ad spend and outcomes.
Until that pixel ships and proves reliable, ChatGPT ads remain a brand awareness channel pretending to be a performance channel. The CPC pricing model creates the expectation of performance measurement, but without conversion tracking, CPC only tells you what you paid for a click, not what that click was worth.
The Contrarian Case: Why GEO Beats Paid Right Now
The strongest case against buying ChatGPT ads today comes not from skeptics but from the advertisers themselves.
Georgia-Pacific, the $10 billion consumer products company, is explicitly prioritizing GEO over paid ChatGPT inventory. Their reasoning: establish a "consistent understanding of how our brands show up across LLMs" before investing in paid amplification. Georgia-Pacific is not a brand that avoids new channels. They are a brand that understands the difference between foundational visibility and paid placement.
Joseph Levi, CEO of Noise Media Group, put it more bluntly: "Running ads, which at the moment is essentially display ads or some type of ads alongside the answers, I don't think is an absolute must or anything which brands need to overpay for."
A Flywheel SVP was more specific: "I want to optimize GEO. That's a game you win through organic, not paid."
The GEO argument has four pillars that deserve serious consideration.
Pillar 1: Permanence vs. Rental
GEO investments (content optimization, authority building, structured data, citation architecture) create lasting organic visibility across every AI engine: ChatGPT, Google AI Overviews, Gemini, Perplexity, Claude, and whatever launches next quarter. Paid ChatGPT ads provide visibility only while you are paying, and only on ChatGPT.
The math is simple. A GEO investment of $50,000 that gets your brand cited organically in AI answers across five platforms for 12 months costs less than two months of ChatGPT ad spend at the former $250,000 minimum. And the GEO citation shows up as a recommendation, not a sponsored placement.
Pillar 2: Trust Architecture
This is the underdiscussed advantage. When ChatGPT recommends your brand as part of an organic answer, it carries the authority of the AI's analysis. When your brand appears as a "sponsored" card at the bottom of that same answer, users process it as advertising, which decades of research shows they discount accordingly.
A 2025 Edelman trust survey found that 63% of consumers trust AI-generated product recommendations less when they know ads are involved. The very presence of a "sponsored" label may undermine the credibility that makes AI answers valuable in the first place. Brands that invest in organic AI visibility avoid this trust penalty entirely.
Pillar 3: Platform Independence
ChatGPT's ad platform is 11 weeks old. Policies, pricing, inventory, and targeting will change, potentially dramatically. CPMs have already fallen 58%. Minimums have dropped 80%. The pricing model has pivoted entirely. If you build your AI visibility strategy on paid ChatGPT inventory, you are building on a foundation that has already shifted three times since February.
GEO strategies are platform-agnostic by nature. A well-structured citation profile that gets your brand recommended by ChatGPT will also improve visibility in Google AI Overviews, Perplexity, and other engines. You are not betting on a single platform's policy decisions.
Pillar 4: Compound Returns
GEO investments compound. Every piece of optimized content, every structured data improvement, every authority signal you build makes the next one more effective. Paid ads are linear: you spend, you get impressions, you stop spending, impressions stop. Over a 12-month horizon, GEO delivers accelerating returns while paid delivers flat or declining efficiency as competition increases.
The AI Visibility Framework: A Decision Tool for Brands
Based on the data above, here is a practical framework for deciding how to allocate budget between GEO and ChatGPT ads. It is built around four questions.
Step 1: Audit Your Organic AI Visibility
Before spending a dollar on ChatGPT ads, you need to answer one question: when someone asks ChatGPT about your product category, does your brand appear in the answer?
If the answer is yes, you have a foundation. Paid ads can reinforce that organic presence. If the answer is no, you have a more fundamental problem than ad placement. You are invisible in the fastest-growing search channel in history, and no amount of sponsored cards will fix that.
Run the audit across multiple AI engines (ChatGPT, Google AI Overviews, Perplexity, Claude) for your top 20 brand and category queries. Document where you appear, where competitors appear, and where the AI surfaces no specific brand at all.
Step 2: Score Your Category Fit
Not every product category benefits equally from conversational AI discovery. Score your category on three dimensions:
- Research intensity: Do customers research, compare, or evaluate before buying? (High: electronics, home improvement, financial products. Low: impulse purchases, commodity goods.)
- Conversational entry point: Do people naturally describe their needs in sentence form? ("What paint should I use for a bathroom with high humidity?" vs. "buy paper towels")
- AI answer richness: Do AI engines provide substantive, multi-source answers for your category, or thin responses with few citations?
Score 2+ out of 3: ChatGPT ads may be worth testing now. Score 1 or 0: prioritize GEO until the platform develops more sophisticated targeting.
Step 3: Evaluate Your Measurement Maturity
Be honest. Do you have the infrastructure to measure ChatGPT ad performance without OpenAI's conversion pixel? Can you track clicks through UTM parameters, attribute conversions through your existing analytics stack, and isolate ChatGPT-driven traffic from other sources?
If yes: you can run a controlled experiment. If no: wait for the pixel. Spending money without measurement is not experimentation. It is charity.
Step 4: Set Budget Parameters
If you proceed with ChatGPT ads, define these parameters before your first campaign:
- Maximum CPC you are willing to pay ($3-$5 is current market; set your ceiling)
- Total experimental budget (recommend 5-10% of your monthly search ad spend)
- Clear stop-loss threshold (e.g., pause after $X spend without a conversion)
- Minimum test duration (recommend 8 weeks minimum to gather meaningful data)
- Specific learning objectives (what will you know after this test that you don't know now?)
The Decision Matrix
| Scenario | Recommendation |
|---|---|
| Strong organic AI visibility + high category fit + measurement ready | Test ChatGPT ads with 5-10% of search budget. Run parallel GEO maintenance. |
| Weak organic visibility + high category fit + measurement ready | Invest in GEO first. Test ChatGPT ads only after organic citations are established. |
| Strong organic visibility + low category fit | Skip ChatGPT ads. Double down on GEO and traditional search. |
| Weak organic visibility + low category fit | Skip both. Your customers aren't using AI to find you yet. |
| Any scenario + no measurement infrastructure | Wait for the conversion pixel. Period. |
The $100 Billion Question: What OpenAI's Projections Assume
OpenAI projects $2.5 billion in ad revenue for 2026, $11 billion by 2027, and $100 billion by 2030. For perspective, Google's annual ad revenue is approximately $200 billion. Meta's is approximately $130 billion. Achieving $100 billion would make ChatGPT ads the third-largest advertising platform on Earth within four years.
Let's stress-test this.
To reach $100 billion by 2030, ChatGPT ads need to compound at roughly 215% annually from their current $100 million run rate. That requires several things to go right simultaneously:
User scale must translate to ad inventory. ChatGPT's 900 million weekly active users are impressive, but only free tier and Go plan users see ads. Paid subscribers on Plus, Pro, Business, Enterprise, and Education tiers are ad-free. If 50 million users are paid subscribers (as OpenAI has disclosed), that leaves roughly 850 million free/Go users as the addressable ad audience. That's large, but the monetization potential per user depends on how often they trigger ad-bearing queries and how many ad slots OpenAI inserts per conversation. At one ad per conversation and an average of 5 conversations per day per user, that's 4.25 billion daily ad impressions. At $25 CPM, that's roughly $106 million per day or $38.7 billion annually. To reach $100 billion, you need either higher CPMs (which are falling), more ad slots per conversation (which degrades user experience), or more ad-bearing queries per user.
The conversion pixel must work. Without closed-loop measurement, ChatGPT ads cannot compete for performance budgets beyond the experimental phase. Google and Meta built their empires on conversion data. If OpenAI's pixel launches late, underperforms, or faces privacy pushback, the $100 billion target becomes fantasy.
International expansion must accelerate. ChatGPT ads launched in the U.S. on February 9 and expanded to Australia, New Zealand, and Canada by mid-April. That's four countries in ten weeks. Global coverage requires navigating vastly different privacy regimes, advertising regulations, and language targeting. Europe alone is a regulatory minefield under the AI Act and GDPR.
Ad formats must evolve beyond "sponsored answers." The current format is essentially display advertising adjacent to AI-generated content. To capture $100 billion, OpenAI needs shoppable recommendations, in-conversation purchase flows, app install campaigns, lead generation, and probably formats that don't exist yet. The Smartly and Criteo partnerships suggest they are thinking about this, but building a full ad format catalog takes years, not months.
My prediction: ChatGPT ads reach $8-$15 billion by 2030, not $100 billion. That would still make it a top-10 global ad platform and a legitimate fourth player alongside Google, Meta, and Amazon. But the $100 billion number assumes a perfect execution that no ad platform in history has achieved.
What to Do This Quarter
The brands that win the AI advertising era will not be the ones who spent the most in April 2026. They will be the ones who built durable visibility that compounds over time. Here is the practical playbook.
Week 1-2: Audit. Run comprehensive AI visibility audits across ChatGPT, Google AI Overviews, Perplexity, and Claude for your top 20 brand and category queries. Document gaps. Identify which competitors are being cited and why.
Week 2-4: GEO foundation. Address the gaps identified in your audit. Optimize content for AI citability. Build structured data. Improve authority signals. This is the highest-ROI investment you can make in AI visibility right now.
Week 4-6: Evaluate. Re-run the audit. Measure improvement. If your organic citations are growing, you have validation that GEO works. If they are flat, adjust your strategy before adding paid spend.
Week 6-8: Controlled ad test (optional). Only if your audit showed strong organic visibility and you have measurement infrastructure in place. Allocate 5-10% of monthly search budget. Set strict stop-loss parameters. Focus on learning, not scaling.
Ongoing: Monitor three metrics. (1) Your organic citation rate across AI engines. (2) ChatGPT ad CPC trends. (3) The conversion pixel launch date. When the pixel ships, the calculus changes. Until then, treat paid ChatGPT ads as an experiment with a capped budget and a clear expiration date.
The Bottom Line
ChatGPT ads at $100 million annualized is a real milestone, but it tells you more about advertiser anxiety than about channel performance. The pricing has collapsed faster than any major ad platform in recent memory. The brands spending money are doing it for positioning, not because the numbers work. The conversion tracking pixel is still not live. And the smartest advertisers in the room, companies like Georgia-Pacific with the budgets to go anywhere, are choosing GEO instead.
The winners in AI advertising will not be determined by who bought the first $250,000 campaign. They will be determined by who built the strongest organic presence across every AI engine, then layered paid on top of that foundation at the right time, with the right data.
That time is not April 2026 for most brands. But it is coming. And when it does, the brands with GEO foundations will be positioned to capitalize on it within weeks, while the brands that skipped organic will be starting from zero.
See How Your Brand Appears in ChatGPT Answers Before Buying Ads
You wouldn't buy Google Ads without knowing your organic ranking. The same logic applies to AI search. Our AI Visibility Audit shows exactly where your brand appears in ChatGPT, Google AI Overviews, Perplexity, and Claude responses for your top category queries, and identifies the specific gaps between you and the brands AI engines are citing today.
Get Your Free AI Visibility Audit
Sources
- Reuters, "OpenAI projects $2.5 billion in ad revenue this year, $100 billion by 2030" (April 9, 2026)
- Digiday, "Marketers join OpenAI's ad pilot, nudged by FOMO" (April 27, 2026)
- Digiday, "OpenAI turns on cost-per-click ads inside ChatGPT" (April 22, 2026)
- Digiday, "OpenAI builds tool to track whether ChatGPT ads convert" (April 14, 2026)
- The Next Web, "OpenAI shifts ChatGPT ads to cost-per-click as $60 CPM erodes in ten weeks" (April 22, 2026)
- Search Engine Journal, "ChatGPT Ads Now Offer CPC Bidding Between $3 And $5" (April 21, 2026)
- AdWeek, "Leaked Deck Reveals StackAdapt's Playbook for ChatGPT Ads" (April 2026)
- AdWeek, "Code in OpenAI's Ads Manager Suggests Conversion Tracking" (April 2026)
- PPC Land, "ChatGPT ad CPMs drop to $25 as OpenAI races toward global auction" (April 17, 2026)
- ExchangeWire, "Price Drops for ChatGPT Ads" (April 20, 2026)
- Adobe, "AI Traffic Report Q2 2026" (55% of shoppers use AI for shopping inspiration)
- OpenAI, "Scaling AI for Everyone" (900M+ weekly active users, 50M+ consumer subscribers)
- Forbes Agency Council, "How Smart Brands Are Approaching ChatGPT Ads Right Now" (April 20, 2026)
FAQ
How much revenue has ChatGPT ads generated?
ChatGPT ads reached $100 million in annualized revenue within six weeks of the February 9, 2026 launch, according to Reuters. Over 600 advertisers have signed up. OpenAI projects $2.5 billion in ad revenue for 2026 and $11 billion by 2027.
Which brands are spending on ChatGPT ads?
Early adopters include Williams-Sonoma, Target, The Knot Worldwide, Ford, Adobe, Expedia, DSW, BEHR, and Mrs. Meyer's. These span home goods, retail, automotive, weddings, footwear, and paint categories. Performance-first DTC brands are notably absent.
Why have ChatGPT ad prices dropped so fast?
CPM prices dropped from $60 at launch to as low as $25 (some reports cite $15 via StackAdapt) within ten weeks, a 58-75% decline. Minimum spend fell from $250,000 to $50,000. OpenAI then pivoted to CPC pricing at $3-$5 per click. The compression suggests early performance did not justify premium pricing and that OpenAI is trading margin for advertiser scale.
Should brands invest in ChatGPT ads or GEO first?
Multiple agency experts and brands including Georgia-Pacific recommend prioritizing GEO (generative engine optimization) before paid ChatGPT ads. GEO creates lasting organic visibility across all AI engines. Paid ads only provide visibility while you are paying, and only on ChatGPT. The strongest position is organic AI visibility first, then paid amplification on top.
What ad platform features does OpenAI have?
OpenAI has launched a self-serve ads manager with real-time monitoring, CPC pricing at $3-$5, contextual targeting, and partnerships with Criteo and StackAdapt. A conversion tracking pixel is in development but not yet live. Ads appear on the free tier and Go plan only; paid subscribers see no ads.
What is GEO and how does it compare to ChatGPT ads?
GEO (generative engine optimization) is the practice of optimizing your content and digital presence so that AI engines like ChatGPT, Google AI Overviews, Perplexity, and Claude cite your brand organically in their answers. Unlike paid ads, GEO visibility is not dependent on ongoing ad spend and works across all AI platforms simultaneously.
Compare ChatGPT Ads vs Google Ads Pricing and Strategy
Is ChatGPT inventory worth testing alongside your existing search budget? See how CPC rates, targeting capabilities, and measurement maturity compare across platforms.
Top comments (0)