SERP Features
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SERP features are elements in Google’s search results that go beyond the standard list of organic links. They include direct answers, visual blocks, maps, product listings, video carousels, and AI-generated summaries. For most queries in 2026, a user sees several of these features before or instead of a traditional organic result. As of mid-2026, only around 1.5% of Google first pages contain no SERP features at all.1
Understanding which features appear for your target queries, and how they affect clicks, is essential for accurate traffic forecasting and content strategy.
Why do SERP features matter for SEO strategy?
A page ranking position 1 in 2016 might have captured 30–40% of clicks. The same position today may capture far less if AI Overviews, a featured snippet, and a People Also Ask block sit above it. Alternatively, your page might be cited inside an AI Overview, generating brand exposure even if the user never clicks through.
The SERP is no longer a ranked list: it is a composition. Knowing what that composition looks like for each query shapes how you measure success and what kind of content you produce.
The main SERP features
AI Overviews
AI-generated summaries that appear at the top of the results page, synthesising information from multiple sources to answer a query directly. As of May 2026, AI Overviews reach 2.5 billion monthly users globally.2 They appear on a majority of Google searches and are most prevalent for informational and general knowledge queries; lower (15–20%) for YMYL topics like healthcare and finance.
Pages cited inside AI Overviews don’t always receive clicks, but they do receive brand impressions. There is a strong correlation between pages that win featured snippets and pages that get cited in AI Overviews: the same content signals that trigger one tend to trigger the other. From May 2026, Google added inline links directly alongside cited bullet points and hover previews on desktop, making cited sources more visible within responses.3
AI Mode
A dedicated AI-powered search interface, accessible via a tab in Google Search, that uses Gemini to synthesise multi-step answers for complex queries. Unlike AI Overviews, which appear inline within standard results, AI Mode is a separate conversational experience where follow-up questions carry context from the session. As of May 2026, AI Mode has over one billion monthly users.2
Users can enter AI Mode from the standard search page, or flow directly from an AI Overview by asking a follow-up question. Input is multimodal: text, images, files, and video are all supported.
For keyword research, AI Mode is most relevant for complex, multi-step queries: research tasks, comparisons, and decision-making searches. These query types are increasingly resolved inside AI Mode rather than through organic results.
Featured snippets
A single extracted answer shown above the organic results, drawn from one page. Snippet formats include paragraph (direct answers), list (steps or items), and table (comparisons and data). Featured snippets appeared on around 15% of queries at the start of 2025 and had fallen to roughly 5.5% by mid-2025, as AI Overviews absorbed many queries that previously triggered snippets.
Despite the decline in volume, featured snippets remain worth targeting because: they claim position 0 above all other organic results, they drive strong click-through when they appear, and pages that hold featured snippets are disproportionately cited in AI Overviews.
What are People Also Ask (PAA) boxes?
A PAA box is an expandable set of related questions shown in Google’s search results, each opening to display a brief answer pulled from a source page. PAA boxes appear on a large proportion of informational queries and expand dynamically: clicking one question loads additional questions. Appearing in a PAA box drives modest direct traffic but contributes to topical authority signals and visibility for related queries.
Knowledge panels
Information panels about entities, including people, organisations, places, and products, that appear on the right side of the desktop SERP (or prominently on mobile). Pulled from the Knowledge Graph, Wikipedia, official sources, and structured data. Knowledge panels are not paid placements; Google determines eligibility based on entity prominence and data availability.
Local pack (map pack)
A block of three business listings with a map, appearing for queries with local intent. Click behaviour on local queries is heavily concentrated on these three listings. Ranking in the local pack depends on Google Business Profile signals, proximity, and local authority, separate from the organic algorithm.
Shopping carousels
Product listings from Google Shopping (Merchant Centre) appearing for commercial and transactional queries. Clicking goes to the retailer’s product page. Appearing here requires a Merchant Centre feed, not organic ranking signals.
Video carousels
A row of video thumbnails, primarily from YouTube, appearing for how-to, tutorial, and entertainment queries. Schema markup (VideoObject) and structured data improve eligibility. Optimising for video carousels means optimising on YouTube as well as on your own site.
Sitelinks
Expanded links below a branded search result showing sub-pages of the same site. Appear automatically when Google judges a site to have strong authority for a branded query. Not directly controllable, but reflect site structure and internal linking quality.
Rich snippets
Enhanced organic results showing additional information extracted from structured data: star ratings, review counts, prices, availability, event dates, recipe details. Rich snippets don’t change your ranking position but can increase CTR by making your result more visually distinct.
Generative UI
From summer 2026, Google Search can generate custom interactive interfaces for specific queries: comparison tables, calculators, simulations, and data visualisations built directly in the results page rather than linking to an external page.2 For queries where the user needs to compare options or perform a calculation, Google may satisfy the intent without any outbound click.
Still in early rollout as of mid-2026. Its keyword research implication: comparative and decision-oriented queries may see further click suppression as Google builds the comparison itself.
How do SERP features affect CTR?
Features don’t uniformly reduce clicks. Their effect depends on query type:
- Navigational queries (brand searches, “X login”): sitelinks improve CTR for the target brand
- Informational queries: AI Overviews and featured snippets often answer the query without a click; impressions rise, CTR falls. Ahrefs research (2026) found the top-ranked page on a query with an AI Overview receives 58% fewer clicks than an equivalent page on a query without one.4
- Transactional queries: shopping carousels capture commercial intent; organic results below them still convert well for users who scroll
- Local queries: local pack dominates; organic results below see very low CTR unless the local pack doesn’t match user intent
When tracking rankings for a keyword, always check the SERP composition. A position 3 result below an AI Overview and a featured snippet performs very differently from a position 3 result with no features above it.
AI Mode adds a further layer: queries resolved inside AI Mode often generate no organic clicks at all, since the user stays within the conversational interface. Traditional click-based metrics don’t capture visibility within AI Mode.
How does SERP composition affect traffic forecasting?
Traditional traffic models (position × average CTR) were built for a ten-blue-links SERP. They overestimate traffic for queries where features displace clicks. When building traffic projections:
- Check SERP composition for your target queries before estimating CTR
- Apply lower CTR assumptions for informational queries where AI Overviews are likely
- Apply higher CTR multipliers for queries where your page could win a featured snippet
- Track impressions alongside clicks: impressions from AI Overview citations still have brand value, even without direct clicks
How to target SERP features
For targeting how-tos, including how to structure content for featured snippets, which schema types enable rich snippets, how to get into the local pack, and how to track feature performance in GSC, see How to Target SERP Features.