Jellyfish Unifies Paid Media Optimisation Across AI and Social Channels
The Development
Jellyfish, The Brandtech Group's digital marketing arm, has launched AI Ads Optimisation as a major expansion of its proprietary Share of Model platform. Originally introduced in 2024 to measure brand visibility inside large language models, Share of Model now extends paid media optimisation across ChatGPT, TikTok, DV360, YouTube, and Reddit, in addition to its existing Google Performance Max integration. The update also introduces an always-on strategy assistant that continuously surfaces and prioritises recommendations across SEO, brand, PR, paid media, and ecommerce — all actionable from within a single interface. Google PMax, YouTube, DV360, and ChatGPT and TikTok ad optimisation are available globally; Reddit capabilities remain in pilot.
Our Take
Share of Model's expansion is the clearest signal yet that the GEO-to-paid pipeline is collapsing into a single discipline. The insight that prompted the original platform — brands need to understand how LLMs perceive them — has matured into something operationally sharper: act on that perception gap with paid inventory before competitors do. Jellyfish is positioning Generative Engine Marketing as the successor framework to performance marketing, which is an ambitious claim, but the product logic holds. An always-on assistant that pulls signal from organic, influencer, and paid simultaneously and routes it into actionable channel recommendations is genuinely ahead of what independent media buying tools currently do. The real test is whether the ChatGPT ad optimisation layer has enough data density to generate meaningful lift.
What Changed
Marketers can now manage and optimise paid media performance across AI assistant environments and traditional social and programmatic channels from a single platform, with an autonomous recommendation layer that continuously identifies and ranks actions without requiring manual analysis cycles.
Marketing Impact
Paid media and performance marketing teams gain a unified optimisation layer that spans AI assistant inventory and conventional channels simultaneously. The always-on assistant directly reduces analyst hours spent on cross-channel opportunity identification, compressing the insight-to-activation cycle.
Competitive Implication
Agencies running integrated paid and GEO mandates gain a defensible tooling advantage over competitors relying on point solutions. Independent performance agencies without a proprietary platform face accelerating commoditisation pressure as clients consolidate spend with shops that can demonstrate cross-channel AI optimisation in a single view.
Strategic Outlook
Competing platforms — both agency-owned and independent martech vendors — will accelerate their own ChatGPT and AI assistant ad integrations through Q4 2026. Jellyfish's early data advantage across LLM ad performance compounds over time, making the window to close the gap narrow for agencies that move late into 2027.
The Exploit
Action Item
Performance marketing directors at brands spending across three or more of these channels should request a Share of Model audit before Q4 planning locks — the cross-channel recommendation layer surfaces budget reallocation opportunities that channel-specific reporting will not.