Observed Signal · Mar 25, 2026 · Market Trend · Source: Digiday · Impact: 3/5 · Sentiment: Positive
Marketers Shift Search Spend to GEO
Marketers are reallocating portions of search and SEO budgets toward Generative Engine Optimization (GEO) as generative AI and large language models change how people search and how brands earn visibility. A Scribewise survey of 205 U.S. marketing leaders found 55% have budget lines for GEO and 70% of those say GEO accounts for 11–20% of that budget. Agencies and brands (VML, PMG, Noise Media Group, Pawco) report experimentation and pilot budgets for GEO — PMG recommends 1.5–2x pilot budgets — and some paid-performance dollars are being repurposed for experimental activations and out-of-home to create signals LLMs pick up. Industry sources note measurement and attribution are becoming fuzzier (fewer clicks, more salience/brand mentions), driving tolerance for ambiguity while firms test AEO/GEO approaches.
Widespread budget reallocation toward GEO/AEO (survey-backed and agency-recommended) signals a measurable strategic shift in search and SEO spend driven by LLM-powered discovery; impacts agencies, measurement approaches, and search/organic strategy but is not a single-platform policy change.
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Key Takeaways & Evidence Grounding
- 55% of marketers surveyed have dollars allocated for Generative Engine Optimization (GEO) in their marketing budgets (Scribewise survey of 205 U.S.-based executive leaders and marketing managers).
- 70% of marketers with GEO budgets said GEO strategy accounted for 11–20% of that budget (Scribewise).
- PMG recommends a pilot budget of 1.5 to 2 times the current search budget for GEO (Matt Allfrey, head of SEO EMEA at PMG).
- Pawco increased its budget by 10% in Q1 to test LLM discovery optimization and allocated an estimated 30–35% of budget for its new brand, Genius Dog, to be experimental (Ryan Bouton, vp of growth at Pawco).
- Marketers are reallocating SEO dollars toward GEO/AEO and moving some paid-performance spend to experimental activations and out-of-home to generate LLM-detectable signals.
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Brands Shift Focus to AI Search for Visibility
MarTech contributor Greg Kihlström argues that brand discovery is shifting from traditional search to AI-driven answer engines, making Generative Engine Optimization (GEO) a C-suite priority. Conductor research cited in the article finds nearly one-third of digital marketing leaders view GEO as the top performance challenge for 2026, with 97% reporting positive results from GEO efforts. Companies are reallocating budget and building GEO capabilities in-house—including structured data/schema work, API-based monitoring, publishing long-form authoritative content and prioritizing first‑party data—to remain discoverable by LLM-powered answer engines like ChatGPT and Gemini. The piece says measurement is moving from volume metrics to quality-focused KPIs (e.g., direct conversions from AI referrals, AI search market share and brand sentiment in AI outputs), and warns brands that delays may widen the gap between high-maturity and laggard organizations.
Marketers Optimize GEO Strategies Amid Zero‑Click Search
Digiday+ published a Digiday+ Research excerpt (May 11, 2026) reporting that marketers are adapting geographic (GEO) strategies in response to AI-driven, zero-click search results. The piece, by Li Lu and Catherine Wolf, draws on a survey of 142 brand and agency professionals plus interviews with marketing and technology executives and is excerpted from a larger report titled “The marketer’s guide to AI applications, agentic AI, AI search and GEO/AEO in 2026.” It finds marketers are feeling measurable effects from AI-generated search results that surface answers without site visits, prompting changes to search optimization approaches (GEO/AEO) and broader marketing tactics. The content is distributed as Digiday+ member research.
Generative Engine Optimization Goes Mainstream
CiteLens published a benchmark study (June 2026, Turkey) that ran 320 buyer queries across four AI answer engines — Google AI Mode, Perplexity, Claude and ChatGPT — and compared each engine’s citations to Google and Bing organic results. Results show Google AI Mode (93%) and Perplexity (89%) overwhelmingly cite Google’s top-10 organic results, indicating classic SEO strongly influences those engines. Claude cited Google top-10 results 53% of the time and skewed toward well-known brands (58% of citations went to sites with a Wikipedia presence). ChatGPT cited only 30% from Google top-10 and surfaced many niche domains; fewer than 4% of ChatGPT’s citations were in Bing’s top-10. CiteLens says the findings mean there is no single “AI SEO” and publishes an AI Leaderboard and tooling to measure AI visibility by engine, country and sector.
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