ChatGPT Ads aren't keyword ads.
We don't treat them like they are.
We map the conversations, problems and buying situations where your business is genuinely relevant. Then we build the ads, landing experience and measurement around them.
Conversation-first analysis. Human-led decisions.
ChatGPT
Google Ads
LinkedIn Ads
Meta Ads
Google Analytics
You'll be working directly withSrivatsa N.Founder, NexaraSearch-ad thinking
doesn't work here.
ChatGPT Ads look familiar enough to tempt advertisers into applying search-ad thinking to them. But conversational relevance is not keyword matching. Get the intent model wrong, and every decision downstream gets weaker.
Treating context hints like keywords.
You describe what you sell instead of understanding the conversations in which someone may actually need it.
- "How do I get my team to use our CRM?" → adoption problem
- "Which CRM integrates with HubSpot?" → actively evaluating
Targeting without context is just broader guessing.
One message for every conversation.
Different problems, buying stages and situations get the same generic ad.
- "What's the difference between ERP and CRM?" → early education
- "How does [Competitor] pricing work?" → late-stage comparison
Relevant placement with irrelevant messaging is still irrelevant.
Clicks are up. Qualified demand isn't.
CTR can look healthy while the people clicking have little commercial value.
- Consultants researching the market
- Competitors checking your messaging
- Curious founders not in-market
Clicks are activity. Pipeline is evidence.
Scaling before the signal is trustworthy.
A new platform, immature benchmarks and weak conversion tracking make premature optimization dangerous.
- CPC dropped → increased spend
- Before confirming: qualified demos or wrong people?
Bad signals compound faster than good intentions.
What happens from the first conversation
to the first useful signal.
We start with the business and buyer, then work outward into conversation intent, campaign structure, measurement and controlled experimentation.
Business & buyer understanding
Before we touch Ads Manager, we map how your business makes money, who actually buys, what triggers demand, and what a valuable conversion looks like. The campaign starts with the buyer, not the platform.
Conversation intent mapping
We map the problems, questions, situations and buying decisions where your business could genuinely be useful. That becomes the foundation for how the account is structured.
Context & message architecture
We turn those conversation territories into focused ad groups, context hints and distinct creative angles. Each message is built for a specific need or situation, not one generic ad stretched across everything.
Landing experience & measurement
We align each campaign with the right landing experience and wire tracking to meaningful business actions. A click only matters if we can see what happened after it.
Controlled launch & optimization
We launch with clear hypotheses and enough separation to learn what is actually working. Then we refine context, creative, landing pages and spend based on qualified outcomes, not activity alone.
Four rules we won't break to make the numbers look better.
Relevance before reach.
More delivery is not automatically better. We would rather appear in fewer conversations where your offer genuinely fits than buy attention that was never commercially useful.
Measurement before optimization.
We don't let platform metrics become the definition of success. Tracking needs to show what happens after the click: qualified enquiries, sign-ups, purchases or whatever outcome actually matters to the business.
One hypothesis at a time.
When context, creative, landing pages and spend all change together, nobody knows what caused the result. We structure tests so there is something useful to learn whether they work or fail.
Scale has to earn its way in.
A new channel does not deserve more budget because impressions, clicks or CTR look encouraging. We increase spend when the downstream evidence gives us a reason to.
The questions we want answered
before the platform starts answering for us.
The mechanics are easy to configure. The harder part is deciding where your business belongs, what should count as success, and what evidence would justify the next decision.
1In what conversations should your business actually be relevant?
Not every conversation related to your category represents a potential buyer. We separate broad interest from the problems, situations and decisions where your offer could genuinely help.
2What would make someone seeing the ad worth paying for?
A click is not enough. We define what a commercially useful visitor or conversion looks like before evaluating campaign performance.
3Does the landing page continue the conversation?
The ad may appear because the user's situation is relevant. The landing page then has to answer that situation clearly. If it falls back to generic company messaging, much of that relevance is lost.
4What exactly are we trying to learn from this campaign?
Every early campaign should test something specific: a buyer problem, conversation territory, message, offer or landing experience. Otherwise spend creates numbers without creating knowledge.
5What evidence would make us increase, change or stop the spend?
We agree on the decision criteria before the results arrive. That makes it harder to rationalize weak performance later simply because the campaign is already running.
Ask these before you let anyone spend your budget on ChatGPT Ads.
The platform is new enough that polished language can easily sound like expertise. These questions expose whether there is an actual method underneath it.
- 01
How are you deciding which conversations we should appear in?
If the answer starts and ends with broad categories or context hints, the strategic work is probably missing. The agency should be able to explain the buyer problems, situations and decisions it is mapping first.
- 02
How will you know whether the traffic is commercially useful?
CTR and clicks are not enough. Ask what happens after the click, how qualified outcomes will be tracked, and how that information will influence future decisions.
- 03
How are you separating what the platform controls from what you control?
ChatGPT decides when an ad is relevant enough to show. The agency still controls the account structure, context provided, creative, landing experience, measurement and budget decisions. Those responsibilities should be clear.
- 04
What exactly are you testing first?
A credible answer should describe a specific hypothesis, not simply "we'll launch and optimize." You should know what the first campaign is intended to prove or disprove.
- 05
What would make you recommend stopping?
A partner should be willing to conclude that ChatGPT Ads are not yet a good acquisition channel for your business. If every result leads to "give it more budget," the incentives are wrong.
- 06
What evidence do you actually have?
Separate experience with paid acquisition from experience specifically running ChatGPT Ads. The platform is new. Be skeptical of claims that imply a long performance history that could not realistically exist.
ChatGPT Ads are worth testing when the economics can support learning.
This is not a channel we recommend simply because it is available. The business, offer and measurement setup need to justify the experiment.
You sell something with meaningful customer value.
There needs to be enough economic upside from a qualified customer to justify paid acquisition and a period of experimentation.
Your buyer has a real problem to think through.
ChatGPT is strongest when people are exploring, comparing, diagnosing or making decisions. If your purchase is purely impulsive, conversational context may add little.
You can identify a meaningful conversion.
Lead, demo, consultation, signup, purchase or another action that gives us something stronger than clicks to optimize around.
You can treat the first phase as a controlled test.
You are willing to establish evidence before demanding scale. Early spend should buy learning and qualified signal, not artificial certainty.
Probably not for you if
You need immediate predictable volume, cannot track post-click outcomes, or only want to be on ChatGPT because competitors might be.
Platform eligibility comes first
OpenAI currently supports a limited set of advertiser categories, so we verify that your business can advertise before recommending a test.
The platform is new.
The underlying problems aren't.
ChatGPT Ads are new. The fundamentals of paid acquisition are not. We bring experience in the parts that still matter: intent, messaging, landing experience, tracking, and qualified demand.
~7× more platform sign-ups
We left the landing page unchanged and fixed where the campaign was finding demand. From a small starting base, sign-ups grew nearly 7× in five weeks on the same budget.
Google Ads example+433% real conversions
The dashboard was counting conversions that did not exist. We fixed the tracking first, then optimized using clean data. Real conversions increased while cost per conversion fell.
Google Ads example0 → 44 real conversions
The original campaign was spending in a market that was not producing real meetings. We moved the same budget to a market with stronger demand and generated 44 real conversions.
Google Ads exampleWhat weak ChatGPT Ads management looks like, and what we do differently.
Questions we get asked
about ChatGPT Ads.
Don't see your question? Email us - we read every one.
hello@nexara.in →When did ChatGPT Ads launch?
Are ChatGPT Ads available in India?
Which industries can advertise on ChatGPT?
How are ChatGPT Ads different from Google Search Ads?
Can advertisers target exact prompts or conversations?
What are context hints?
How do you measure conversions from ChatGPT Ads?
Is ChatGPT Ads suitable for B2B?
Should ChatGPT Ads replace Google Ads?
How long should we test before judging the channel?
Will ads influence ChatGPT's answers?
Srivatsa runs strategy and daily execution on every Nexara account himself, with performance-marketing experience from Merkle, Wipro, and Mu Sigma behind it. He works directly with founders to find where paid acquisition is actually constrained and build campaigns around real buying demand.
Strategy and decisions stay with the founder; a support layer handles reporting, production, and tracking setup against documented workflows. The depth is senior, and nothing stalls if one person is offline.
Talk through ChatGPT Ads
with an Expert.
30 minutes. No pitch deck. We discuss your business, your acquisition situation, and whether ChatGPT Ads are worth testing.
No commitment. The call is diagnostic, not a sales process.
Direct access. You speak with the founder, not a junior rep.
Thinking that applies
across every paid channel.
Platform mechanics change. The underlying questions do not. Read more at nexara.in/notes.
Why Switching Marketing Channels Doesn't Fix What's Actually Broken
The instinct to change channels often leaves the real constraint untouched. Diagnose before you pivot.
Read the note →MeasurementThe Purpose of Analytics
Most businesses measure more than ever but struggle to make better decisions. Analytics was never meant to answer what happened — its real purpose is to improve the next decision.
Read the note →DemandWhy Search Visibility Doesn't Create Demand
Rankings capture what buyers can already articulate, not what makes them buy. Traffic growth without pipeline impact signals a structural misalignment.
Read the note →