New U.S.-focused data reported by Search Engine Journal suggests that traffic from ChatGPT ads produced significantly less revenue per visit than Google Search ad traffic, and that many advertisers recorded no sales from those visits. While the figures relate to U.S. traffic rather than the European market, the report adds to an important question for businesses experimenting with AI-driven discovery channels: whether emerging ad formats in AI interfaces can match the commercial intent and conversion performance of traditional search.

What happened

According to the report, advertisers analysing U.S. traffic found that visits coming from ChatGPT ads generated only a fraction of the revenue per visit seen from Google Search ads. The article also says that most advertisers in the dataset did not see sales from ChatGPT ad visits.

The source is reporting on performance data rather than announcing a regulatory or platform policy change. The findings should therefore be treated as an indicator of current advertiser outcomes in a specific market context, not as proof that AI-based ad placements cannot perform commercially in other sectors, countries or campaign types.

Why it matters for European businesses

For European companies, especially SMEs and e-commerce brands, the practical issue is budget allocation. Many businesses are exploring AI search and conversational interfaces as new customer acquisition channels, but performance marketing decisions still depend on measurable outcomes such as leads, sales and revenue per visit.

Google Search continues to benefit from strong user intent: people often search when they are actively comparing suppliers, researching a product or preparing to buy. By contrast, users engaging with AI assistants may be looking for information, summaries or recommendations without immediate purchase intent. That difference can have a direct impact on conversion rates and return on ad spend.

The report also matters because some businesses may be under pressure to test AI-native channels quickly for fear of missing the next shift in digital discovery. The current data suggests companies should avoid assuming that visibility in AI interfaces automatically translates into the same commercial performance as established paid search campaigns.

For marketing teams, this is less a signal to ignore AI platforms and more a reminder to evaluate them with the same commercial discipline used for search, social and display advertising.

Who may be affected

The findings are most relevant to businesses that rely on measurable digital acquisition:

• E-commerce companies comparing conversion performance across search, shopping, social and new AI channels.
• SMEs with limited media budgets that need to prioritise channels with clearer return.
• Marketing teams and agencies testing AI traffic sources and reporting performance to management or clients.
• Founders and commercial leaders deciding whether AI advertising should be treated as an experimental budget line or a core growth channel.

B2B companies may also be affected, although performance can vary widely depending on deal size, buying cycle and whether campaigns are optimised for lead generation rather than direct online sales.

What companies should consider

• Measure by business outcome, not novelty. Track revenue per visit, lead quality, assisted conversions and customer acquisition cost before expanding AI ad spend.
• Separate experimentation from core budget. If testing ads in AI environments, consider using a controlled pilot budget rather than shifting large amounts away from proven search campaigns too early.
• Compare user intent across channels. Lower performance may reflect different audience behaviour rather than poor execution alone.
• Review attribution carefully. Emerging channels can be harder to evaluate if analytics setups are inconsistent or if conversions happen later through another touchpoint.
• Test sector by sector. Results may differ for retail, lead generation, software, professional services or high-consideration purchases.
• Keep watching platform development. Early ad products often change quickly in targeting, placement and reporting, which can materially affect performance over time.

At this stage, the reported U.S. data supports a cautious approach: established search advertising appears to remain the stronger direct-response channel for many advertisers, while AI-based ad inventory may be better treated as an experimental or upper-funnel opportunity until more market-specific evidence is available.