Advertising Inside ChatGPT: The Beginning of Conversational Advertising
For most of digital advertising history, marketers have been trying to infer what people want from very small pieces of evidence. A Google search might contain four words. A Facebook profile might contain demographic signals and browsing behavior. A website visit might tell us which product page somebody viewed before disappearing into t…
That is what makes advertising inside ChatGPT more interesting than simply the arrival of another large advertising platform. ChatGPT Ads began testing in the United States in February 2026 and expanded rapidly throughout the year, with self-service advertising now available across more than 60 countries, including Qatar, the UAE, Saudi Arabia, Lebanon, and much of Europe and Asia. OpenAI said in August that ChatGPT Ads had reached a $1 billion annualized revenue run rate in less than 200 days and was already being used by tens of thousands of advertisers. In October, OpenAI said ChatGPT itself was reaching 1.2 billion people weekly. Those numbers immediately make ChatGPT a meaningful advertising environment, but scale is not what makes the format strategically unusual.
The more important change is the nature of the signal available before an advertisement appears. People do not only type, "best hotel Rome." They might explain that they are traveling to Rome for four nights with elderly parents, want somewhere near major attractions but away from heavy nightlife, require adjoining rooms, prefer a breakfast buffet, and have a specific budget. Someone shopping for software might describe the size of their team, existing technology stack, budget ceiling, security requirements, frustrations with their current provider, and which capabilities matter most. Someone furnishing an apartment may gradually explain the dimensions, style, color palette, pets, budget, delivery deadline, and which pieces they already own.
Traditional advertising spends enormous effort trying to reconstruct that kind of intent from behavioral signals. Conversational advertising begins much closer to the intent itself.
The Ad Is Entering the Conversation
ChatGPT Ads currently appear separately below ChatGPT responses rather than being embedded invisibly inside the answer. Each standard ad can include the advertiser's identity, title, descriptive copy, landing page, and image, while OpenAI explicitly separates sponsored placements from the model's organic response. Ads do not influence what ChatGPT answers, advertisers cannot pay to change or rank the answer, and advertisers do not receive access to users' conversations. Ads may currently appear to eligible adult users on Free and Go plans, while Plus, Pro, Business, Enterprise, and Edu users are not shown ads.
That separation matters because conversational interfaces operate on trust differently from search-result pages or social feeds. When someone searches Google, people already understand that paid listings may appear above organic results. When someone scrolls Instagram, advertising has been embedded within the feed for years. ChatGPT is different because users often experience the assistant as something closer to an adviser, researcher, tutor, brainstorming partner, or problem-solving interface. If commercial influence silently altered the answer, the distinction between advice and advertising would become extremely difficult to trust.
OpenAI has therefore built the advertising model around the idea that the answer and the ad remain separate systems. The organic answer is supposed to remain optimized for helpfulness, while the advertisement is an additional sponsored option displayed alongside that interaction when relevant. OpenAI's advertising policies also restrict ad placement around sensitive contexts, including high-stakes or emotionally vulnerable conversations where commercial messages could undermine trust or create an inappropriate experience. That makes ChatGPT Ads fundamentally different from an auction in which the advertiser simply pays enough money to appear beside any matching phrase. The context of the conversation matters both commercially and from a suitability perspective.
Keywords Are No Longer the Main Language of Targeting
For marketers accustomed to Google Ads, one of the biggest adjustments is that ChatGPT Ads are not primarily built around keyword lists. Advertisers organize campaigns into ad groups representing particular products, themes, use cases, or customer needs, and can then provide context hints describing situations in which those ads may be useful. OpenAI says these hints can describe what the product offers, who it helps, and when it becomes relevant. The advertising system combines those signals with the ad itself, landing-page content, and conversational intent to decide when a particular advertisement may fit.
That sounds like a subtle interface change, but it forces marketers to think differently. A keyword such as "accounting software" tells you what somebody searched. A context hint such as "small business owners trying to replace spreadsheets with accounting software that supports invoicing and multiple currencies" describes a situation. The second statement is closer to the way people actually explain needs during a ChatGPT conversation. It gives the advertising system more contextual information without requiring the marketer to predict every phrase someone might use.
This may eventually make customer understanding much more important than keyword research. Search advertising rewarded marketers who became extremely good at discovering the language people typed into search boxes. Conversational advertising rewards marketers who understand the circumstances in which a product becomes useful. That means use cases, constraints, motivations, frustrations, decision criteria, and customer situations become inputs into media targeting rather than merely material for a persona presentation nobody opens after the strategy meeting.
Imagine a company selling portable power stations. Traditional keyword research might identify terms such as "portable battery," "power station," "camping generator," "backup electricity," and brand comparisons. A ChatGPT advertising strategy could instead map situations: someone planning a remote camping trip, somebody preparing for frequent power cuts, a photographer needing electricity on location, an RV owner comparing battery capacity, or a homeowner building an emergency kit. Those are not simply synonyms. They are different moments with different reasons to buy, which means they may also deserve different creative messages.
Conversational Intent Can Be Much Richer Than Search Intent
Search marketers often categorize intent using labels such as informational, navigational, commercial, and transactional. The framework is useful but crude because one short query can hide many motivations. Someone searching "best CRM" could be a student researching software, a consultant writing an article, an employee investigating competitors, or a company preparing to spend $100,000 a year on technology. Advertising systems use additional signals to improve that guess, but the query remains incomplete.
Inside ChatGPT, the conversation can reveal the problem incrementally. A user might begin by asking what CRM software does, then explain that they manage a twenty-person sales team, ask whether Salesforce is too complicated, compare HubSpot and Zoho, mention that the company operates in three countries, ask about WhatsApp integration, and eventually request a shortlist below a specific annual budget. The commercial intent becomes clearer with every exchange. The interface therefore allows intent to develop rather than treating the original prompt as the only meaningful signal.
This may produce advertising moments that feel more natural than many existing formats because the advertisement can arrive after the user has articulated a relevant need. OpenAI describes ChatGPT Ads as a way for businesses to reach people while they explore options, compare alternatives, evaluate trade-offs, and make decisions. That is particularly interesting because these are precisely the stages where traditional digital advertising struggles with attribution. A user may spend an hour researching before visiting any advertiser's website, leaving most of the important decision process invisible to conventional analytics.
The opportunity for marketers is not simply better targeting. It is the possibility of participating closer to the moment when a decision is actually taking shape. A display banner may interrupt someone reading an unrelated article. A social advertisement may introduce a product while somebody is entertaining themselves. A search advertisement responds to explicit demand. A conversational advertisement can potentially surface while someone is actively reasoning through the problem the product solves.
This Does Not Mean ChatGPT Knows Everything About the User
The richness of conversational context inevitably creates privacy questions, and marketers need to understand the limits before imagining some dystopian targeting dashboard containing every private conversation a person has ever had. OpenAI says conversations remain private from advertisers and user data is not sold to advertisers. Advertisers do not receive the conversation that caused an ad to appear, and they cannot inspect individual users or access private chat histories through Ads Manager. Advertising personalization can use selected signals from a user's broader ChatGPT experience where personalization is enabled, but the platform does not turn conversations into advertiser-accessible profiles.
There are also differences by market because privacy regulation affects what forms of personalization are available. For example, OpenAI's advertiser documentation currently advises marketers not to rely on custom-audience targeting for campaigns in the European Economic Area or Switzerland while ads personalization is unavailable there. That is another reason marketers should avoid assuming one global ChatGPT advertising strategy will work identically everywhere. The platform is expanding rapidly, but regional privacy and advertising rules continue shaping what capabilities can be used.
This boundary is strategically important because ChatGPT advertising will probably succeed only if users continue believing that explaining more to ChatGPT does not mean handing the same information directly to advertisers. Conversational interfaces become useful precisely because people provide context. If every personal detail felt like something likely to be sold to a marketer, users would rationally become less willing to provide that context. The advertising model therefore depends on preserving a separation between understanding enough context to deliver relevance and exposing the underlying conversation to the advertiser.
The Creative Has to Become More Useful
ChatGPT Ads also challenge one of advertising's most persistent habits: trying to say something clever before saying something useful. In a conversational environment, users are often trying to accomplish a specific task, and an advertisement that interrupts that process with vague branding language may feel especially irrelevant. OpenAI's own advertiser guidance recommends clear, specific, benefit-focused copy that explains what the product offers, who it is useful for, and when it might help. It explicitly encourages advertisers to create multiple distinct angles rather than simply producing minor variations of the same message.
Consider the difference between "Transform Your Business Today" and "Automate invoices and expense tracking for small businesses." The first sounds like advertising because it could describe almost any B2B product ever created. The second helps someone immediately decide whether the offer is relevant to what they are trying to do. Conversational advertising therefore creates pressure for advertising copy to behave more like useful information and less like decoration.
That does not mean creativity becomes unimportant. It means creativity needs to work inside a different environment. A strong image, distinctive visual style, memorable framing, compelling offer, or unusual product proposition can still make an advertisement more effective. But the ad has to earn relevance before cleverness matters. Someone discussing how to furnish a tiny apartment probably benefits more from an advertisement saying "Modular sofas designed for rooms under 20 square meters" than one declaring "Live Beautifully."
OpenAI is also expanding visual formats. In October 2026, it announced testing of a new multi-image visual ad format during image generation, designed to show products, inspiration, usage, or experiences related to what someone is creating. The first tests are beginning in the United States with selected advertisers, and the ads remain labeled and separate from the generated image itself. This suggests that ChatGPT Ads will not remain a single card beneath a text response but may gradually become a family of formats adapted to different forms of AI interaction.
Sponsored Agents Could Be the Bigger Long-Term Shift
Another experimental format points toward an even more radical version of advertising. OpenAI is testing Sponsored Agents, which allow someone to open a conversation with an AI representative of a business directly from an advertisement and ask questions about its products or services. The format is currently limited to selected advertisers in an alpha test and is not generally available through self-service campaigns. Even so, it gives us a glimpse of where conversational advertising could eventually go.
Traditional digital ads are mostly gateways. You see an advertisement and click somewhere else, usually a product page, landing page, ecommerce store, or lead form. A Sponsored Agent could make the advertisement itself interactive. Instead of clicking a hotel ad and searching through the website for whether rooms accommodate three adults, the user could potentially ask the sponsored agent directly. Instead of opening a software website and hunting for an integration list, the customer could ask whether the system works with their existing stack.
That could fundamentally change landing-page strategy. For decades, marketers have optimized pages to anticipate as many customer questions as possible because visitors arrive with different concerns and the page has to serve all of them. A conversational brand agent could respond dynamically to the individual question instead. The customer's path might become ChatGPT research, sponsored recommendation, conversation with the advertiser's agent, and transaction, with much less traditional browsing in between.
There are obvious risks. A sponsored agent that gives inaccurate pricing, exaggerates capabilities, invents product features, or misunderstands policy could damage trust quickly. Businesses would need stronger product information, governance, knowledge sources, escalation rules, and brand guidelines than many currently maintain. But if the format works, the distinction between advertising, sales assistance, customer service, and product discovery begins becoming much less clear.
ChatGPT Ads Are Already a Real Media Channel
It would be easy to treat all of this as speculative because ChatGPT advertising is young, but the buying infrastructure is already much more developed than it was at launch. Advertisers can use a self-service Ads Manager in eligible markets, run campaigns optimized for views, clicks, or conversions, set daily or campaign-total budgets, organize ads into themed ad groups, upload custom audiences, create product-feed campaigns, and measure conversions. OpenAI also supports bulk campaign uploads, Shopify connections, measurement partners, HubSpot workflows, and an Ads Manager plugin that lets marketers create, update, and analyze campaigns through natural-language interaction in ChatGPT.
The available buying models already resemble established digital platforms. A Views objective uses CPM pricing to maximize exposure. A Clicks objective uses CPC pricing to drive traffic. Conversion campaigns optimize toward supported conversion events and can currently use either click-based optimized CPC billing or impression-based optimized CPM billing when eligible, although advertisers are not charged directly per conversion. Daily budgets are averaged over a seven-day period and can spend above the nominal daily figure on individual days, while campaign-total budgets provide stricter control over total campaign spend.
That means marketers should stop discussing ChatGPT Ads purely as a future possibility. The channel is young, the reporting and optimization infrastructure are still developing, and some features remain beta or alpha products. But it is now possible for eligible businesses to create an account, upload creative, define targeting context, buy traffic or reach, track conversions, and optimize campaigns in a way that looks increasingly familiar to anyone who has managed paid digital advertising elsewhere.
How to Advertise on ChatGPT
The practical setup is relatively straightforward, but the strategic preparation matters more than the number of screens involved. The mistake would be copying a Google Ads campaign into ChatGPT, replacing keywords with a few vague context hints, uploading the same banners, and expecting the platform to perform identically. ChatGPT's advantage is contextual intent, which means campaign structure should begin with customer situations rather than only product categories. Before opening Ads Manager, decide what customer problem each campaign is supposed to intercept, what outcome you want, and what information makes your product useful in that situation.
Step 1: Create and Verify Your Ads Manager Account
Campaign creation currently happens through OpenAI Ads Manager Beta. You can sign in with an existing OpenAI account or create one, then establish the advertiser account, add the brand identity and logo, configure billing, complete required verification, and invite team members who need access. During onboarding, advertisers can either enter a website URL and allow Ads Manager to help draft an initial advertisement or skip that step and enter the campaign environment directly. Ads submitted during onboarding can begin serving after they pass review and the account, billing, campaign status, budget, and scheduling requirements are ready.
Self-service availability depends on where the legal advertising entity is based. As of October 2026, the availability list includes Qatar, the UAE, Saudi Arabia, Bahrain, Kuwait, Oman, Lebanon, Jordan, Egypt, Morocco, much of Europe, the United States, Canada, Australia, India, Japan, South Korea, several Southeast Asian markets, and many others. Larger advertisers with complex requirements can also work through OpenAI's Ads Solutions team or approved agency and technology partners. Because availability is evolving quickly, marketers launching in several markets should verify the current country list rather than assume that user access to ChatGPT automatically means advertiser access exists there.
Step 2: Decide What You Want the Campaign to Accomplish
Ads Manager currently gives advertisers three principal objective choices: Views, Clicks, and Conversions. Views is the awareness option and bills on a CPM basis. Clicks is intended for traffic generation and bills for valid clicks. Conversion optimization is designed for advertisers with measurement configured and optimizes toward a selected supported conversion event, with eligible campaigns choosing either optimized CPC or optimized CPM billing.
Do not choose the objective simply because one sounds more sophisticated. A new advertiser testing whether ChatGPT can generate qualified traffic may learn more initially from a tightly defined Clicks campaign than from immediately asking a young optimization system to maximize conversions on limited data. A large ecommerce advertiser with reliable transaction tracking may reasonably move directly toward conversion optimization. A new consumer brand entering a category might care more about visibility among relevant conversations than immediate sales.
The business objective should determine the media objective, not the other way around. If the company needs qualified demo requests, website visits are only an intermediate metric. If the product is inexpensive and purchased quickly, direct conversion optimization may make much more sense. If the brand sells something with a six-month enterprise sales cycle, measuring ChatGPT solely on immediate website purchases would misunderstand how the channel contributes to the decision.
Step 3: Structure Campaigns Around Customer Problems
ChatGPT campaigns follow a familiar hierarchy of campaign, ad group, and ad. The campaign holds the objective, budget, schedule, geography, and broad targeting rules. Ad groups organize related advertisements around a common theme, use case, product, service, or intent area. The individual ad contains the brand identity, title, description, image, and destination URL.
The interesting part is how you define those ad groups. Instead of creating a generic "Accounting Software" ad group, you might separate "Freelancers needing invoicing," "Small businesses replacing spreadsheets," "Companies operating in multiple currencies," and "Teams needing expense management." The product might be identical in every case, but the context that makes it relevant changes. That gives you a much more useful foundation for both context hints and creative.
This resembles persona development, but it is more concrete. A useful ChatGPT ad group should correspond to a recognizable problem someone might actually describe during a conversation. "Young professionals" is a demographic. "Professionals trying to furnish their first small apartment on a limited budget" is a situation. The second gives an advertising system much more information about when an offer becomes helpful.
Step 4: Write Context Hints Like a Strategist, Not a Keyword Tool
Context hints are one of the defining features of ChatGPT Ads. They are added at ad-group level and provide additional information about the product, customer, and circumstances in which an advertisement may be useful. OpenAI suggests thinking in terms of what, who, and when: what your product or service does, who it suits, and what situation creates relevance.
Suppose you sell premium noise-canceling headphones. Weak hints might be "headphones," "audio," and "electronics" because they tell the system almost nothing beyond the product category. Better hints would describe people comparing headphones for frequent air travel, remote workers needing to block office noise, users looking for long battery life, or buyers comparing premium headphones below a certain budget. Those hints correspond to real decisions.
Avoid turning context hints into enormous disguised keyword lists. The purpose is not to predict every possible phrase someone could type but to teach the system about the conditions that make the offer relevant. If your product is particularly suitable for one situation, say so. If it is available only in certain locations, price ranges, customer types, or circumstances, context hints can add information that may not be immediately obvious from the advertisement.
This is also where marketing teams should work closely with sales and customer service. The best context hints may come from the questions customers actually ask before buying. What problem prompted them to contact the company? What constraints do they mention? What alternatives are they considering? What objections repeatedly appear? Those are conversational-intent signals hiding inside your existing business.
Step 5: Write Ads for Usefulness Rather Than Hype
Each standard ChatGPT advertisement includes a title, description, landing page, image, and the advertiser's identity. For bulk uploads, OpenAI currently recommends titles of roughly 16 to 24 characters with a maximum of 50, and descriptions around 32 to 48 characters with a maximum of 100. Images should be square JPG or PNG files, publicly accessible, and no larger than 1200 by 1200 pixels. Those technical constraints are easy; creating enough meaningful variation is harder.
OpenAI recommends building multiple distinct ad variants for each offering so the system has enough creative coverage to match different situations. That does not mean changing "Save Time With Acme" to "Acme Helps You Save Time" and calling it a second idea. Each variation should introduce a different benefit, use case, customer problem, feature, or reason to choose the product. The more genuinely different the variations, the more opportunities the system has to match a useful message to the right context.
For a hotel, one advertisement might emphasize family rooms, another the walking distance to major attractions, another free airport transfers, another late check-in, and another business facilities. For project-management software, one might emphasize agency collaboration, another client approvals, another automated reporting, and another migration from spreadsheets. The system can then choose among messages rather than merely deciding whether to show the company at all.
Step 6: Use a Landing Page That Finishes the Conversation
A common digital advertising mistake is sending every advertisement to the homepage because the homepage feels safe. ChatGPT Ads work better when the destination directly continues the need expressed in the advertisement. OpenAI recommends using specific product, collection, or content pages rather than defaulting to generic homepages and encourages marketers to add tracking parameters directly to destination URLs.
If your ad promises a comparison of three software plans, the destination should not force someone to hunt through the site to find pricing. If the ad is about a specific hotel package, send them to that offer. If someone has spent ten minutes using ChatGPT to clarify exactly what they need and then clicks a highly relevant advertisement, the landing page should not reset the conversation by presenting generic corporate messaging.
Your technical team should also make sure OpenAI can actually crawl the destination. OAI-AdsBot must be permitted because OpenAI uses it to validate landing pages and may also use landing-page content to help determine relevance. OpenAI recommends also allowing OAI-SearchBot, particularly where product feeds and image URLs are involved. Robots.txt rules, Cloudflare or other bot protection, CAPTCHAs, authentication systems, rate limiting, or geographic restrictions can inadvertently block these crawlers and prevent ads from being approved or processed correctly.
Step 7: Set Geography, Budget, and Bids Deliberately
Campaign-level targeting currently allows marketers to choose countries, while the buying system supports daily or campaign-total budgets. Daily budgets are averages calculated over a seven-day period rather than rigid same-day limits, which means spending can exceed the selected daily number on individual days while remaining constrained across the seven-day period. Campaign-total budgets are more appropriate when there is a fixed amount available for an activation or test.
Bid strategy depends on the objective and available campaign controls. Reach-oriented campaigns use CPM logic, click campaigns use CPC logic, and conversion campaigns use the applicable optimized buying model. For bulk campaign creation, the current schema supports maximum CPM bids for reach campaigns and maximum CPC bids for click campaigns. ChatGPT Ads is still a relatively young marketplace, so advertisers should expect auction dynamics and benchmarks to evolve considerably as both advertiser demand and available inventory increase.
This is a good reason to avoid importing Google Ads benchmarks directly. A $3 click on ChatGPT does not necessarily have the same value as a $3 Google Search click because the context, customer stage, competition, and intent structure are different. Establish your own baseline for qualified traffic, conversion rate, assisted conversions, lead quality, and eventual revenue. A new advertising channel deserves to be evaluated on what it contributes, not on whether its CPC resembles a platform built around a different consumer behavior.
Step 8: Install Conversion Measurement Before You Scale
Ads Manager reports impressions, clicks, spend, CTR, average CPC, average CPM, and conversions when measurement is configured. Conversion measurement is intended to track actions occurring after someone interacts with an advertisement, including purchases, leads, registrations, and other supported events. Reporting can separate eligible click-through and view-through conversions and allows advertisers to expose individual event types within reporting columns.
OpenAI supports browser Pixel and server-side CAPI approaches, along with partner and mobile measurement integrations. As with every advertising platform, simply seeing that the pixel loads is not enough. The actual conversion event needs to fire correctly after the relevant action, use the correct Pixel ID and event name, and carry appropriate data if the advertiser wants useful conversion reporting.
Add UTMs as well. OpenAI supports static tracking parameters on landing-page URLs, which means ChatGPT Ads traffic can be identified inside existing analytics systems and compared with other channels. OpenAI has also begun beta testing a direct GA4 connection that can support attribution comparisons and, for eligible advertisers, optimization, although this integration currently requires early access through an account manager.
Do not be surprised when attribution numbers differ between systems. Every platform has its own attribution methodology, windows, identity resolution, and handling of view-through conversions. The correct response is not deciding that one dashboard must be lying. Understand the methodologies, compare directional performance, and evaluate whether ChatGPT advertising contributes to commercially meaningful outcomes across the larger customer journey.
Step 9: Use First-Party Audiences Where They Make Strategic Sense
ChatGPT Ads also supports custom audiences created from customer or prospect lists using supported identifiers such as email addresses, phone numbers, hashed versions of those identifiers, and Google Advertising IDs. These audiences can be used for campaign-level inclusion or exclusion. Inclusion targeting currently requires at least 25,000 matched users, while smaller matched audiences can still be used for exclusions, and OpenAI recommends significantly larger lists for inclusion or bid-adjustment use cases.
The obvious use case is excluding existing customers from acquisition campaigns. A subscription company may not want to spend money advertising an introductory offer to someone already paying for the product. A retailer might exclude recent purchasers from the same acquisition campaign while targeting them differently later. A B2B company with a sufficiently large qualified-prospect database could use an inclusion audience to concentrate campaign eligibility around people already identified through other channels.
This is another place where ChatGPT advertising intersects with the broader return of CRM and first-party data. The contextual intelligence belongs to ChatGPT, but the proprietary customer knowledge belongs to the advertiser. Combining the two thoughtfully can be more valuable than trying to reconstruct everything through third-party audience targeting.
Step 10: Launch, Then Watch the Right Signals
Once the account, campaigns, ad groups, creative, and measurement are ready, the campaign is submitted for review. Ads can begin delivering after approval when billing, account verification, budgets, status, and scheduling allow it. Ads Manager then reports early delivery signals including impressions, clicks, CTR, average CPC, average CPM, spend, and conversions when configured. Impressions, clicks, and CTR currently refresh approximately every fifteen minutes, while spend data can lag by several hours.
Do not evaluate the campaign solely on CTR. A highly curiosity-driven advertisement may receive excellent clicks and terrible sales. Compare ad groups by customer context, evaluate which creative angle produces downstream behavior, inspect lead quality, and watch whether certain situations consistently generate stronger business outcomes than others. Conversational advertising gives marketers a new way to think about the reason behind the interaction, so reporting should eventually become more sophisticated than simply asking which headline received the highest click rate.
The early strategic question should be whether ChatGPT is finding valuable decision moments you were not reaching effectively elsewhere. Perhaps your Google Ads campaign captures customers searching directly for the category, while ChatGPT Ads reaches people earlier when they are still describing the problem. Perhaps the opposite happens and ChatGPT proves strongest at comparison-stage conversations immediately before purchase. The channel's role should emerge from the data rather than being decided in advance because it happens to be fashionable.
Step 11: Keep Creative Coverage Broad
OpenAI explicitly encourages advertisers to create a high volume of meaningfully diverse ads because the system can then identify more conversational situations in which one of them becomes relevant. This is different from making dozens of nearly identical banners. The objective is coverage of customer needs, not creative volume for its own sake.
Think of each advertisement as an answer to a possible customer concern. Why should someone choose this? Who is it particularly suitable for? What problem does it solve? What practical constraint does it address? What makes it different from another option?
If you sell travel insurance, one creative angle might focus on families, another adventure travel, another long trips, another medical coverage, and another last-minute policies. If you operate restaurants, one might emphasize family dining, another late hours, another dietary needs, another delivery, and another group reservations. Conversational intent is diverse, so your creative library should reflect the diversity of reasons someone might actually need you.
Step 12: Use the Ads Manager Plugin to Reduce Manual Work
ChatGPT advertising has an unusual advantage in that the platform itself can also become an interface for managing the campaigns. OpenAI introduced an Ads Manager plugin that allows eligible advertisers to create, update, and analyze campaigns through natural-language prompts. The plugin can compare campaign performance, analyze impressions, clicks, spend, CTR, CPC, CPM, and attributed conversions, examine trends, and break supported performance down by dimensions such as country, device, or time.
This may sound like a small convenience, but it points toward a broader transformation in paid-media management. Instead of navigating through reporting menus, a marketer can increasingly ask questions in ordinary language. "Which ad groups generated the strongest conversion rate in the UAE last month?" or "Compare CPC and lead volume between these campaigns." The interface begins shifting from operating software toward interrogating an advertising system.
That does not eliminate the need for expertise. In fact, it makes good questions more valuable. An inexperienced marketer can produce a perfectly accurate report answering an irrelevant question. A strong marketer understands which comparisons reveal a real business issue, which performance changes deserve investigation, and which optimization recommendation should be ignored because it conflicts with something the system cannot know.
Product Feeds Will Matter for Ecommerce
Retailers can also create campaigns using product feeds inside Ads Manager. Product-feed campaigns allow advertisers to provide structured product information that can help the system match relevant items to appropriate advertising opportunities. Shopify integration is also part of the growing commerce infrastructure around ChatGPT Ads.
This becomes particularly interesting because product discovery inside ChatGPT can be conversational rather than category-driven. Someone may not ask for a particular shoe brand but describe needing comfortable waterproof shoes for a winter trip with extensive walking. A structured product catalog gives the system more information from which to identify suitable options than a generic advertisement for the retailer.
Ecommerce marketers should therefore think about feed quality as creative and targeting infrastructure. Titles, product descriptions, availability, imagery, pricing, attributes, and categorization need to be accurate and useful. The same principle already exists in Google Shopping, but conversational shopping may make descriptive richness even more important because the system has more detailed criteria against which to evaluate products.
What You Should Not Do With ChatGPT Ads
Do not copy your Google Search account and pretend context hints are keywords. Do not write broad hints such as "people interested in marketing" and expect the system to discover your strategy. Do not create one generic ad and assume the platform will somehow personalize it into twenty useful messages. Do not send every click to the homepage, and do not scale before conversion tracking works.
Most importantly, do not try to game conversational targeting by stuffing context hints with situations only loosely related to the product. The incentive exists because every new advertising platform produces a generation of marketers looking for loopholes before the platform has fully matured. But relevance is particularly important inside ChatGPT because irrelevant advertising damages not only campaign performance but the user's experience of the conversation. The fastest way to make conversational advertising unpopular would be to recreate the worst habits of display advertising inside an interface people currently experience as useful.
Advertisers should also understand the restrictions around sensitive contexts and regulated categories rather than assuming every commercially valuable conversation can carry advertising. OpenAI's ad policies deliberately exclude various high-stakes and vulnerable situations. That reduces the available inventory in some categories, but it also protects the broader environment in which all advertisers operate. Trust is not simply an ethical consideration here; it is part of the value of the media product.
ChatGPT Ads and Google Ads Are Not the Same Fight
Marketers will inevitably compare ChatGPT Ads with Google Ads because both can reach people actively looking for information, products, and solutions. But I do not think ChatGPT simply becomes another search engine with sponsored results. The consumer behavior is different enough that the channels may occupy different roles even when they compete for some of the same advertising budgets. Google often begins with a query. ChatGPT often begins with a problem.
A search for "best project management software" presents clear commercial intent immediately. A ChatGPT conversation may begin with "My agency is getting chaotic and we're losing track of client approvals," continue into workflow advice, then move into whether software could solve the problem. One platform captures declared product demand. The other may witness demand being formed during the conversation.
That distinction could make ChatGPT particularly interesting for categories where customers need substantial education before purchasing. Financial software, B2B technology, travel, home improvement, consumer electronics, education, professional services, automotive products, and complex ecommerce categories all involve customers comparing trade-offs rather than simply finding the cheapest available item. Conversational advertising can potentially enter that consideration process at a moment traditional paid search cannot see.
ChatGPT Ads and Social Advertising Are Different Too
Meta and TikTok are extraordinarily powerful because they can create demand before somebody expresses it. A person does not need to be shopping for running shoes to encounter a compelling running-shoe advertisement between videos. The platform predicts who may respond based on behavior, interests, creative engagement, and enormous amounts of historical performance data. The advertiser essentially interrupts entertainment with something hopefully relevant enough to deserve attention.
ChatGPT is not an entertainment feed in the same sense. Most interactions begin because the person wants to accomplish something, answer something, understand something, create something, or decide something. That can create a very different advertising mindset. The ad is less about stopping a scroll and more about earning relevance within an active task.
Creative strategy should therefore differ too. Social advertising frequently benefits from hooks designed to seize attention immediately because users did not arrive looking for your message. ChatGPT advertising can assume the user is already engaged with the surrounding subject, so the job becomes demonstrating fit. The strongest creative may feel less like shouting across a crowded room and more like quietly saying, "What you're describing is exactly what we help with."
The Real Opportunity Is Advertising to a Problem
Marketing has always tried to reach people around problems, but platforms traditionally forced those problems into proxy signals. Search turned them into keywords. Social media turned them into audiences. Programmatic advertising turned them into behavioral segments. Retargeting turned them into browsing history.
Conversational interfaces can potentially understand the problem in much richer form. The customer may explain what they have tried already, why it failed, what matters most, what they cannot afford, which options they dislike, and what success looks like. That gives the advertising system something much closer to the customer's decision logic.
The implication is that marketers will need better customer knowledge than ever. If you cannot describe the circumstances in which your product is genuinely useful, conversational advertising will not magically discover a positioning strategy for you. The platform can connect context to an offer. It cannot make a mediocre offer strategically interesting.
This is why customer interviews, sales conversations, reviews, support tickets, search queries, Reddit discussions, CRM notes, and qualitative research become valuable advertising inputs. All of those sources contain the language people use when describing problems. ChatGPT Ads provides a way to turn understanding of those problems into media strategy.
The Landing Page May Eventually Become Less Important
For now, standard ChatGPT Ads still direct users to external landing pages, so all the familiar conversion-rate principles still apply. But Sponsored Agents hint at a future in which more of the evaluation process happens inside ChatGPT itself. If the advertiser can answer questions, compare products, explain policies, recommend configurations, and perhaps eventually facilitate transactions conversationally, the website may become less central to certain journeys.
That does not mean websites disappear. They remain authoritative sources, destinations, transaction environments, and places where businesses control the complete brand experience. But the assumption that every marketing interaction must ultimately push the customer toward navigating a website could weaken.
Marketers should therefore start thinking about their information architecture beyond pages. Is product information structured clearly enough for AI systems to understand? Are prices current? Are terms, availability, specifications, service areas, compatibility, policies, and customer questions documented accurately? In an agentic environment, information quality becomes part of customer experience.
Measurement Will Be the Hard Part
The biggest challenge may eventually be proving what conversational advertising actually contributed. Someone could spend twenty minutes discussing a purchase with ChatGPT, see an advertisement, never click it, remember the brand, search for it on Google the following day, visit a physical store, and purchase a week later. Conventional click attribution captures almost none of that influence.
OpenAI already reports both eligible click-through and view-through conversion activity when conversion measurement is enabled, and measurement integrations are expanding. GA4 integration, partner integrations, HubSpot connections, conversion APIs, and ecommerce data provide increasingly sophisticated ways to evaluate outcomes. Even so, no advertising platform can perfectly observe a customer's entire decision process.
Marketers should resist repeating the attribution mistakes of the social and search era by believing whichever dashboard gives its own platform the most credit. Use platform reporting for optimization, analytics for cross-channel behavior, CRM data for actual lead and customer quality, controlled experiments where possible, and broader business outcomes to judge whether the channel is incrementally valuable. A new platform should make measurement more thoughtful, not merely add another column to the attribution spreadsheet.
What This Means for Media Agencies
ChatGPT advertising also creates an interesting challenge for agencies because much of the traditional execution work can be simplified quickly. Campaigns can be created through guided workflows, bulk uploads, integrations, and increasingly natural-language commands. Performance analysis can also be accelerated through the Ads Manager plugin. Knowing exactly which interface button to click becomes less defensible as a major source of agency value.
Agency value therefore needs to move toward strategy, experimentation, creative coverage, customer research, measurement design, commercial understanding, and cross-channel integration. An agency should be able to tell a client which customer situations deserve separate ad groups, what context hints accurately describe real demand, how ChatGPT fits beside Google and Meta, what conversion events matter, and whether the resulting customers are commercially useful.
The technology lowers the technical barrier to launching advertising. It does not lower the strategic barrier to launching good advertising.
What This Means for Brands
Brands need to become better at articulating exactly why they are useful. That sounds obvious, but decades of vague marketing language suggest it is not. Websites are filled with phrases such as "innovative solutions," "world-class service," "transform your journey," and "unlock your potential." Those phrases survive partly because traditional advertising often rewards emotional impression and brand familiarity.
Conversational matching needs specificity. What do you actually do? Who needs it? Under what circumstances are you better than the alternatives? What constraints do you solve particularly well?
If your company cannot answer those questions clearly, the problem is not ChatGPT Ads. The problem is positioning.
The Beginning of Conversational Advertising
ChatGPT Ads are still early enough that anyone pretending to know exactly what the channel will look like five years from now is guessing. Formats will change, targeting capabilities will expand, auction dynamics will develop, measurement will improve, and Sponsored Agents or entirely new formats could eventually become more important than the standard ads running today. But the underlying behavioral shift is already visible.
Search advertising monetized the query. Social advertising monetized the feed. Conversational advertising may monetize the process of figuring something out.
That creates both enormous commercial potential and a much higher obligation to maintain trust. If the ads are genuinely relevant, clearly separated from answers, respectful of privacy, and useful to the decision being made, conversational advertising could feel considerably less intrusive than many existing formats. If marketers flood the system with vague targeting, irrelevant promotions, manipulative messages, and aggressive commercialization, users will learn to ignore the format just as they learned to ignore banners.
The advertising industry's history contains plenty of examples of valuable media environments being degraded because marketers optimized aggressively toward what was technically possible rather than what was good for the audience. ChatGPT advertising has an opportunity to begin differently because usefulness is already central to the surrounding product experience. The commercial message needs to earn its place beside that usefulness.
For marketers, that requires a subtle change in mindset. Do not begin by asking how many people you can target on ChatGPT. Ask what conversations reveal a genuine need for what you sell. Do not begin with a keyword list. Begin with customer situations. Do not write twenty slogans. Create twenty useful reasons somebody might care.
The marketers who succeed on ChatGPT probably will not be the ones who become best at manipulating a new advertising algorithm. They will be the ones who understand customers well enough to recognize the moment their product becomes relevant.
Because the most interesting thing about ChatGPT Ads is not that advertisements have finally arrived inside AI.
It is that advertising is beginning to understand the conversation around the purchase, not just the click that came after it.
