Tuesday, July 7

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⚡️ Today’s Headlines ⚡️

✍️ OpenAI can now generate ChatGPT ads for you. The new feature is available under the “Add new ad” option as “Generate ads for you.” The advertiser can then opt to let ChatGPT create the ad, then review, edit, and approve it for delivery on its ad platform.

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🖌️ Meta launched a new AI-powered creative app. The app, called Pocket, lets users create games and tools that others can try out by writing basic prompts for what they want to generate to Meta’s AI.

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🗣️ Meta’s Edits app now has auto-generated bilingual captions. The new update will offer auto-generated text in 15 languages to help brands and creators reach more audiences with their content.

💡 Today’s Insight 💡

ChatGPT commands 92% of AI referral traffic

🗞 TL;DR - For the last year, SEO experts have been betting on which AI platform will win out for discovery. According to a new study from Previsible of 6.77 million LLM-driven sessions, the answer is ChatGPT with its hold of 92.4% of traffic.

💡 Insight - According to the study, AI referral traffic grew 9.9x year over year, reaching more than 644,000 monthly sessions in the dataset from May 2026. While Perplexity, Claude, Gemini, and Copilot continue to grow, none are close to ChatGPT's share.

The study also found that AI referrals are highly volatile. When ChatGPT referrals dropped from 448,412 to 213,345 (most likely due to model-related changes), sessions fell 50% in one month. The major drop proves that one platform’s decisions could halve your AI traffic overnight.

Another emerging trend found in the study is Claude's steady growth, rising in sessions 64x from November 2024 to May 2026. This suggests marketers shouldn't ignore smaller AI platforms even as ChatGPT currently dominates.

The biggest insight from the study though may be that AI traffic is not evenly distributed. Brands that create content aligned with conversational prompts, provide clear answers, and match user intent are capturing a disproportionate share of referrals. Success depends less on traditional keyword rankings and more on creating content that AI models can confidently cite, such as structured, comparable product data and machine-readable pricing.

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