Beyond the Click: What ChatGPT Sponsored Agents Could Change in Paid Media

 

From Ad Exposure to Conversation | From Customer Intent to Consideration | From Engagement to Business Outcome

ChatGPT Ads has already introduced a different context for paid media: reaching people while they are exploring, comparing and making decisions through conversation.

Sponsored Agents add another layer to that journey.

After seeing an eligible ad, a user can choose to open a clearly labelled conversation with an AI representative sponsored by that business. They can ask follow-up questions about the product or service and, when ready, continue to the advertiser's website.

That creates an interesting paid media journey:

Ad Exposure → Sponsored Conversation → Product Exploration → Consideration → Website → Business Outcome

Sponsored Agents are currently being tested with selected advertisers in the United States. So this is not a hands-on European performance case study. My interest is in what this format could mean for paid media strategy, creative, measurement and optimization if it develops more broadly.

1. What Exactly Is a Sponsored Agent?

Imagine someone researching running shoes in ChatGPT.

They see a relevant sponsored ad for a particular model. Instead of immediately leaving ChatGPT, they can choose to continue with the advertiser's Sponsored Agent.

The conversation could develop around questions such as:

“Is this suitable for overpronation?”

→ “How does the sizing compare with my current shoes?”

→ “Would this work for 20–30 km of running each week?”

→ “Which model would suit me better?”

→ Visit the advertiser's website

The Sponsored Agent conversation is clearly identified as sponsored. It is also separate from ChatGPT's independent answers and separate from the original conversation the user was having.

From a paid media perspective, that separation is important. The Sponsored Agent is an advertiser experience entered from the ad, rather than the advertiser taking over the original ChatGPT conversation.

2. A New Layer in the Customer Journey

Consider the journey of a typical paid media click:

Ad → Website → Product Exploration → Consideration → Conversion

With Sponsored Agents, part of that exploration could potentially happen before the website visit:

Ad → Sponsored Agent → Questions → Product Exploration → Website → Conversion

That middle layer is what interests me.

Take a hypothetical furniture retailer advertising a dining table.

A potential customer might want to know:

Will a 180 cm table fit comfortably in my room?

Can six people sit around it?

How should the surface be maintained?

Does it come in a lighter finish?

Those questions represent consideration.

For paid media planning, I would therefore think about Sponsored Agents as another stage in the journey rather than simply another creative format.

3. From Click Intent to Conversational Intent

Clicks give us one signal:

The user chose to engage with the ad.

A conversation can potentially contain much richer expressions of intent.

Imagine a hypothetical electronics advertiser.

User A:
“Tell me more about this laptop.”

User B:
“Does this support two external 4K monitors, and is 16 GB RAM enough for Premiere Pro?”

Both users engaged with the advertising experience, but the nature of that engagement is very different.

This opens an important paid media question:

Which conversational interactions are meaningful indicators of consideration?

I would want to understand signals such as:

Sponsored Agent Starts → Follow-Up Interactions → Product Exploration → Website Visits → Conversion Events → Revenue

Exactly which conversational signals advertisers will ultimately receive for reporting and optimization will depend on how the product develops. That measurement boundary is important because private user conversations remain protected from advertisers.

4. Creative Strategy Could Change Too

A standard ad has limited space.

The headline, description and image need to create enough relevance and interest for someone to take the next step.

Sponsored Agents potentially give the advertising experience somewhere to continue.

For a hypothetical travel advertiser, the ad could introduce a proposition around a Mediterranean holiday.

The Sponsored Agent could then help the user explore:

Destination → Travel Dates → Hotel Type → Budget → Activities → Available Options

That changes how I would think about creative architecture.

The initial ad still needs a strong proposition. But it can also serve as the entrance to a deeper product or service experience.

This creates another optimization layer:

Which ad propositions generate clicks?

and potentially:

Which ad propositions generate meaningful sponsored conversations that eventually contribute to business outcomes?

Those are different questions.

5. The Website Visitor Could Arrive With More Context

Sponsored conversations could also affect what happens after the user leaves ChatGPT.

Take a hypothetical fashion retailer.

A user might discuss:

Occasion: September wedding
Budget: €300
Style: Smart-casual
Preference: Nothing too formal
Product: Outfit and shoes

If that conversation helps the user narrow the available options before visiting the retailer, the website visit occurs at a different point in the consideration journey.

For performance marketing, I would want to examine whether that changes:

Landing Page Engagement → Product Views → Add-to-Basket Rate → Conversion Rate → Average Order Value → Customer Acquisition Cost

I would also want to understand where the Sponsored Agent contributes value and where the website remains better suited to the task.

Product discovery, detailed comparison, inventory, checkout and transaction completion do not necessarily need to happen in the same environment.

6. Measurement Becomes the Critical Question

This is where I would spend considerable attention before scaling investment.

The ideal measurement framework would help me understand the complete journey:

Stage	What I would want to understand
Ad Exposure	Reach, impressions, relevance
Ad Engagement	Clicks and engagement
Sponsored Agent	Meaningful interaction signals made available to advertisers
Website Visit	Qualified traffic and landing behaviour
Consideration	Product views, key actions, add to basket
Conversion	Leads, purchases or subscriptions
Business Outcome	Revenue, CAC, customer quality and incremental value

 

ChatGPT Ads already has conversion measurement infrastructure through browser and server-side tracking. Sponsored Agents introduce another potential interaction layer between the ad and the advertiser's website.

For me, the important question will be how clearly that layer can eventually be connected to downstream business outcomes.

A high number of Sponsored Agent conversations would be interesting.

A high number of commercially valuable conversations that contribute to profitable customer acquisition would be much more meaningful.

7. Optimization Could Gain Another Signal

Suppose two hypothetical campaigns each generate 10,000 ad engagements.

Campaign A

10,000 engagements
→ 1,500 Sponsored Agent interactions
→ 600 website visits
→ 60 purchases

Campaign B

10,000 engagements
→ 3,000 Sponsored Agent interactions
→ 1,200 website visits
→ 150 purchases

These are deliberately hypothetical numbers.

The example illustrates the optimization question I would eventually want to answer:

Can the quality of conversational engagement help us understand and optimize downstream performance?

If the platform eventually provides suitable aggregated signals, advertisers could potentially evaluate more than impression and click behaviour.

The optimization chain could become:

Media → Ad → Conversation → Site Behaviour → Conversion → Business Value

That would make Sponsored Agents particularly interesting for products where customers naturally have several questions before making a decision.

8. Where I See the Strongest Paid Media Use Cases

I would initially look at categories with meaningful consideration journeys.

Business / Vertical	Potential Sponsored Agent Role
Fashion & eCommerce	Sizing, fit, occasion, product comparison
Consumer Electronics	Specifications, compatibility, use cases
Travel	Destination, accommodation, budget and itinerary questions
Home & Furniture	Dimensions, materials, suitability and care
Beauty	Product characteristics, routines and comparisons within appropriate advertising boundaries
Automotive	Features, configurations and product research
Subscription Services	Plans, features and suitability
Technology	Product capabilities, integrations and requirements

 

The common characteristic is a customer who benefits from additional information before taking the next step.

That is where conversational advertising becomes particularly interesting to me.

9. The Advertiser Workflow Is Becoming Conversational Too

There is another development happening on the opposite side of the advertising experience.

Advertisers can now use natural-language instructions through ChatGPT Work to work with Ads Manager.

That can support activities such as:

Website / Brief

↓

Campaign Creation

↓

Campaign Updates

↓

Performance Analysis

↓

Recommendations and Next Actions

Ads Manager is also adding AI assistance for creative development, including suggested copy and imagery based on the landing page and campaign objective. Advertisers can review and edit those suggestions before using them.

AI-powered text customization can go further by adapting existing headlines and descriptions to conversational context and translating copy into the user's preferred language when enabled.

So there are potentially two conversational layers developing around the same advertising ecosystem.

Consumer side

User → Ad → Sponsored Agent → Business

Advertiser side

Marketer → Natural-Language Instruction → Advertising Platform → Campaign

For paid media operations, that combination could become significant.

10. CRM and Commerce Integrations Add Another Layer

The connection with existing marketing systems is equally interesting.

CRM integration can bring advertising closer to:

Campaign → Lead → CRM → Follow-Up → Customer

Commerce integration can bring advertising closer to:

Product Catalog → Campaign → Product Discovery → Website → Purchase

For example, ChatGPT Ads can now connect with CRM workflows that support campaign creation, lead capture, follow-up and performance measurement.

Commerce integrations can connect advertising workflows more closely with merchant product data and campaign management.

For me, this matters because paid media rarely operates as an isolated platform.

Its value ultimately needs to connect with the systems that contain:

Products → Leads → Customers → Transactions → Revenue

11. What I Would Test First

If Sponsored Agents become broadly available, I would begin with a controlled test built around a product where customer questions are already an important part of the buying journey.

For example:

Hypothetical German Consumer Electronics Retailer

Product: Premium laptop range

Step 1: Identify common pre-purchase considerations.

Performance → Battery → Compatibility → Display → Portability → Price

Step 2: Build advertising around commercially relevant contexts.

Step 3: Use the Sponsored Agent to help users explore those considerations.

Step 4: Connect website conversion measurement.

Step 5: Evaluate the complete journey.

Ad Exposure → Sponsored Conversation → Website → Product Behaviour → Purchase → Revenue

I would keep the initial investment controlled until enough data exists to understand the quality of the resulting traffic and customers.

12. The Questions I Would Want Answered

Sponsored Agents are still in limited testing, so several questions matter before making broader performance conclusions.

Measurement: Which Sponsored Agent interactions will advertisers be able to measure?

Optimization: Can meaningful conversational engagement eventually become an optimization signal?

Reporting: How much aggregated insight will advertisers receive about sponsored interactions while preserving user privacy?

Creative: How much control will advertisers have over the knowledge, tone and behaviour of their Sponsored Agent?

Product Data: How dynamically can product availability, attributes and other relevant information be incorporated?

Attribution: How will Sponsored Agent engagement appear within the wider conversion journey?

Incrementality: Are Sponsored Agents creating additional conversions, assisting existing demand, or doing both?

Scale: How does performance behave as advertiser adoption and available inventory increase?

Those questions require testing and evidence.

13. What This Could Mean for Europe

There is an important geographic distinction today.

ChatGPT Ads is already available across European markets, while Sponsored Agents are currently being tested with selected advertisers in the United States.

So I would not treat Sponsored Agents as an existing European campaign capability.

But their development is highly relevant to European paid media because it gives us an early view of where the ChatGPT advertising experience could evolve.

If the format eventually expands into Europe, the regional environment will also matter.

Privacy requirements, personalization capabilities, measurement, audience availability and market-specific product features will all influence how I would build the strategy.

The U.S. test gives us the concept.

A future European implementation would need to be evaluated on its own capabilities and constraints.

14. My Paid Media View

Sponsored Agents introduce an interesting additional layer between advertising exposure and the advertiser's website.

For products with meaningful consideration journeys, that layer could allow consumers to explore questions that traditionally happen across landing pages, product pages, comparison tools, FAQs, reviews or sales interactions.

From a paid media perspective, I would evaluate the opportunity through four connected areas:

Media Strategy

Where does the sponsored conversation belong in the customer journey?

Creative Strategy

Which proposition should start the conversation, and what should the Sponsored Agent help the customer explore?

Measurement

Can interaction with the Sponsored Agent be connected meaningfully to downstream customer behaviour and business outcomes?

Optimization

Can those signals eventually help advertisers allocate budget toward conversations that create genuine commercial value?

And alongside that consumer journey, the advertiser workflow itself is becoming increasingly conversational through AI-assisted campaign creation, creative development, analysis and integrations with CRM and commerce systems.

That creates a broader paid media model worth watching:

Customer Intent → Ad Exposure → Sponsored Conversation → Consideration → Website → Conversion → Business Outcome

with an advertiser workflow increasingly moving toward:

Strategy → Prompt → Campaign → Measurement → Analysis → Optimization

For me, the most interesting part of Sponsored Agents is what happens between the impression and the business outcome.

That is where the next set of paid media questions begins.

 

Building the Right eCommerce Media Mix -How AOV and Purchase Frequency Can Shape Media Planning Decisions

 

An eCommerce media plan often starts with channels.

How much should go into Google Ads? What role should paid social play? Should YouTube be part of the mix? Does Connected TV (CTV) make sense? Where can programmatic advertising add value? How much should we invest in remarketing?

But before deciding the channels, there is a more fundamental question:

What kind of purchase are we actually trying to generate?

Two useful signals can help answer that:

Average Order Value (AOV) and purchase frequency.

Neither determines the media plan on its own. But together, they provide a useful lens for understanding the customer journey, acquisition economics, repeat-purchase opportunity and the jobs different media channels may need to perform.

That makes them useful inputs for building the media mix.

1. The Same Media Mix Does Not Fit Every eCommerce Business

Consider four different purchase situations.

1.      Someone buying a mattress may spend several hundred euros but might not need another one for years.

2.      A meal-kit customer can generate a meaningful basket and potentially order repeatedly.

3.      Someone buying a relatively inexpensive sports accessory may make a smaller transaction without creating an obvious near-term repeat purchase.

4.      A fashion customer may have a smaller basket but return several times during the year.

All four are eCommerce customers.

But commercially, they behave very differently.

And if the economics and customer journeys are different, the media plan should be different too.

2. A Simple Planning Lens

Before allocating budget, I would start with two questions:

How much is an average order worth?

How frequently does the customer realistically purchase again?

Put those together and four broad planning profiles emerge:

	Lower Purchase Frequency	Higher Purchase Frequency
Higher AOV	Considered Purchase	High-Value Repeat
Lower AOV	Acquisition-Constrained	High-Velocity Commerce

This isn't designed to permanently classify an entire company.

A retailer can have categories, products or customer segments with very different economics.

The framework is simply a planning lens:

What does the commercial model tell us about the job media needs to perform?

3. Considered Purchase

Higher AOV + Lower Purchase Frequency

Think about Emma and the mattress category.

The purchase is relatively valuable, but the natural replacement cycle is long. The customer may research alternatives, compare products, read reviews and return several times before buying.

The media challenge therefore extends beyond capturing today's demand.

Media may need to:

→ Generate awareness and consideration
→ Explain product differentiation
→ Build confidence during a longer decision journey
→ Capture high-intent category demand
→ Re-engage genuine prospects
→ Convert when purchase intent becomes stronger

Media Mix Implications

Search & Shopping
Strong demand-capture role when consumers actively research products, brands, prices and alternatives.

Paid Social
Useful for discovery, product storytelling, social proof, offers and bringing the product into the consideration set.

YouTube / Online Video
Stronger role where demonstration, differentiation and education can influence consideration.

Connected TV (CTV)
Potentially valuable for broader reach and demand creation when scale, budget and market maturity justify it.

Programmatic Advertising
Can support reach, contextual activation, audience strategies and controlled re-engagement.

Remarketing
Important, but longer consideration should not become an excuse for excessive frequency.

Planning priority: Demand Creation + Consideration + Demand Capture

4. High-Value Repeat

Higher AOV + Higher Purchase Frequency

Now consider a business such as HelloFresh.

Here the commercial equation changes.

The first order matters, but it may represent only part of the customer's potential value if that customer continues ordering.

The media question therefore becomes:

How efficiently can we acquire customers who have the potential to become valuable beyond their first transaction?

Media Mix Implications

Search
Captures existing category demand and consumers actively comparing solutions.

Paid Social
Can play a major acquisition role through proposition-led, promotional and creative-led prospecting.

YouTube / Online Video
Useful for explaining the proposition and building familiarity before acquisition.

Affiliate / Partnership Channels
Potential acquisition role where economics and customer quality can be measured effectively.

Remarketing
Focused on converting meaningful consideration rather than simply following every site visitor.

Retention & Reactivation
Become increasingly important because the economics extend beyond the first transaction.

Here, the first-order Return on Ad Spend (ROAS) doesn't necessarily tell the complete story.

But projected Customer Lifetime Value (LTV) should not become justification for inefficient acquisition either. Repeat behaviour needs to be demonstrated through real customer cohorts.

Planning priority: Acquisition + Customer Quality + Retention

5. Acquisition-Constrained

Lower AOV + Lower Purchase Frequency

Consider selected lower-ticket, occasional-purchase categories within a retailer such as Decathlon.

The transaction value may be relatively small while near-term repeat purchasing is limited.

That creates a difficult acquisition equation.

If there isn't much revenue in the initial basket and limited repeat value afterwards, there is less room to absorb an expensive Customer Acquisition Cost (CAC).

Media Mix Implications

Search & Shopping
Strong role where identifiable purchase intent already exists.

Paid Social
Can support prospecting, but acquisition economics need particularly close attention.

Retail Media
Potentially valuable where products are distributed through retail environments with strong shopping intent and useful first-party commerce signals.

Remarketing
Needs discipline. Repeatedly paying to chase a relatively small transaction can quickly damage the economics.

Upper-Funnel Media
Still relevant for brands with sufficient scale, but its role and incremental contribution need to be understood clearly.

This profile also creates a question that media optimisation alone cannot answer:

Can we improve the economics of the transaction?

Bundles, complementary products, cross-sell, merchandising and shipping thresholds can increase basket value.

Sometimes improving media efficiency starts outside the advertising platform.

Planning priority: Intent Capture + CAC Discipline + Basket Economics

6. High-Velocity Commerce

Lower AOV + Higher Purchase Frequency

Now consider a fashion commerce model such as Zalando.

Individual baskets may be smaller than major considered purchases, but customers have substantially more opportunities to return and purchase again.

That changes the planning question.

It isn't only:

How efficiently can we generate today's transaction?

It is also:

How efficiently can we acquire customers who continue generating value?

Media Mix Implications

Search & Shopping
Continuous demand capture across categories, products and brands.

Paid Social
Strong role across discovery, product-led creative, prospecting and new-customer acquisition.

YouTube / Online Video
Can create broader demand around categories, collections, seasons and the brand itself.

Programmatic Advertising
Can support reach, prospecting, contextual activation and controlled re-engagement at sufficient scale.

Dynamic Product Advertising
Particularly relevant when the business has a large and frequently changing product catalogue.

Retention & Reactivation
Become strategically important because repeat purchasing contributes to customer economics.

The media plan therefore needs to connect acquisition and retention rather than treating every transaction as an isolated event.

Planning priority: Scalable Acquisition + Repeat Purchase + Reactivation

7. The Media Planning Matrix

Putting the four profiles together makes the differences clearer.

Media Planning Area	Considered Purchase	High-Value Repeat	Acquisition-Constrained	High-Velocity Commerce
Illustrative example	Emma	HelloFresh	Selected Decathlon categories	Zalando
Demand creation	High	High	Selective	High
Demand capture	Very High	High	Very High	Very High
Search & Shopping	High	High	High	High
Paid social prospecting	Medium-High	High	Selective	High
Video	High	Medium-High	Selective	Medium-High
CTV	Scale dependent	Scale dependent	Selective	Scale dependent
Programmatic advertising	Consideration & reach	Supporting role	Selective	Reach & re-engagement
Remarketing	Longer journey	Important	Controlled	Important
Retention / Reactivation	Lower immediate role	Very High	Lower	Very High
CAC flexibility	Higher potential	Repeat-value dependent	Restricted	Repeat-value dependent
Measurement horizon	Longer	Cohort-oriented	Tighter	Transaction + customer value

This is not a channel budget template.

It would be misleading to suggest that every considered-purchase business should spend a fixed percentage on video or that every high-frequency retailer should allocate the same percentage to paid social.

Instead, the framework helps determine something that comes before budget allocation:

What job should each channel perform?

8. From Commerce Economics to Media Plan

A more useful planning sequence is:

Business Economics → Customer Journey → Media Objective → Channel Role → Budget Priority → Measurement

Consider how differently this works across the four profiles.

For a considered purchase, part of the budget may need to create demand before Search eventually captures it.

For a repeat-driven business, acquisition economics can increasingly be evaluated through customer cohorts rather than only transaction one.

For a low-value, low-frequency purchase, the media plan may need to stay much closer to identifiable demand and strict acquisition economics.

For high-velocity commerce, acquisition and retention increasingly become connected parts of the same growth model.

The media mix becomes an output of the commercial strategy, rather than the starting point.

9. Where Should the Next Euro Go?

Purchase frequency also changes one of the biggest eCommerce budget questions:

Acquisition or retention?

For a naturally low-frequency category, repeatedly advertising to existing customers may produce limited incremental value simply because they aren't ready to purchase again.

For a higher-frequency business, ignoring existing customers can mean continually paying to acquire replacements for customers who could potentially have been retained or reactivated.

That influences:

→ New-customer acquisition budgets
→ Existing-customer exclusions
→ CRM audience activation
→ Cross-sell
→ Replenishment
→ Reactivation windows
→ Promotional strategy

The objective isn't to choose acquisition or retention.

It is to find the balance that reflects the economics and natural purchase rhythm of the business.

10. Measurement Should Follow the Business Model

The measurement framework should change too.

A €700 considered purchase and a €60 repeatable purchase shouldn't automatically be evaluated through identical expectations.

Depending on the model, useful business and media metrics can include:

→ Return on Ad Spend (ROAS)
→ Customer Acquisition Cost (CAC)
→ New Customer CAC
→ Contribution margin
→ Repeat purchase rate
→ Customer payback period
→ Customer Lifetime Value (LTV)
→ Cohort revenue
→ Incremental revenue

The objective isn't to create a longer KPI dashboard.

It is to measure media against how the business actually creates economic value.

11. What AOV and Purchase Frequency Cannot Tell Us

AOV and purchase frequency are useful planning inputs, but they are not the entire media strategy.

Two businesses occupying similar positions in the framework could still require very different plans because of:

→ Contribution margin
→ Existing brand demand
→ Competitive intensity
→ Market maturity
→ Category behaviour
→ Seasonality
→ Subscription versus transactional models
→ Customer acquisition costs
→ Geographic expansion
→ Promotional dependency
→ Available media budget

The framework therefore shouldn't answer:

“What should our media plan be?”

It should help us ask:

“Given how this business makes money, what should media be expected to do?”

12. The eCommerce Media Planning Checklist

Before turning the strategy into channel budgets, I would want to understand:

→ What is our AOV?

→ How frequently do customers actually purchase?

→ How does that frequency change across customer cohorts?

→ What is the contribution margin after discounts, fulfilment and returns?

→ What can we sustainably afford to pay for a new customer?

→ How quickly does CAC need to pay back?

→ How much category and brand demand already exists?

→ Where does media need to create demand?

→ Where does media need to capture demand?

→ Which channels are best suited to those jobs?

→ How important are repeat purchase and reactivation?

→ What should success look like at the business level?

Only after answering those questions would I start deciding how much budget belongs in each channel.

Build the Media Mix Around the Business

There is no universal eCommerce media mix.

Search, Shopping, paid social, YouTube, Connected TV, programmatic advertising, retail media and other channels can all play valuable roles.

But their importance changes depending on the commercial problem they are being asked to solve.

AOV tells us something about the economics of the transaction.

Purchase frequency tells us something about the opportunity beyond that transaction.

Together, they provide a useful starting point for thinking about customer journeys, acquisition economics, channel roles, retention and measurement.

The question shouldn't begin with:

“Which channels should we use?”

It should begin with:

“How does this business create customer value, and what does media need to do to help create more of it?”