Splitting a Client's Content Budget: SEO, Google's AI Overviews, and the Assistants
Not competing strategies - three distinct layers of how a buyer arrives at a name, each needing different content, different evidence and a different line on the plan.
Three acronyms arrive in planning meetings and compete for the same content budget. They are not alternatives, and treating them as a choice is the fastest way to build a plan you cannot defend six months later.
They map to three different moments: traditional organic results (SEO), Google’s AI summary blocks (AIO), and standalone assistants like ChatGPT, Perplexity and Claude (GEO). McKinsey’s 2025 research found half of consumers now deliberately use AI-powered search, with $750 billion in US revenue projected to flow through it by 2028.
Treat the revenue and conversion figures throughout as market context for planning. They are category forecasts, not outcomes anyone can commit to on a client’s behalf, and client-specific attribution depends on the client’s own analytics.
| SEO | AIO | GEO | |
|---|---|---|---|
| Where it happens | Google results page | Google AI Overview block | ChatGPT, Perplexity, Claude, Gemini |
| Discovery layer | Ranked results | Summary above results | Conversational answer |
| What you measure | Rankings, organic sessions | Inclusion in the overview | Presence in answers, share of mentions |
| Content signal | Authority, links, keywords | E-E-A-T (Google’s experience-expertise-authoritativeness-trust standard), 50–70 word summaries | Answer capsules, attributed statistics, entity density |
| Volume | High (Google: ~15B queries/day) | Very high (13.14% of Google queries) | Growing fast from a small base |
| Competition | Saturated | Moderate | Low - fewer than a quarter of brands have any strategy |
| Time to first signal | 3–6 months | 4–8 weeks | Days to weeks on freshness-weighted platforms |
SEO: still the volume, with a shrinking yield
SEO is improving a site’s visibility in traditional results through keyword targeting, technical health, content relevance and links.
It remains the highest-volume channel. Google processes roughly 15 billion queries a day and holds 89–90% of global search share. Organic search still drives 48.5% of global web traffic against AI platforms’ collective 0.15% (Position.digital, November 2025). Any plan that abandons it is wrong.
The problem is yield rather than volume. Where an AI Overview appears, average organic CTR for the top-ranking page drops from 1.76% to 0.61% (Ahrefs, 2025) - a 61% decline, with paid down 68% (Search Engine Land, 2025). AI Overviews went from 6.49% of queries in January 2025 to 13.14% by March. The client earns the ranking and receives progressively less for it.
Where SEO still wins: high-volume transactional queries, product and category pages, informational content with genuine click intent, and any context where buyers deliberately browse multiple options rather than accepting one recommendation.
AIO: inside Google, by different rules
AIO (AI Overviews optimisation) is structuring content to be cited inside Google’s AI summary blocks, which now appear above organic results for 13.14% of queries.
It sits between the other two: Google’s ecosystem, different selection logic. Domain authority alone does not predict inclusion - a site ranking fifth organically may be cited while the top-ranked site is not, which is the single most useful fact to have ready when a client asks why their number-one position is not appearing in the summary.
It rewards 50–70 word summary answers near the top of a page, FAQPage and HowTo schema, E-E-A-T signals, and longer queries - questions of 8+ words are 7x more likely to trigger an overview (SEranking, 2025). Brands cited in AI Overviews see about 35% more organic clicks than uncited competitors on the same results page.
Where AIO wins: comparison queries, definitional content, and “how do I choose” material where the buyer wants an authoritative answer before committing to a click.
GEO: the uncrowded one
GEO is structuring content so assistants outside Google’s ecosystem cite it in generated responses.
The structural difference is that a cited brand is not one of ten options. It is the recommendation. This is why Semrush’s June 2025 research found AI-referred visitors converting at 4.4x organic: they arrive post-recommendation rather than mid-research.
The opportunity is that almost nobody is doing it deliberately. Only 23% of businesses have any deliberate GEO strategy (Omnius, 2025), and only 16% systematically measure AI search performance (McKinsey, 2025). For an agency, that combination - high buyer intent, low competitive density, near-zero measurement - is unusual and will not persist.
The Princeton GEO study (KDD 2024) identified what actually moves citation rates: quotation addition (+41%), statistics addition (+33%), citing sources (+28%). Keyword stuffing decreased visibility by 9%. Every one of those is an editorial instruction, which is why this line item belongs in a content budget rather than a technical one.
Where GEO wins: consideration-stage questions, “best X for Y” requests, comparative research, and any category where buyers delegate shortlisting to an assistant.
How the three map to a buying journey
| Stage | Primary layer | What the buyer does |
|---|---|---|
| Framing the problem | GEO | ”What should we be looking at for [situation]?” |
| Comparing options | AIO / GEO | ”How does [A] compare to [B] for [use case]?” |
| Validating a choice | SEO / paid | ”[Vendor name] pricing / reviews / implementation” |
| Expanding after purchase | GEO | ”How do we get more out of [product]?” |
Fewer than 10% of sources cited in ChatGPT, Gemini and Copilot rank in the top 10 Google organic results for the same query (McKinsey, 2025). A brand’s own website accounts for only 5–10% of what AI search references; the rest comes from review sites, industry publications, editorial coverage and community content.
That last statistic reframes the work. A plan that only touches the client’s own domain is addressing a minority of what the assistants read.
Four allocation shapes
Optimal splits depend on how the client’s buyers actually behave, not on category convention. These are starting positions to argue from, expressed as proportions of the content and search budget rather than fixed sums.
B2B software
B2B buyers adopt AI-powered search at roughly 3x the rate of consumers (Forrester, 2024), and B2B AI-generated traffic has been growing over 40% per month from a small base.
| Layer | Share | What it buys |
|---|---|---|
| SEO / content | 30% | Pillar content, comparison pages, integration and use-case pages |
| GEO | 25% | Answer capsules for category questions, attributed thought leadership, community presence |
| AIO | 20% | Feature comparison schema, FAQ content per use case, credentialed bylines |
| Paid | 15% | Bottom-funnel branded and competitor terms |
| Experimental | 10% | Podcast and newsletter citations, emerging surfaces |
Professional and specialist services
Buyers here use assistants to build a shortlist before making any contact. The purchase is high-stakes, infrequent and research-intensive - the exact pattern where assistant recommendations carry most weight.
| Layer | Share | What it buys |
|---|---|---|
| GEO | 35% | Answer-shaped thought leadership, proprietary data, named-expert entity building |
| SEO / content | 30% | Practice and specialism pages, case studies |
| AIO | 20% | FAQ schema per service area, comparison content, expert quotes |
| PR / third-party | 15% | Trade coverage, industry association content, conference presence |
Considered-purchase ecommerce and manufacturing
In these categories more than 65% of AI-sourced citations come from publishers, user-generated content and affiliates rather than brand websites (McKinsey, 2025).
| Layer | Share | What it buys |
|---|---|---|
| SEO / paid | 35% | Product and category SEO, shopping, brand terms |
| AIO | 25% | Product schema, buying guides, 50–70 word summary blocks |
| GEO | 20% | Coverage in AI-indexed publications, review-site and community presence |
| Social / other | 20% | Platform-native discovery |
Multi-brand or portfolio clients
Where one client owns several brands or product lines, the constraint is usually editorial capacity rather than budget. The allocation matters less than the sequencing: instrument every brand, then concentrate production on the two or three where the assistants currently return a competitor’s name for high-value questions. Spreading production evenly across a portfolio is the most common way this budget gets wasted.
The reallocation argument, honestly stated
For B2B and professional services specifically, moving 15–20% of an SEO budget toward GEO is defensible on four grounds.
- Competitive density. A client competing for a saturated commercial keyword faces hundreds of well-resourced rivals. The same client competing to be named in an assistant’s answer to the same buying question faces a category where most competitors have published nothing addressing it directly.
- Buyer stage. AI-referred visitors arrive post-recommendation. The 4.4x conversion differential (Semrush, June 2025) means a smaller volume can be worth modelling carefully against a larger one - with the client’s own numbers, not a benchmark.
- Feedback speed. Freshness-weighted platforms surface new material quickly, so a programme produces evidence in weeks rather than quarters. That matters more for retaining a client than it does for the client.
- Compounding. A brand cited consistently across multiple AI-read sources accumulates a position that is progressively harder to displace.
It is a portfolio adjustment, not a replacement. The most practical version is not new spend at all: it is restructuring content already being commissioned - answer capsules, attributed statistics, comparison sections, direct claims - so the same budget produces material that works in both channels.
Measuring each layer
| Measure | What it tells you |
|---|---|
| Presence in answers | Share of target buying questions where the client is named |
| Share of mentions | Client versus competitors across the same question set |
| Source attribution | Which pages assistants actually draw from |
| Framing and sentiment | How the client is characterised when named |
| Published-work performance | Readers, click-throughs to the client’s site, last assistant fetch |
Content updated within the past 30 days receives roughly 3.2x more ChatGPT citations than older content (Onely, 2025), which sets the cadence: monthly at minimum, with refreshes planned rather than improvised.
The last row is the one most measurement frameworks omit and the one that most changes what gets commissioned. Knowing which published pieces are being read, which are sending people through to the client’s site, and when the assistants last fetched them tells you what the category actually responds to. Combined with the gap data, it means next month’s brief is decided by two kinds of evidence rather than by a planning instinct. A named editor - yours or your client’s - still makes the call, but they make it holding something.
Frequently asked questions
What is the difference between the three? SEO targets rankings on Google’s traditional results. AIO targets Google’s AI summary blocks above them. GEO targets citations inside standalone assistants like ChatGPT, Perplexity and Claude.
Which comes first? Maintain the SEO investment and add a 15–20% GEO allocation. With fewer than a quarter of brands holding any deliberate GEO strategy (Omnius, 2025), it is the least contested high-intent channel currently available.
Does GEO work damage SEO performance? No. Content structured for AI citation also improves E-E-A-T signals and snippet eligibility. The techniques are additive.
How does AI search affect click-through rates? Where a Google AI Overview appears, average organic CTR drops from 1.76% to 0.61% (Ahrefs, 2025).
Do AI-referred visitors convert better? Semrush (June 2025) found 4.4x organic. Treat it as a market benchmark; client-specific conversion has to come from the client’s analytics.
Which clients benefit most? B2B and professional services, because the competitive bar for being named in an assistant’s answer is dramatically lower than the bar for ranking on a contested commercial keyword.
Key takeaways
- The three are not interchangeable. Different platforms, different content, different moments in a buying decision.
- SEO is not dying; its yield is falling. A 61% CTR drop on AI Overview queries means clients must be cited in summaries to retain traffic they already earned.
- GEO is the uncrowded layer. Fewer than a quarter of brands have any deliberate strategy and only 16% measure anything. That will not last.
- AI-referred buyers are qualitatively different. They arrive post-recommendation, which is why benchmark conversion rates are so much higher.
- Allocation follows buyer behaviour, not category convention. B2B software and professional services justify the largest GEO share.
- Measurement needs two signals, not one. What the assistants say now, and what the published work earned. Either alone produces a worse brief.
- The strongest version of the reallocation costs nothing new. Restructure content already being commissioned so it works in both channels.
Found by AI monitors how leading AI assistants answer buying questions, produces the content that addresses the gaps, and reports on what it earns - under our partners’ brands, never in front of their clients. See how the partner programme works.
What to do with this
The gaps are the brief. We write what fills them.
Monitoring shows which buying questions the leading AI assistants answer with somebody else’s name. Those questions become the month’s articles, answer blocks, fact sections, FAQs and refreshes - written, published and measured under our partners’ brands.