ChatGPT is becoming more than an AI assistant. For millions of users, it is increasingly a place where research, comparison and decision-making happen.
People use ChatGPT to ask questions such as:
Which project management software is suitable for a 300-person company with complex resource planning?
What are the best alternatives to our current CRM for a European B2B SaaS company?
Which cybersecurity vendors should we evaluate for a mid-sized enterprise?
This creates an advertising environment fundamentally different from traditional search or social media. Instead of reaching users based only on a keyword, demographic attribute or professional profile, ChatGPT Ads can reach people in the context of what they are currently trying to understand, solve or decide.
OpenAI describes ChatGPT Ads as a way for advertisers to reach users while they are exploring options, comparing alternatives and making decisions inside ChatGPT. Ads are displayed separately from ChatGPT’s answers and are clearly identified as sponsored content.
For marketers, this introduces a new category of paid acquisition: conversational advertising. And for B2B companies in particular, it could become an important new layer between traditional search advertising, paid social and AI-driven product discovery.
What Are ChatGPT Ads?
Why ChatGPT Ads Matter
How Do ChatGPT Ads Work?
From Keywords to Intent Clusters
How ChatGPT Ads Campaigns Are Structured
ChatGPT Ads Campaign Objectives
What Do ChatGPT Ads Cost?
Where Are ChatGPT Ads Available?
Who Sees ChatGPT Ads?
Do advertisers get access to ChatGPT conversations?
ChatGPT Ads Targeting Options
Custom Audiences
ChatGPT Ads Conversion Tracking
ChatGPT Ads Reporting and Measurement
ChatGPT Ads Manager
ChatGPT Ads Manager Plugin
What Makes a Good ChatGPT Ad?
Weak vs. strong B2B ChatGPT Ads
Benchmarks CPC and CTRs for ChatGPT Ads
A practical ChatGPT Ads campaign structure
Why ChatGPT Ads Are Interesting for B2B
ChatGPT Ads vs GEO
ChatGPT Ads vs Google Ads
ChatGPT Ads vs LinkedIn Ads
Which companies should test ChatGPT Ads?
When are ChatGPT ads less attractive?
How to Launch Your First ChatGPT Ads Campaign
Which Metrics should B2B companies track?
ChatGPT and account based Marketing
ChatGPT Ads and the B2B buyers journey
What should ChatGPT Ads be used for first in B2B?
The relationship between ChatGPT Ads, SEO and GEO
What are the current Limitations of ChatGPT Ads in 2026
ChatGPT Ads Agency for B2B SaaS, IT & Tech
The Future of ChatGPT Advertising
Frequently Asked Questions about ChatGPT Ads
ChatGPT Ads are paid advertisements displayed inside ChatGPT.
They can appear below a ChatGPT response when OpenAI’s advertising system determines that an advertiser may be relevant to the context of the conversation. A standard ChatGPT ad can include:
advertiser name
company favicon or logo
headline
description
landing-page link
image creative
Ads remain visually separate from the actual ChatGPT response. That distinction is important. Advertisers cannot pay to influence ChatGPT’s answers. OpenAI states that advertising runs separately from the system generating ChatGPT answers, advertisers cannot influence or rank themselves inside those answers, and ads are clearly labeled as sponsored placements. So there are now effectively two different ways a company might become visible around a ChatGPT conversation:
1. Organic visibility through GEO: Your company, product or content is referenced naturally because ChatGPT considers it useful to the answer.
2. Paid visibility through ChatGPT Ads: Your company appears in a separate sponsored placement associated with the conversation.
The two should not be confused.
Digital advertising has traditionally relied on three major types of signals.
Search intent: Google understands what somebody searches for. A query such as: project management software provides a relatively clear commercial signal. But it still contains limited context.
Audience intent: Platforms such as LinkedIn understand characteristics of the user.
For example:
job title
company
industry
seniority
company size
That makes LinkedIn especially powerful for B2B targeting.
Conversational intent
ChatGPT introduces something different. A user might explain:
“We have around 300 employees and run more than 80 concurrent projects. Our biggest problem is that project managers continuously compete for the same specialists. We need software that combines portfolio management with resource planning. What should we evaluate?”
That conversation contains substantially more context than a traditional keyword. It can reveal:
the user’s problem
requirements
constraints
company context
existing alternatives
stage of evaluation
possible purchase intent
This richer context is one of the fundamental reasons ChatGPT Ads are strategically interesting. OpenAI explicitly positions the platform around these moments of exploration, comparison and decision-making.
At a simplified level, ChatGPT Ads work through four layers.
1. The user has a conversation: Someone asks ChatGPT questions or explores a topic.That conversation creates contextual information about what the person is trying to accomplish.
2. OpenAI evaluates eligible ads: The advertising system evaluates ads that could be relevant.OpenAI says delivery may take into account signals including:
the context and intent of the current conversation
the advertiser’s landing page
ad title
ad description
advertiser-provided context hints
targeting selections
and, where ad personalization is available and enabled, selected signals from a user’s broader ChatGPT experience
3. Relevant advertisements can appear: Eligible sponsored placements can appear below the ChatGPT response.
4. The user can interact with the advertisement: Depending on the format, users can click through to the advertiser’s website or interact with the sponsored unit.
One of the biggest mistakes advertisers can make is treating ChatGPT Ads like another version of Google Search Ads. OpenAI does allow advertisers to provide context hints. But context hints are not exact-match keywords. They are descriptions that help OpenAI understand:
what your product offers
who it is useful for
what problem it solves
which conversations may be relevant
OpenAI specifically recommends describing real needs and situations rather than simply entering disconnected keywords.
For example:
Weak context hint: project management software
Better context hint: Enterprise project and resource management software for organizations coordinating multiple simultaneous projects and shared specialist resources.
Even stronger intent context: Relevant when project leaders or PMOs are evaluating software to identify resource bottlenecks, prioritize portfolios or coordinate specialist capacity across multiple projects.
The advertiser is therefore moving away from “Which keyword should we bid on?” toward “In which situations should our solution become relevant?” That is an important strategic shift.
For B2B advertisers, we recommend structuring ChatGPT campaigns around intent clusters rather than large keyword lists. An intent cluster represents a type of situation in which a potential customer might need your product. Consider a project portfolio management platform.
Problem intent: The user recognizes a problem but does not necessarily know the solution category yet. Examples: Our projects are constantly competing for the same resources. We cannot see whether we have enough capacity for the projects planned next quarter.
Solution intent: The user knows approximately what type of solution could help. What software can help us manage resources across multiple projects?
Evaluation intent: The user is actively evaluating solutions. Which PPM software is suitable for an enterprise with 500 employees?
Comparison intent: The user compares vendors or approaches. What are the differences between vendor A and vendor B?
Alternative intent: The user is considering replacing an existing solution. What are alternatives to [competitor]?
Purchase intent: The user is close to a commercial decision. Which enterprise project management vendors should we shortlist?
These different conversations should not necessarily receive the same ad. The closer your message matches the user’s underlying situation, the more useful the ad can become.
–> For a deeper look at campaign architecture, read our Guide to ChatGPT Ads for B2B and intent targeting.
OpenAI Ads Manager follows the familiar hierarchy:
Campaign → Ad Group → Ad
Campaign: The campaign defines the broader commercial goal. Campaign settings can currently include:
campaign name
objective
conversion event
budget
start and end dates
geography
platform targeting
custom audience inclusion or exclusion
Ad group:
Ad groups organize related themes, use cases or intents. This is also where context hints become particularly important.
For example:
Campaign: Enterprise Project Management Software
Ad Group 1: Resource Planning
Ad Group 2: Portfolio Prioritization
Ad Group 3: Project Risk
Ad Group 4: PPM Software Evaluation
Ads: Each ad contains the actual message and creative shown to eligible users. OpenAI recommends creating multiple distinct variations rather than repeating essentially the same message.
ChatGPT Ads have evolved quickly since the original pilot. Advertisers can currently work with three major buying or optimization models:
OpenAI currently describes these as CPM, CPC and conversion-optimized CPC objectives.
CPM: You pay based on impressions. This can make sense for:
category awareness
product launches
broad discovery
brand visibility
CPC: You pay for valid clicks. This is more directly comparable to traditional performance campaigns. It is suitable when the goal is:
website traffic
content downloads
product research
landing-page visits
Conversion-optimized CPC (cCPC): OpenAI also supports campaigns designed to optimize toward downstream actions after someone clicks the ad. Potential conversions include:
lead submission
registration
purchase
account creation
demo request
Conversion optimization requires sufficient measurement infrastructure.
The average Cost-Per-Click (CPC) for ChatGPT ads generally ranges from $3 to $6 for B2B campaigns, though niche or higher-competition targeting can push effective costs up to $13 per click. B2B advertisers find these early ChatGPT CPCs are typically one-third or less of comparable high-intent Google Search benchmarks (which often exceed $20+ for industrial/software terms).
OpenAI explicitly states that the platform is still early and does not yet provide generalized performance benchmarks across industries or campaign types. Costs depend on factors including:
objective
advertiser bids
competition
relevance
audience
market
campaign setup
creative
landing-page quality
available inventory
The platform supports CPC and CPM buying, with conversion optimization also available.
Minimum campaign budget: For EUR-denominated campaigns, OpenAI currently lists a minimum daily budget of €15.
That is a technical minimum, not necessarily a recommended testing budget. For B2B advertisers, a meaningful test should normally generate enough delivery across several:
intent clusters
creatives
ad groups
messaging angles
to produce interpretable results.
Advertisers can work with daily or campaign-level budgets. OpenAI explains that a daily budget should be understood as an average daily amount across a seven-day period, rather than an absolute same-day cap. Spend can therefore be higher or lower on individual days as the system attempts to pace delivery.
OpenAI has also introduced improved pacing for campaign-total budgets, designed to distribute spending more evenly over the scheduled campaign period. This was included in the latest advertiser update shared by OpenAI. For campaign managers, this means daily variance should not automatically be interpreted as poor budget control.
The platform began with a U.S. test in February 2026 and has expanded rapidly. On August 18, 2026, OpenAI announced expansion into 31 European markets.
On August 31, OpenAI updated the announcement to confirm that self-service Ads Manager access was available across those European markets. As of September 2026, OpenAI’s advertiser availability list includes self-service access in countries including: Germany, Austria, Switzerland, United Kingdom, France, Spain, Italy, Netherlands, Belgium, Sweden, Norway, Denmark, Poland ,Ireland, India, Japan, South Korea, Australia, Canada, Brazil, Mexico, United States as well as additional markets across Europe, the Middle East and North Africa.
ChatGPT Ads are now a practical acquisition channel for advertisers targeting the DACH region.
Ads currently appear for eligible users on the:
Free plan
Go plan
OpenAI states that ads are not shown to users on:
Plus
Pro
Business
Enterprise
Edu
and are not shown to accounts identified as belonging to users under 18. This is an important consideration for B2B advertisers. ChatGPT Ads do not mean that every corporate ChatGPT Enterprise user can suddenly be reached with advertising.
Your reachable audience consists primarily of users accessing ad-supported versions of ChatGPT. That makes testing and measurement especially important for niche B2B categories.
European advertisers should also understand that ChatGPT’s ad personalization framework differs by region. OpenAI states that personalized ads are not initially available in the European Economic Area or Switzerland.
That does not mean contextual advertising disappears. Ads can still be selected based on factors including:
the current conversation
language
broad location
campaign targeting
advertiser context hints
ad content
landing-page relevance
The distinction matters because conversational context should not be confused with traditional behavioral profiling.
No. This is one of the most important facts companies should understand before evaluating the channel. OpenAI states that advertisers do not receive:
ChatGPT conversations
chat history
memories
names
email addresses
precise location
IP addresses
sensitive personal information
Advertisers instead receive campaign-performance information such as views and clicks. So advertisers should not imagine ChatGPT Ads as a system where they can read what individual users are saying.
The conversation helps OpenAI determine relevance. It is not handed over to the advertiser.
ChatGPT Ads combine several targeting and relevance signals rather than relying on traditional keyword targeting alone. Current campaign and ad-group settings can include:
Geographic targeting
Platform targeting
Custom Audiences
Context hints
Campaign-level targeting settings
Ad and landing-page relevance signals
The exact capabilities can vary by market and may continue to evolve as OpenAI expands Ads Manager.
Geographic targeting: Advertisers can target supported countries and, depending on the market, more specific regions. For B2B companies, this makes it possible to separate campaigns by market, for example:
Germany
Austria
Switzerland
United Kingdom
France
United States
This is especially useful when messaging, offers and landing pages differ by region.
Platform targeting: ChatGPT Ads can be targeted across:
Web
iOS
Android
This allows advertisers to analyze whether performance differs by device or platform.
Context hints: Context hints are one of the most distinctive targeting elements in ChatGPT Ads. Instead of defining only keywords, advertisers describe situations in which their product or service may be relevant. For example:
The purpose is to help OpenAI understand the kinds of conversations in which the advertiser may be relevant.
Custom Audiences: Advertisers can also use first-party audience data through Custom Audiences. Depending on the campaign setup, Custom Audiences can be used for:
Audience inclusion
Audience exclusion
Bid adjustments
This creates opportunities for remarketing, customer exclusion and first-party data activation.
Targeting is not the same as keyword matching: This is one of the most important differences between ChatGPT Ads and Google Search Ads. With Google Ads, advertisers often target explicit search queries. With ChatGPT Ads, relevance can be based on a broader combination of:
Current conversational context
User intent
Context hints
Campaign targeting
Ad messaging
Landing-page relevance
Eligible audience signals
For B2B marketers, this means campaign planning should start with buyer situations and intent clusters, not with a long keyword list.
Recommended B2B targeting approach: For a first campaign, we recommend structuring targeting around three layers:
Market: Where is the target customer located?
Audience: Do you want to include, exclude or prioritize known first-party audiences?
Intent: In which problems, research situations or buying scenarios should your product become relevant?
This creates a stronger campaign structure than treating ChatGPT Ads as a traditional search campaign.
One of the most important recent additions for performance marketers is Custom Audiences. Advertisers can upload first-party audiences based on identifiers such as:
email address
phone number
hashed email
hashed phone
Google Advertising ID / GAID
Custom audiences can be used for three important purposes.
OpenAI currently supports bid multipliers between 0.1x and 10x at the ad-group level.
There is an important B2B limitation. OpenAI currently requires at least 25,000 matched users for audience inclusion or bid adjustment. For exclusions, smaller audiences below 25,000 matched users can be used. OpenAI recommends at least 100,000 users for inclusion targeting or bid adjustments. This matters for account-based marketing.
A highly focused ABM list with only several thousand contacts may therefore be useful for exclusion but may not qualify for direct inclusion targeting.
OpenAI has expanded Custom Audience management. Advertisers can now:
add audience members
remove members
replace audience members
mix supported identifier types
maintain audiences without rebuilding them
create audiences beyond five million members
use GAID
use audiences under 25K for exclusion
These updates make first-party audience activation increasingly viable.
OpenAI currently reports metrics including:
impressions
clicks
spend
CTR
average CPC
average CPM
conversions
Performance can be reviewed at:
campaign level
ad-group level
ad level
Ads Manager provides:
table reporting
charts
CSV exports
This makes it possible to compare intent groups and creative variants rather than treating ChatGPT Ads as an opaque black box.
View-through conversions: Another important development is view-through conversion measurement. For eligible accounts, OpenAI can report one-day view-through conversions. This means a user:
sees an eligible ad,
does not click it,
converts within one day,
and no qualifying click receives attribution.
These view-through conversions are currently reported separately from standard click-through conversions.
OpenAI has also announced that it plans to introduce a new conversion-optimization model incorporating view-through conversions into optimization. According to the latest platform update, this model will use impression-based billing while optimizing delivery toward a selected conversion goal. The functionality is still rolling out and should therefore be treated as upcoming rather than universally available today.
Product feeds and carousel ads: ChatGPT Ads are not limited to single static ad units. OpenAI also supports product-feed campaigns designed primarily for retail and catalog advertisers. These allow product catalogs to be uploaded and used to create ads at scale. OpenAI states that product-feed campaigns have been among the strongest-performing ads in the program to date.
For B2B SaaS companies, this format will often be less important than intent-driven standard campaigns. But it demonstrates that the ad ecosystem is already expanding beyond a single creative format.
New carousel reporting: OpenAI’s latest advertiser update also introduced more detailed reporting for multi-product carousel campaigns. Reporting can include:
carousel-card impressions
carousel-card clicks
product-level insights
A carousel card impression is counted when an individual product card becomes viewable. Importantly, these card-level impressions are separate from the billable ad-impression count. OpenAI states that full data became available from August 20, 2026, on a rolling 30-day basis.
Campaign management takes place through OpenAI Ads Manager Beta. Advertisers can currently use Ads Manager to:
create campaigns
create ad groups
create ads
bulk upload campaigns
manage billing
manage users and permissions
review reporting
access API keys
export data
manage audiences
The interface remains a beta product, so advertisers should expect frequent changes.
ChatGPT Ads Manager is now available inside ChatGPT: One of the most interesting recent changes is the ChatGPT Ads Manager plugin. The OpenAI-developed plugin enables advertisers to work with Ads Manager through ChatGPT itself. It can help with tasks such as:
finding advertising accounts
reviewing campaigns
analyzing performance
reviewing conversions
creating ads
uploading creatives
managing campaign entities
troubleshooting delivery
OpenAI’s update also describes the ability to use natural-language instructions to turn a website or campaign brief into ad concepts, create variants and review recommendations before applying changes. This is strategically important.
Advertising management itself is becoming conversational. Instead of manually navigating dozens of campaign settings, advertisers may increasingly be able to say: Analyze our last 30 days of ChatGPT Ads and identify the three ad groups with the weakest CTR.
or:
Create three new ad variants based on our landing page but emphasize resource planning instead of portfolio management.
That potentially changes how agencies and internal teams operate.
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OpenAI has introduced a ChatGPT Ads Manager plugin that allows advertisers to manage parts of their advertising workflow directly through ChatGPT. Instead of navigating only through the traditional Ads Manager interface, marketers can use natural-language instructions to work with campaigns, ads and performance data. The plugin can support tasks such as:
finding advertising accounts
reviewing campaigns
analyzing campaign performance
reviewing conversions
creating new ads
creating ad variants
uploading creatives
updating campaign elements
troubleshooting delivery issues
identifying performance problems
generating prioritized optimization recommendations
According to the latest OpenAI advertiser update you shared, the plugin can also turn a website or campaign brief into ready-to-launch ad concepts, create variants and recommend changes. Before changes are applied, the plugin previews the recommended actions and asks for confirmation.
Campaign management becomes conversational: The biggest change is not simply that Ads Manager becomes easier to access. It introduces a new way of managing advertising campaigns. Instead of manually reviewing dozens of tables and settings, a marketer could increasingly ask questions such as:
Which campaigns had the highest cost per conversion during the last 30 days?
Show me the ad groups with high spend but no conversions.
Create three new ad variants for our best-performing intent cluster.
Compare performance between our resource planning and portfolio management campaigns.
Recommend budget changes but do not apply them yet.
This makes campaign management itself more conversational.
Why this matters for B2B advertisers: For B2B advertisers, the plugin can reduce operational work around campaign management. However, it does not replace the strategic parts of advertising. The most important decisions still include:
Which ICP should we target?
Which buyer problems matter?
Which intent clusters should we test?
Which value proposition should we communicate?
Which landing page should match each intent?
Which conversions actually indicate qualified pipeline?
The easier campaign execution becomes, the more important these strategic decisions become.
What this means for agencies: For agencies, tools such as the ChatGPT Ads Manager plugin shift value away from manual campaign setup and toward:
campaign strategy
intent mapping
positioning
messaging
creative development
conversion strategy
experimentation
performance interpretation
cross-channel optimization
The difficult part is increasingly not: “How do we create the campaign?” but: “Which buyer situation should we target, what should we say, and what should happen after the click?”
That is where specialized B2B expertise becomes particularly valuable.
ChatGPT is a very different environment from an Instagram feed or a Google results page. Creative strategy should reflect that. OpenAI recommends:
clear messaging
specificity
practical benefits
explaining who the product is for
explaining when the product is useful
multiple distinct ad variations
In other words: relevance beats generic advertising language.
Weak:
Headline: Transform Your Projects Today
Description: Discover our innovative next-generation platform.
The problem is obvious.The message tells the system and user almost nothing.
Better:
Headline: Plan Resources Across Every Project
Description: Enterprise PPM for PMOs managing shared resources, portfolios and project capacity.
Now the system can better understand:
what the product does
who it serves
where it is relevant
And the user immediately understands why the advertisement might matter.
Do not create five advertisements that effectively say the same thing. Instead, create different value propositions. For a project management platform, you might test different messaging angles:
The underlying product remains the same. The conversational entry point changes.
OpenAI includes the landing page among the signals considered when evaluating advertisement relevance. That means the landing page is not simply the destination after the click. It can also contribute to the advertising system’s understanding of the offer.
For B2B advertisers, that means generic homepages are rarely ideal. Instead, align landing pages to the intent cluster. For example:
That creates a coherent chain:
conversation → ad → landing page → conversion
Suppose a company sells enterprise project-management software. A stronger campaign architecture might look like this:
Campaign 1: Resource & Capacity Management
Ad Group 1
Resource bottlenecks
Ad Group 2
Capacity planning
Ad Group 3
Skill management
Campaign 2: Portfolio & Multiproject Management
Ad Group 1
Project prioritization
Ad Group 2
Portfolio visibility
Ad Group 3
Multiproject planning
Campaign 3: Software Evaluation
Ad Group 1
PPM software comparison
Ad Group 2
Enterprise project-management alternatives
Ad Group 3
PMO software selection
This is much closer to conversational buying behavior than creating one generic campaign named:
“Project Management Software.”
B2B purchases are rarely impulsive. They often involve:
complex problems
multiple stakeholders
lengthy research
product comparisons
integrations
technical requirements
implementation questions
budget considerations
risk evaluation
These are precisely the types of topics that naturally generate longer conversations. For example, a buyer evaluating CRM software might not simply ask: CRM software
They might ask: We have a 60-person B2B sales organization across Germany, France and the UK. We need strong Salesforce integration but want something easier for sales managers to administer. Which CRM platforms should we evaluate? For an advertiser, this is qualitatively different from a two-word keyword.
This distinction will increasingly matter: GEO. Generative Engine Optimization aims to increase the likelihood that a company, product, data point or piece of content becomes useful to generative AI systems organically. The objective is: earn visibility inside the answer.
ChatGPT Ads
ChatGPT Ads are paid placements. The objective is: buy relevant visibility around the conversation. A mature AI-discovery strategy can therefore include both.
GEO
Build the authority and information architecture that helps AI systems understand and reference your company. ChatGPT Ads Create paid campaigns around high-value conversational intent.
The same concept already exists in search: SEO + Google Ads. The emerging equivalent could increasingly become: GEO + ChatGPT Ads
ChatGPT Ads are not a replacement for Google Ads. They address a different behavioral signal.
Google Ads: A user enters: PPM software. The advertiser receives a search-intent signal.
ChatGPT Ads: A user explains: Our PMO manages 70 simultaneous projects, but resource conflicts are making our planning unreliable. Which project portfolio management platforms should we consider? The environment potentially contains significantly more situational context. Google’s strength remains:
explicit searches
enormous search volume
mature attribution
established keyword economics
highly developed optimization systems
ChatGPT’s strength is potentially:
richer conversational context
problem-oriented research
comparison moments
exploratory buying journeys
complex decision support
The question therefore should not be: Should we stop Google Ads and run ChatGPT Ads? It should be: Which moments in the buyer journey are best suited to each channel? That is also the positioning already established on your commercial ChatGPT Ads agency page.
The difference is equally important for B2B marketing. LinkedIn excels at identifying who somebody is. For example:
That is extremely powerful B2B audience data. ChatGPT can potentially add another dimension: What is that person trying to accomplish right now? A simple way to think about the three channels is:
For sophisticated B2B demand generation, these channels can complement each other rather than compete.
The channel may be especially interesting for:
B2B SaaS companies: Particularly where users research specific problems, features or competing platforms. Examples:
project management
CRM
HR software
ERP
EPM
marketing technology
cybersecurity
analytics
AI software
IT and technology companies: Especially when buyers need to understand technical trade-offs before selecting a provider.
Enterprise software companies: Long sales cycles can create many research and comparison moments before a buyer speaks to sales.
Consulting firms: Potential clients frequently begin with the problem rather than the provider. For example: How do we migrate away from Oracle Hyperion? rather than: Hyperion consulting company.
Specialized B2B service providers: The more clearly a service maps to a recognizable business problem, the more interesting intent-based advertising can become.
Not every B2B company should immediately shift budget into the channel. Be cautious when:
your total addressable audience is extremely small
your buyer population is unlikely to use ad-supported ChatGPT plans
your product requires very narrow account-level targeting
you have no conversion tracking
your landing page cannot convert cold traffic
you cannot generate multiple messaging hypotheses
you expect mature-channel benchmarks immediately
ChatGPT Ads are still in beta. OpenAI itself emphasizes that features, inventory, optimization capabilities and reporting will continue to evolve. For most B2B companies, the correct approach in 2026 is therefore: structured experimentation, not blind budget migration.
Weak
Headline: Transform Your Projects Today
Description: Discover our innovative next-generation platform.
The problem is obvious. The message tells the system and user almost nothing.
Better
Headline: Plan Resources Across Every Project
Description:Enterprise PPM for PMOs managing shared resources, portfolios and project capacity.
Now the system can better understand:
what the product does
who it serves
where it is relevant
And the user immediately understands why the advertisement might matter.
For B2B ChatGPT Ads, there still aren’t official cross-industry benchmarks from OpenAI. OpenAI explicitly says the platform is too early to publish reliable advertiser-wide benchmarks, so any CPC/CTR numbers should be treated as directional early-market data, not hard standards. A reasonable benchmark range right now is:
One early dataset based on eight active advertiser accounts reported 0.8%–1.2% CTR for B2B SaaS, with CPCs around $4.50–$7.20 for category-research campaigns and $5.50–$9.00 for comparison queries. OpenAI itself recommends starting CPC campaigns with a maximum bid of about $3–$5 per click, although the actual CPC can be higher in competitive B2B contexts.
Your fictional Planora Ads Manager screenshot showing CTR around 0.9%–1.5% is therefore actually quite believable. I’d use something like this if you want realistic-looking example data:
Resource & Capacity Planning: 1.25–1.45% CTR
Portfolio Management: 0.95–1.20%
PPM Software Comparison: 1.15–1.50%
Enterprise PMO: 0.70–0.95%
Broad Project Management: 0.65–0.90%
For CPC, I’d make the fictional dashboard roughly:
$4.50–$5.50 = strong / efficient
$5.50–$7.00 = healthy B2B range
$7–$9 = plausible for high-intent comparison/evaluation traffic
$9+ = worth investigating unless lead quality is excellent
A good first test should follow a structured sequence.
Step 1: Define the business objective: Decide what the campaign should actually accomplish. Examples:
generate demo requests
acquire leads
generate qualified website traffic
promote a lead magnet
increase awareness in a new category
Step 2: Define your ICP: Especially for B2B, document:
industries
company size
business problems
buying committee
market
use cases
Step 3: Map conversational intent: Identify the questions a buyer might ask before discovering your company. Think about:
pain
solution
comparison
alternatives
evaluation
purchase
Step 4: Build ad groups around intent: Do not place unrelated use cases into a single ad group.
Step 5: Write several ad variants: Each should address a different reason why the product might matter.
Step 6: Align landing pages: Keep the message consistent between conversational intent, advertisement and destination.
Step 7: Implement conversion tracking: Use:
OpenAI Pixel
Conversions API where relevant
UTMs
GA4
CRM attribution if possible
Step 8: Launch: Check:
billing
account verification
campaign status
creative approval
dates
tracking
Step 9: Analyze intent performance: Evaluate not only which ad won, but which intent category performed.
Step 10: Scale what works: Shift more budget toward combinations of: intent + ad + landing page that produce qualified outcomes.
A sensible measurement framework includes several levels.
impressions
spend
CPM
clicks
CTR
CPC
conversions
conversion rate
cost per conversion
cost per lead
For B2B, this is where the real answer lies. Measure:
MQLs
SQLs
opportunities
pipeline generated
qualified pipeline per € spent
eventually revenue
A ChatGPT Ads campaign with a higher CPL could still outperform another channel if the resulting leads convert into pipeline at a higher rate.
Early-channel testing often creates a temptation to obsess over front-end metrics. But B2B companies should avoid optimizing solely for:
cheapest CPC
highest CTR
most clicks
A low-cost click from low commercial intent may be less valuable than an expensive click from somebody actively evaluating a solution. Ultimately, your question should be: Which conversational contexts produce commercially meaningful outcomes? That is the metric that matters.
Custom Audiences create interesting opportunities for B2B companies with sufficiently large databases. Examples include:
The platform does not currently replace LinkedIn or dedicated ABM platforms for narrow account targeting. LinkedIn remains stronger when you need to reach: CFOs at these 350 target accounts.
ChatGPT’s potential strength is different: reach people when the conversation indicates that the underlying problem is becoming relevant. This makes ChatGPT Ads potentially more useful as an intent layer within ABM, rather than as a standalone replacement for account targeting.
Consider a simplified enterprise buying journey.
Problem discovery: Why are our project deadlines becoming increasingly unreliable?
Problem definition: How can we improve project-resource planning?
Solution research: What software helps companies manage resources across multiple projects?
Evaluation: Which PPM platforms support skill-based resource planning?
Comparison: What are alternatives to [competitor]?
Selection: Which three vendors should we shortlist?
Potentially, ChatGPT can participate across every one of these stages. That creates opportunities for different advertising messages at different levels of commercial maturity.
Because ChatGPT conversations range from early education to vendor comparison, the platform potentially spans the entire funnel.
Problem education. Example: Why do projects constantly compete for the same specialists?
Possible content offer: Guide: 7 causes of resource conflicts in project organizations
Solution exploration. Example: How can software improve resource capacity planning?
Possible offer: Resource Planning Checklist
Vendor evaluation. Example: Which PPM systems should we shortlist?
Possible offer: Book a personalized demo
This is why a single “Request demo” ad for every conversational context is unlikely to be optimal.
For many companies, the best initial use case may not be direct demo generation. Lead magnets can create a lower-friction first conversion. Examples include:
buyer guides
comparison guides
checklists
assessments
migration guides
maturity models
benchmarks
templates
technical guides
The key is relevance. A lead magnet should solve the problem implied by the conversational intent.
The rise of ChatGPT Ads does not reduce the importance of organic search. It increases the number of discovery surfaces marketers need to understand. A modern acquisition strategy may increasingly involve:
Google SEO – Earn visibility in search results.
Google Ads – Buy visibility for explicit search demand.
GEO – Increase organic visibility inside AI answers.
ChatGPT Ads – Buy visibility around AI-driven research and decisions.
LinkedIn Ads – Reach known professional audiences.
These channels solve different problems.
A major shift in digital behavior is that users increasingly obtain substantial information without visiting multiple websites. A person might use ChatGPT to:
understand a market
create a shortlist
compare categories
identify important buying criteria
before clicking anywhere. For marketers, that changes the point at which paid visibility can matter. Advertising can potentially appear during the research process itself, not only after a user has formulated a traditional search query.
Google Ads performs exceptionally well when demand already exists in recognizable keyword form. But not every problem begins with a product-category search. Someone may not know that they need: project portfolio management software
They may simply know: We have too many projects and not enough visibility into resource capacity. Conversational environments can capture this earlier, less structured intent. That is one of the most interesting opportunities for B2B advertisers.
Despite the opportunity, advertisers should understand the platform’s current limitations.
The platform is still in beta: Features can change quickly.
Benchmarks are immature: There is currently no robust industry-wide benchmark for CTR, CPC, CPL or conversion rates.
User reach differs from Google and LinkedIn: Not every ChatGPT user sees ads.
B2B audience sizes can be restrictive: Custom Audience inclusion requires substantial matched audiences.
Attribution is still evolving: Conversion measurement has improved quickly, but OpenAI is still expanding attribution and optimization.
Geographic and personalization capabilities vary: Certain features differ by region.
All of this argues for experimentation rather than assumptions.
Launching a campaign is relatively easy. Designing a useful B2B test is harder. At GROWSaaS, we help B2B SaaS, IT and technology companies develop structured ChatGPT Ads campaigns around actual buyer intent. Our approach combines:
B2B Go-to-Market
ICP, buying committee, positioning and messaging.
Intent Mapping
Identifying the problems, comparisons and evaluation situations in which your solution should become relevant.
Campaign Strategy
Campaigns and ad groups structured around meaningful intent clusters.
Ad Creation
Headlines, descriptions, CTAs and differentiated creative variations.
Tracking
UTMs, GA4, GTM, conversion measurement and OpenAI measurement infrastructure depending on scope.
Conversion Optimization
Aligning landing pages and offers to the user’s underlying intent.
Optimization
Evaluating performance across intent, creative, spend and conversions.
Our dedicated ChatGPT Ads Agency for B2B SaaS, IT & Tech service offers structured campaign packages starting at €990.
ChatGPT Ads are still at the beginning of their development. But the direction is already visible. Over a short period, OpenAI has introduced or expanded:
self-service Ads Manager
CPC buying
conversion optimization
Pixel measurement
Conversions API
Custom Audiences
product feeds
carousel ads
granular reporting
view-through measurement
campaign-budget pacing
an Ads Manager plugin for ChatGPT
The platform is moving rapidly toward the feature set advertisers expect from established performance-marketing ecosystems.
The bigger change, however, may not be another bidding model or reporting column. It is the advertising signal itself. Search advertising grew around:
What did someone type into a search box?
Social advertising grew around:
Who is this person?
Conversational advertising can increasingly ask: What is this person trying to accomplish?
That could become one of the most important new layers of digital customer acquisition.
"Working with GROWSaaS, specifically with Arno and Patrick for the past years, supported us tremendously in increasing our brand awareness in the German market. Their expertise in finding the right local opportunities, together with their proactive approach, made them a great partner for boosting our marketing efforts in this region."
Monday.com
"Working with GrowSaaS is everything I look for in a good agency partner - flexible, informed and effective. Especially as a company where you have to try to achieve solid results quickly with just a few people in Germany, the agency is an indispensable partner and was quickly recognised as part of our marketing team. Arno and Patrick always respond to our requirements, draw up clear strategies and provide honest advice with a great deal of expertise - they don't just implement and bill, but deliver real added value, better than I have ever experienced in the SaaS environment."
Effectory
„The collaboration with Grow SaaS has been a complete success. Through targeted LinkedIn ad campaigns, we tripled the number of MQLs within a month – all while maintaining an excellent CPL. Particularly impressive: within a short time, the first MQLs were converted into SQLs and even real opportunities. GROWSaaS not only brings deep B2B marketing expertise to the table, but also stands out with structured processes and strategic foresight. A partnership that truly pays off.“
Can Do
“I can confidently say that GROWSaaS helped us to take our paid ads for both Google and LinkedIn to the next level. Patrick, Arno and their entire team have been the exact answer and help to what we were needing. I would absolutely recommend to anyone looking for a solid marketing agency, they can rely on at a resonable market price and get also good quality work and content out if it.ith our choice for GROWSaaS and would definitely recommend them. If you are looking for a marketing agency, GROWSaaS are the ones."
BanQu
"GROWSaaS has been a great partner in shaping our go-to-market approach for the DACH region. From the initial workshop to the final GTM document, their support was responsive, thoughtful, and well-aligned with our needs. The collaboration ran smoothly, with strong engagement across our German sales team and senior marketing leads. We’re now moving forward with a clear GTM plan in place and continuing to work closely with GROWSaaS as we grow in the region."
OneStream Software
"We are a small marketing and communications team. Thanks to the collaboration with Patrick and Arno, we skillfully bring the necessary power to the ground to captivate the Swiss market effectively for us. They can identify extremely well with our company and product, and due to their expertise and experience, they have become an essential part of our team. The collaboration with Patrick and Arno is not only personally valuable to us, but they also work very efficiently, punctually, and purposefully."
Peax
“We started our efforts in the DACH region without any help from a local agencies. That proofed a big mistake. Patrick and Arno helped us setting up the basics and together we drafted a go to market strategy for the DACH region. Both of them bring a lot of expertise in various fields and we were able to quickly launch a digital marketing strategy and drive traffic to our website, resulting in numerous leads. Besides their expertise, we especially like the way of working of Grow-Saas. Really structured and very good communication. We would definitely recommend them."
TimeChimp
ChatGPT Ads are paid sponsored placements that can appear inside ChatGPT. Ads are displayed separately from ChatGPT's generated answers and can include an advertiser name, headline, description, image and landing-page link.
Yes. Self-service ChatGPT Ads access is currently available in Germany through OpenAI Ads Manager. Austria and Switzerland are also supported.
OpenAI started expansion into 31 European markets on August 18, 2026, with self-service access becoming available across those markets since August 31, 2026.
OpenAI evaluates contextual and campaign signals to determine which ads may be relevant to a conversation. Signals can include conversational context, advertiser context hints, ad copy, landing-page content, campaign targeting and, where available and enabled, selected personalization signals.
Ads can appear below ChatGPT responses and are clearly separated from the generated answer.
No. OpenAI states that advertisements do not influence ChatGPT's answers and advertisers cannot pay to change or rank within generated responses.
No. OpenAI states that advertisers do not receive users' conversations, chat history, memories or personal details.
Ads may appear to eligible users on ChatGPT Free and Go plans. Plus, Pro, Business, Enterprise and Edu plans remain ad-free.
Personalization depends on user settings and region. OpenAI currently states that personalized ads are not initially available in the EEA or Switzerland. Context from the current conversation can still contribute to ad relevance.
Current capabilities can include geography, platform targeting, context hints and Custom Audiences. Supported functionality can vary by market and continues to evolve.
Context hints are descriptions advertisers provide at ad-group level to help OpenAI understand when a product might be useful. They can describe a use case, problem, audience or situation. Context hints are not exact-match keywords and do not guarantee delivery for a specific phrase.
Not in the same way as Google Search Ads. Context hints can include topics or relevant terminology, but OpenAI treats them as contextual guidance rather than exact-match keyword targeting.
OpenAI currently supports CPM, CPC and conversion-optimized CPC campaign objectives for reach, traffic and downstream conversions respectively.
OpenAI currently lists a €15 minimum daily campaign budget for EUR-denominated accounts. This is a platform minimum rather than a recommended testing budget.
There is no universal CPC or CPM benchmark yet. Costs depend on the campaign objective, auction dynamics, relevance, bids and available delivery. OpenAI says broad industry benchmarks are not yet established.
Yes. OpenAI supports conversion measurement through the OpenAI Pixel and Conversions API.
Yes, according to OpenAI, provided the tag-management setup loads the Pixel correctly and does not interfere with initialization or event calls.
Ads Manager currently provides metrics including impressions, clicks, spend, CTR, average CPC, average CPM and conversions where conversion measurement is configured.
Eligible accounts can currently see one-day view-through conversion reporting separately from click-through conversions. OpenAI has also announced future conversion optimization incorporating view-through conversions.
Yes. Custom Audiences can use supported identifiers including email, phone, hashed identifiers and GAID.
Inclusion targeting and audience bid adjustment currently require at least 25,000 matched users. Smaller audiences can be used for exclusion. OpenAI recommends at least 100,000 matched users for inclusion or bid adjustments.
Potentially, but the current audience-size requirements mean ChatGPT Ads do not replace highly granular LinkedIn or dedicated ABM targeting. They may be more useful as an additional intent-based layer within a broader ABM strategy.
They can be particularly interesting for B2B products with complex research and evaluation journeys because users can communicate detailed problems, requirements and constraints inside a conversation. Actual performance should still be validated through structured testing.
Not necessarily. Google captures explicit search demand, while ChatGPT can capture richer conversational context. Most companies should evaluate the channels as complementary rather than direct substitutes.
They solve different targeting problems. LinkedIn excels at professional audience targeting, while ChatGPT can provide richer contextual signals about what a user is trying to accomplish.
ChatGPT Ads are paid advertising placements. GEO aims to increase organic visibility inside generative AI answers. Paid ads do not influence organic ChatGPT answers.
Ads Manager is OpenAI's self-service platform for creating, managing and measuring ChatGPT advertising campaigns.
Yes. OpenAI currently offers a ChatGPT Ads Manager plugin that can access advertising accounts, campaigns, ads and performance data and support campaign-management workflows through ChatGPT.
Yes. Companies can work with an agency for campaign strategy, account setup, intent mapping, ad development, tracking and optimization. GROWSaaS offers dedicated ChatGPT Ads services for B2B SaaS, IT and technology companies.
ChatGPT Ads give companies a new way to reach potential customers – not only based on what they are searching for, but also on what they are trying to achieve.
We turn this into a structured test with clearly defined intents, messaging, creatives, tracking, and measurable results.
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