Overview
As marketers sift through the rise of ChatGPT Ads, a familiar budgetary dilemma has surfaced for many pay per click teams: should money be moved from paid search into this new placement or left where it is? Based on reporting by Brooke Osmundson for Search Engine Journal, advertisers need to treat ChatGPT Ads as a distinct channel with its own expectations, measurement and risks rather than a direct substitute for Google Search. See the original piece on Search Engine Journal.
What job do you want ChatGPT Ads to do?
The most important question is not how much to spend but why you are spending at all. ChatGPT can meet users earlier in a decision journey by surfacing brand recommendations inside conversational flows, or it can be used to capture near‑purchase intent. Those are very different roles and require different creative, landing pages and success metrics. For many Irish businesses that prize efficient acquisition, the instinct will be to measure the new placement by familiar metrics such as cost per acquisition and return on ad spend. That would be a mistake if the campaign is intended to drive awareness or shape consideration rather than immediate conversions. OpenAI is already positioning the ads product to leverage chat context in ways search does not, and advertisers should build tests to match the job they expect the channel to do. For more on how ChatGPT Ads operate, see OpenAI’s site.
Do you understand the intent you are buying?
Paid search gives you a query, a keyword and a long history of performance. ChatGPT Ads do not. OpenAI uses the conversation context, advertiser Context Hints and other signals to decide when to show an ad, but advertisers do not receive the underlying chat transcripts. That makes the offer of intent visibility very different from keyword data in Google Ads. PPC teams that are used to pruning search term reports, adding negatives and restructuring bids will find fewer of those levers available at first. The upshot is that early ChatGPT traffic will be harder to value with confidence, and teams should be cautious about reallocating large sums from channels where performance history is well established. For background reporting that informed this analysis, see Brooke Osmundson at Search Engine Journal.
Where will the test budget come from?
In the current media environment few advertisers are getting fresh incremental budgets for experiments. Most tests will be funded by trimming existing channels. Paid search is a convenient target for PPC teams, but convenience is not a strategy. If branded search is efficiently capturing demand or non‑brand campaigns are delivering qualified leads at acceptable cost, cutting those programmes to test ChatGPT Ads risks destroying proven value for the sake of an uncertain experiment. A more considered approach is to identify underperforming segments inside a mature Google Ads account or to pool small amounts from several channels so no single proven engine is damaged. Any reallocation decision should include a clear stop loss: what performance outcome will justify keeping the budget in ChatGPT Ads and what will trigger its return to the original channel.
How will you measure success?
Measurement is where many tests live or die. OpenAI now supports Pixel and Conversions API tracking as well as UTMs and conversion optimisation, which means advertisers can link ad impressions to business outcomes in familiar ways. That said, the appropriate metrics differ depending on the channel role. If you are testing direct response, standard lead and purchase tracking will do. If you expect ChatGPT Ads to work mid or upper funnel, last click conversions will underreport value and clicks or CTR are too soft to justify long term investment on their own. Use assisted conversions, CRM attribution, branded search lifts and cohort analyses to build a robust picture before declaring victory or failure. Crucially, set those evaluation criteria before the test begins so results are not retrofitted to support a preferred outcome.
How does paid advertising fit with your organic ChatGPT visibility?
Unlike search results pages, ChatGPT separates advertising from the model’s answers. Ads do not influence the content of replies and brands cannot buy placement inside organic recommendations. That creates a novel dynamic: your brand could run ads against valuable conversations while rarely appearing organically, or you may already benefit from strong organic citations inside the model without spending a euro. Before deciding on paid spend, marketers should audit where their brand already appears in ChatGPT responses and where competitors are being cited instead. For smaller-scale checks, manually testing customer questions can help; for broader monitoring, AI visibility tools can automate tracking of brand mentions and sources. If organic visibility is weak, paid ads alone will not fix perception issues that stem from content, SEO or digital PR gaps.
A case for careful testing, not wholesale shifts
The practical conclusion for Irish advertisers is modest and pragmatic. ChatGPT Ads deserve testing — the product is evolving, and there will be opportunities where conversational context outperforms traditional placements. But every test needs a rationale, a defined role, a measured budget source and a predeclared success metric. PPC teams will run many of the early pilots, yet that does not mean paid search should automatically be the funding stream. Where ChatGPT Ads are compared against alternatives, the comparison should align to the intended outcome whether that is awareness, consideration or conversion.
This assessment draws on reporting by Brooke Osmundson for Search Engine Journal and on vendor documentation from OpenAI. Read the original Search Engine Journal article for more detail and practical examples.
