By David McGuckin — May 8, 2025

Understanding Google’s SERP Features (and AI Overviews) – A Guide for SEOs and Marketers

Google’s search results are filled with special features like featured snippets, local packs, AI overviews, and more—each impacting how users find and click on content.

Google’s search results page isn’t just “10 blue links” anymore – it’s filled with special SERP features that can dominate the page. In fact, nearly 99% of Google searches include at least one SERP featureahrefs.com. These range from direct answer boxes and carousels, to image packs, local maps, and more. Each feature influences how users engage with the page and how your content can (or can’t) appear. Some features offer quick answers with no clicks needed, contributing to the high rate of “zero-click” searches (one study found 65% of searches ended without a click because users got their answer directly on the SERPahrefs.com). Others do include links that you can target to drive trafficseranking.com.

Adding another layer, Google’s new AI-powered overviews (generative AI answers at the top of the SERP) are one of the most disruptive changes since featured snippetssemrush.com. These AI overviews can summarize information from multiple sources and potentially siphon attention away from traditional results and features. Understanding how each SERP feature works – and how the AI overview might tap into or overshadow it – is crucial for modern SEO strategy.

Below, we’ll explain each major SERP feature, what it looks like, its impact on visibility and SEO, how Google’s AI overview might interact with it, and whether you can track or optimize for that feature. Use this as a roadmap to prioritize your efforts and ensure your content still shines in an AI-infused search landscape.

Featured Snippet

What it is: A Featured Snippet is a highlighted answer excerpt that Google pulls from a webpage, displayed at the top of the organic results (in position “0”). It can be a paragraph of text, a list, a table, or even include an image. It directly addresses the user’s query with a concise answer and always includes a link to the source webpagesemrush.com. For example, if you ask “How does photosynthesis work?”, Google might show a short blurb from a science site explaining the process, with the page title and URL.

SEO/Visibility impact: Featured snippets are highly visible (often above all other results), which can dramatically increase your brand’s exposure. If your page wins the snippet, you effectively leapfrog to the top. This can boost click-through rates – though paradoxically, sometimes the snippet gives away the answer so clearly that users may not click at all. To optimize for these, focus on answering specific questions clearly and succinctly. Use headings or lists that match common question phrases. Being featured signals authority and can steal traffic from the #1 organic spot if you’re not there. On the flip side, if a competitor holds the snippet for a query you rank for, you might see lower clicks even if you’re high in the normal rankingsahrefs.com.

AI overview interaction: Google’s AI-generated overview is somewhat analogous to an expanded featured snippet – it also provides an answer summary. The AI overview, however, might pull from multiple sources instead of one. If AI overviews roll out widely, they could reduce the prominence of featured snippets (since the AI answer appears even above them). It’s possible the AI summary might even use the same content that appears in a featured snippet, but blended with other sources. In any case, if an AI overview satisfies the query, users might not scroll to see the featured snippet. However, Google’s own documentation suggests featured snippets will continue to appear for many queries, so it’s still worth aiming for them. Also, being the source of a featured snippet likely means you’re a trustworthy source – which could increase your chances of being cited by the AI overview as well (since the AI often references top-ranked content).

Trackability: Yes – trackable. Featured snippets contain a URL, so you can identify when your site is in a snippet (Google Search Console and rank tracking tools can flag this). It’s effectively an organic result (one that’s elevated), so data on clicks/impressions is available. Prioritize featured snippet opportunities as they’re one of the few special features that directly drive traffic to your site.

Answer Box (Direct Answer)

What it is: An Answer Box is a direct answer that Google shows for factual queries – often pulled from Google’s own Knowledge Graph or a trusted public domain source. It typically appears at the top of the results in a simple box with text (and sometimes an image). Unlike featured snippets, answer boxes are usually not attributed to a specific external website (or may cite a generic source like Wikipedia or a dictionary). For example, if you search “Halloween 2024 date”, you might just see “Thursday, 31 October – Halloween 2024” in a boxdataforseo.com. These are sometimes called “instant answers” or knowledge cards.

SEO/Visibility impact: Answer boxes provide the information instantly, so the user often doesn’t need to click any result. This means they can significantly reduce organic click-through for that query – if Google provides the answer (like a date, calculation, or simple fact), there’s little reason for the user to visit a website. From a branding perspective, there’s also typically no credit given (or a very small citation) to your site even if your content informed the answer. That makes these boxes a bit of a double-edged sword: they greatly improve user experience but can cause zero-click searches. As an SEO, you usually can’t directly optimize for answer boxes the way you would for featured snippets, because Google often draws on its own data or extremely authoritative sources. However, marking up factual content with structured data (like definitions, calculations, etc.) might help if Google ever chooses an external source. In general, don’t rely on answer-box queries for traffic – instead, try to target longer-tail queries where users need more explanation (those tend to trigger featured snippets or organic clicks rather than a simple answer box).

AI overview interaction: AI overviews might handle these ultra-simple questions internally. For example, if you ask a question like “What’s 5+5?” or “Capital of France”, the AI overview (if triggered) could answer in the conversational response – or Google might decide to just show the usual answer box. In many cases, straightforward factual queries might not trigger the generative AI at all, since a one-line answer suffices. If AI is used, it’s likely pulling from the same knowledge base that feeds answer boxes (Google’s Knowledge Graph, Wikipedia, etc.). In effect, the AI overview could render answer boxes redundant for those queries by integrating the fact into a broader answer. But from a strategy view, there’s not much an SEO can do here except ensure your business’s facts (like your company’s founding date or CEO name) are correct in the Knowledge Graph so that if an AI or answer box shows info about you, it’s accurate.

Trackability: No – not directly trackable. Answer boxes typically don’t have a clickable link to your website (unless it’s citing an external source like Wikipedia), so they don’t show up in your analytics or Search Console as a clicked result. You can track if an answer box appears for a keyword (SEO tools often note its presence), but you won’t get traffic from it. Essentially, it’s a feature to be aware of (as competition for user attention) rather than one you can “win” for your site in any meaningful way.

Knowledge Graph Panel (Knowledge Panel)

What it is: The Knowledge Graph panel is the information box that appears on the right side of desktop search results (or top on mobile) for known entities – people, places, organizations, movies, etc. It’s also commonly called a Knowledge Panel. It displays a curated summary of facts about the entity: names, descriptions, photos, key details, and related links. For instance, searching a celebrity or a company often triggers a knowledge panel with a bio, picture, birth/founder date, stock price (for companies), social profiles, and so on. This info is pulled from Google’s Knowledge Graph – a huge database of interconnected facts. It’s not one of the “organic results”, but rather a standalone feature with data and sometimes links (like a Wikipedia link, official site, or social media). According to Google, the knowledge panel “displays extra information about the topic” (often with images, related searches, etc.) and is specifically positioned on the right on desktopdataforseo.com.

SEO/Visibility impact: For branded searches (your company or personal brand), the knowledge panel is prime real estate. It can reinforce credibility by showing that Google “knows” your entity. If you have control of your presence (via a Google Business Profile for businesses, or claiming your panel via Google’s processes), you can influence some aspects like suggesting changes to facts or updating your images. However, for most entities, Google decides what to show from various sources (Wikipedia, official databases, etc.). From an SEO perspective, you’re not getting click traffic from the panel itself (it’s informational), but it certainly affects user behavior. For example, if a user’s query is satisfied by reading the panel, they might not click your site which is ranking organically. On the other hand, the panel often contains a link to your homepage or a Wikipedia page – so ensuring those sources are accurate is important. Marketers should optimize their Knowledge Graph presence by doing things like: maintaining a Wikipedia page if appropriate, using schema markup on your site to feed info to the Graph, and keeping your Google Business Profile updated (for local businesses). In local SEO, that panel (which doubles as a Google Business Profile summary) is critical for conversions (showing reviews, hours, etc.). Overall, the knowledge panel boosts visibility and credibility but doesn’t directly drive clicks unless users interact with a specific link in it.

AI overview interaction: An AI-powered overview could incorporate a lot of the same information found in a knowledge panel. For example, if someone asks, “Who is Elon Musk?” an AI summary might provide a quick bio and relevant facts – essentially duplicating what the knowledge panel shows, but in sentence form and possibly with multiple sources cited. In early observations, the AI overview might appear alongside the knowledge panel (the AI text on the left, and the panel on the right on desktop). In such cases, the knowledge panel still serves users who glance to the side for structured info. However, if the AI can present that info in its answer, some users might ignore the panel. There’s also a chance the AI overview might pull in data from the Knowledge Graph (e.g. birth dates, etc.) to ensure accuracy. If your brand has a knowledge panel, the AI might summarize info from it, potentially reducing clicks on the panel’s links. In short, the knowledge panel data is likely a source for AI answers, but the panel itself will probably remain for quick reference. Ensure your Knowledge Graph info is accurate so that whether it’s shown in a panel or used by AI, users get correct information.

Trackability: Not directly trackable. The knowledge graph/panel is not an organic result with your website’s link (unless your site’s link is included as one of the reference links). You won’t see “rank #0” traffic from it. It’s an element you monitor (does my brand have a panel? is the info correct?) rather than something that shows up in ranking reports. Only when users click through (e.g. on your website link or on a social profile) would you see any referral, and those clicks are relatively few compared to how many eyeballs the panel gets. So, treat it as brand visibility rather than a traffic source.

People Also Search For (PASF)

What it is: “People Also Search For” is a related-search feature that usually appears after a user clicks a result and then returns to the SERP. It’s a bit hidden in normal view – you won’t usually see it on the initial page load. The way it works: suppose you search something, click a result, and then hit the back button because that result didn’t satisfy you. Google then displays a small box under the result you clicked, labeled “People also search for”, with a handful of other queries that are related. These are essentially suggestions for what you might try searching next. For example, you search “best running shoes”, click a result, then come back – under that result you might see suggestions like “running shoe reviews” or “best running shoes for flat feet”. This is Google’s way of helping you refine or broaden your search if your first click wasn’t the answer. It’s often abbreviated as PASF in SEO circles. One key point: A “People Also Search For” box only gets triggered when you go back to the results after clicking a resultseobuddy.com. In contrast to PAA, which is always visible on the page, PASF is behavior-dependent.

SEO/Visibility impact: PASF is less directly “winnable” – it doesn’t feature content or links to your site (it’s suggesting alternative queries to the user). So you can’t be the “answer” in a PASF box; you can only hope to rank for those related searches if the user chooses one. The presence of PASF suggests the user’s first attempt didn’t satisfy them, so Google is trying to keep them on track by offering related topics. For marketers, those PASF keywords are useful insights. They show you what other terms people commonly search in relation to the topic. You can leverage that for keyword research – perhaps include content that addresses those related queries to capture users who refine their search. While PASF doesn’t directly improve your visibility on the initial query, it can indirectly drive traffic if you rank for one of the suggestions a user clicks next. Also, note that PASF suggestions often overlap with Related Searches (the ones at the bottom of the page – see next section), but they’re triggered contextually. As an SEO, you might want to intentionally search for your target keywords, click a result, and see what suggestions Google offers when you return. Those could be content gaps you can fill. The existence of PASF on a query indicates that users often pogo-stick (click, then go back) on that query, meaning no one result is satisfying – which is a hint that maybe a comprehensive or different approach content could serve that query better. However, there’s no direct ranking boost or anything from PASF itself; it’s more about understanding user behavior and related interests.

AI overview interaction: If Google’s AI overview effectively answers a user’s query on the first try, the user might not need to click a result and come back – thus potentially preventing the PASF scenario from ever happening. In other words, a good AI answer could reduce pogo-sticking. Also, an AI chat-like interface might handle the “People also search for” function by just letting the user ask a follow-up in the chat or showing suggested follow-up questions as part of the AI result. Google’s SGE, for example, sometimes shows “Ask a follow-up” prompts which are essentially the AI’s version of related searches. These might replace or reduce the use of the traditional PASF box. If the AI is guiding the user to refine the query, the user might never scroll down or trigger the classic PASF. That said, PASF isn’t gone yet – it will likely still appear for users who don’t have AI results (or if the AI isn’t available for that query or user). Over time, if AI makes search sessions more conversational and less “click back and forth”, PASF could become less common. For now, marketers should treat PASF suggestions similarly to how they treat PAA or Related Searches – as ideas for what the AI might also get asked. In fact, those same topics might be good to cover in your content because if the user doesn’t go back to Google but instead asks the AI a follow-up, you’d want your content to potentially be sourced in that follow-up answer. In summary, AI might subsume the role of PASF by proactively offering or handling follow-up queries.

Trackability: Not applicable for direct tracking. Since PASF are just suggested queries, there’s nothing for your site to “track” unless the user actually searches one and then you have a result. You won’t see in Search Console that your site appeared in a PASF box (because your site isn’t in it). If you rank for a PASF-suggested query and the user clicks that suggestion, then your site might get an impression/click for that second query – but you’d have no way to tie it to the PASF event specifically. So, think of PASF as a research tool, not a metric. You might manually note “Google showed these 5 related searches when I did X” but beyond that there’s nothing in analytics to capture.

What it is: Related Searches are the queries listed at the bottom of the Google search results page under a heading like “Searches related to [your query]”. These eight (usually) suggestions are alternative or refined searches that Google thinks are relevant to the original query. They’ve been around for a long time as a way to guide users to explore further. For example, if you search “content marketing strategy”, at the bottom you might see related searches like “content marketing strategy examples”, “content marketing plan template”, etc. Unlike PASF, these are always visible on the initial SERP (no interaction needed), but they serve a similar purpose of helping users find the next thing to search if the current results aren’t quite what they want. Essentially, they are common expansions or variations of the query. As one definition puts it, Google displays Related Searches at the bottom of almost every results page – a list of searches connected to the initial querydataforseo.com.

SEO/Visibility impact: Related searches don’t directly display any website’s content, but they are valuable clues for SEOs. Much like PASF, they tell you “people who searched for X also tend to search for Y.” If your content strategy covers those related topics, you can potentially capture more of that user journey. Also, if a related search is very close to your main keyword, it might be worth optimizing a page for it (or incorporating it as a subsection) because clearly Google sees it as relevant. Sometimes, related searches can reveal user intent nuances – for instance, adding words like “for beginners” or “2025” or “cost” indicates what information people specifically want. By addressing those in your content or having dedicated pages, you stand a chance to rank when users click those suggestions. From a pure SERP feature perspective, related searches occupy space at the bottom – they don’t push your results down (since they’re after all results), but they can draw a user’s attention after they’ve scrolled through results. A user might glance at them and decide to try one of those queries instead of clicking any of the current results, which means you lose that visit if you were ranking on the first query. Conversely, if your site ranks for one of the related searches and the user goes there, you gain a visitor on the second query. Marketers should monitor what Google lists here for their primary keywords as it often overlaps with keyword research, and ensure their content strategy aligns with these terms. They can be low-hanging fruit for SEO content.

AI overview interaction: Similar to PASF, AI results may preempt related searches. If the AI provides a comprehensive answer and perhaps even suggests follow-up questions in its interface, a user might not scroll to the bottom at all. Google’s AI experiment sometimes showed “Ask a follow-up” or a set of suggestions directly below the AI answer, which are basically Google’s AI-era version of related searches. If those become standard, the classic list of blue links at the bottom might become less prominent. However, even in an AI-driven result, Google might still show the related searches section for those who scroll past everything (currently, in SGE tests, the related searches often still appear below the AI and organic results). In any case, the existence of related concepts remains – the AI just might surface them differently. Another angle: the AI overview might use related searches internally to broaden its answer. For example, if the query is broad, the AI might incorporate aspects that people usually refine (which are essentially those related searches). Google has a feature called “Things to know” (for broader topics) which is somewhat analogous to an AI summarizing subtopics – and related searches often reflect those subtopics. We may see the AI effectively doing the job of guiding the user that the related searches list does. For now, continue to consider related searches in your SEO strategy – they likely indicate what the AI might cover too. If Google’s AI sees that a lot of people who ask about “X” also want to know “Y”, it might proactively include info about “Y” in the initial AI answer. So, covering related search topics in your content could also mean the AI is more likely to cite you in a comprehensive answer.

Trackability: Not directly trackable. Related searches are just queries, not results. You can’t “rank in the related searches box.” Thus, you won’t see anything in Search Console about appearing there. You can track the queries themselves – i.e., if you optimize for those suggestions and then rank, you’ll see impressions/clicks for them as normal keywords. So the value here is indirect: use them for ideation and then track your performance on those terms.

Organic Results (Classic Blue Links)

What it is: The Organic results are the traditional search listings – typically title, URL, and snippet – that appear for a query, which are not paid ads. These are the results that SEOs have optimized for since the dawn of Google. When no special SERP features interrupt, Google generally shows 10 organic results on a page (sometimes fewer on page 1 due to other features taking space). Organic results can themselves have “rich results” enhancements (like star ratings, sitelinks, etc.), but they’re fundamentally the web page listings that Google’s ranking algorithm (SEO) determines. They appear in the main left column. For instance, if you search “best Italian restaurants in Belfast”, below any map pack or ads, you might see normal organic links to restaurant review websites or lists of Italian restaurants.

SEO/Visibility impact: Organic results remain the primary source of SEO traffic for most sites. If you rank #1 organically for a query without too many SERP features, you stand to gain a large share of clicks. However, with the proliferation of features, the organic results are often pushed down. It’s not uncommon that the first organic listing is actually halfway down the page, after an AI overview, maybe a featured snippet, a PAA box, and an image carousel. This means that even being #1 organically might not guarantee the traffic it once did, as user attention could be stolen by above-the-fold features. Nevertheless, being on page 1 is still crucial – the majority of users will click an organic result if the SERP features didn’t already satisfy them. Marketers should continue to prioritize technical and content SEO to rank high organically. The presence of features just means you may need to also optimize for those (where possible) or at least be aware of them. One silver lining: many SERP features themselves are fed by high-ranking organic content (featured snippets, PAAs, etc.), so strong organic performance often begets presence in features. Also, not all queries have heavy features; for many long-tail or specific intents, the organic list is still king. In summary, organic results are your main SEO battleground, but the context around them has changed. You want to rank high and ideally be the source of featured snippets/PAA when relevant.

AI overview interaction: AI overviews will likely have a significant impact on organic results. If an AI summary answers the query at the top, some users might not scroll to the organic listings at all – similar to how featured snippets could cause zero-click, but possibly on a larger scale for certain queries. However, one important aspect: Google’s AI overview (as tested) includes citations with links to sources. These are often shown as small clickable cards or links to the websites that contributed information. Essentially, those are organic results being elevated into the AI box. If your site is one of the 3-5 sources cited by the AI, you might actually get a click from that AI box (some early studies showed users do click those source links). It’s a new kind of organic visibility: instead of just the 10 blue links below, a few lucky sites get featured above in the AI result. The criteria seem to heavily favor already top-ranked content. So SEO strategy in an AI world might shift toward optimizing to be a cited source – which probably means having authoritative, well-structured content that the AI chooses as representative of the answer. If you’re not cited and the AI answer suffices, your organic listing might see drop in CTR. On the flip side, if AI overviews lead to users refining queries less or not going deeper, perhaps the total number of organic clicks per search could decline for info queries. It’s early to say, but anticipate lower organic CTR on queries that now trigger AI summaries (just as we saw CTR declines on queries with featured snippets or big knowledge panels). In any case, organic SEO isn’t going away – but it’s evolving. You should monitor which of your keyword queries start showing AI results and see if your traffic drops for those. Then adjust by trying to get into that AI’s citations. Google has indicated that being in the top 10 is a common trait of AI-cited pages, so classic SEO (to get into that top ten) remains foundationalseranking.com.

Trackability: Yes – fully trackable. Organic results are what Google Search Console and all rank trackers focus on by default. You’ll see impressions, position, and clicks for your organic rankings. If an AI overview appears, currently Search Console doesn’t explicitly separate that out – it would still count a click from the AI box citation as an organic click for that query (presumably). Over time Google might refine reporting, but the standard organic tracking is still in place.

Paid Results (Google Ads)

What it is: Paid results on Google (often just called Google Ads or sponsored results) are advertisements that appear above or below the organic results. They usually show for commercial queries. They’re typically text ads that look somewhat like organic listings but are marked with a small “Ad” or “Sponsored” label. On desktop, you might see up to four ads at the top and a few at the bottom; on mobile, sometimes ads also appear mid-stream. There are also specialized paid features like Shopping ads (with images; we’ll discuss those separately). Paid search results are an SEM (search engine marketing) domain rather than SEO, but they heavily impact the SERP layout. Top Ads vs Bottom Ads: The ones at the very top get prime attention – they can push everything else down. According to industry knowledge, top and bottom ads and Shopping results are always marked as sponsoredseranking.com, ensuring users know they’re advertisements.

SEO/Visibility impact: From an SEO perspective, paid ads are “competition” for user attention that you can’t beat with organic effort. If someone is bidding high to appear on a keyword, their ad will show above you no matter how good your SEO is. This can siphon off clicks that might have gone to the organic results. For example, if you rank #1 for “best CRM software” but there are three ads on top, some users will click those ads instead of scrolling to you. The more ads on a query, the lower the organic CTR tends to be. Marketers need to be aware which keywords important to them are dominated by ads – sometimes the entire above-the-fold screen is ads and maybe a featured snippet. You might consider running your own ads for those queries if they’re critical (that’s an SEM decision, of course). Also, note that ads can come with ad extensions (sitelinks, callouts, etc.) that make them even more eye-catching. For SEO reporting, it’s wise to temper expectations on high-value commercial terms – even if you rank well, your traffic share might be small if ads are absorbing most clicks at the top. In terms of strategy, some companies focus SEO on queries that don’t have heavy ad competition (informational queries, long-tails) and use PPC for the highly commercial ones, to cover all bases. Paid and organic can also work together – sometimes having both an ad and an organic result yields more total real estate (if budget allows). For pure SEO, though, understand that ads are essentially a SERP feature that displaces you. There’s no optimizing into the ad section except by buying ads.

AI overview interaction: AI overviews at present do not include ads – they are generated answers. However, Google will surely find ways to monetize AI answers if they become a staple. It’s possible Google could show sponsored results or “ads” integrated with the AI (maybe a sponsored mention or a product listing if the query is product-focused). But for now, think of AI overviews as another content block pushing organics down – but unlike ads, you can’t pay to get in it (and unlike organic, you can’t exactly optimize specifically for it yet either, aside from strong content). Interestingly, if AI answers keep users on Google longer, it might actually increase Google’s ability to show ads (in a traditional sense) elsewhere on the page or in subsequent interactions. For example, maybe after the AI answer, as you scroll, you’ll see ads relevant to that query or follow-ups. We might also see fewer top-of-page text ads if the AI box is there (because it would be weird to have an answer and then clearly labeled ads below it, but Google could). In short, AI overviews don’t directly “pull” from paid results – they pull from organic content. But the presence of AI is another thing pushing organic (and even paid text ads) further down. Marketers should watch how Google experiments with ads in an AI-driven SERP. It could be that ads still appear at top, followed by AI box, which would be doubly tough for organic (imagine: Ads, then AI, then maybe one snippet, then organics). Or Google might cut back on ads for queries with AI answers, which would be interesting – but Google’s revenue model likely means ads will be present in some form. We might end up with new ad formats (e.g., an ad that appears as one of the “options” the AI suggests – purely speculative). For now, assume ads and AI will coexist, each taking up space.

Trackability: Yes (for presence, via ad platforms). If you are running ads, you track their performance through Google Ads, not through SEO tools. If you’re not running ads, you can’t directly “track” ads except to manually see that “on this query, 3 ads show up.” SEO tools sometimes report if ads are present on a SERP and how many, but not their content unless you specifically scrape. From an organic standpoint, just note that if ads are present, your impressions might remain the same but clicks could be lower than expected. There’s no direct analytics in GA or GSC for “lost clicks to ads” – it’s just a competition factor to consider.

Carousel (Horizontal Carousel Results)

What it is: In Google SERPs, a Carousel refers to a row of horizontally scrollable results or items. These usually appear for certain queries that have multiple entities or answers. For example, a search for “best horror movies” might show a carousel at the top with movie posters or titles that you can scroll through. Each card in the carousel is often a link to a new Google search for that entity or a result related to it. Carousels are very visual and interactive. Common carousel types include: movies, books, tourist attractions, “People also search for” images of celebrities, etc. One key thing: clicking an item in a carousel usually takes you to a new SERP focused on that item (it’s not a direct click to an external website in many cases). According to one resource, carousel results appear for general queries with several relevant answers (a group of results)seranking.com. They’re eye-catching and often appear at the top or mid-SERP.

SEO/Visibility impact: Carousels can push organic results down, and they can capture user interest (especially if they have images). If the carousel items are things (entities) rather than webpages, then as an SEO you can’t directly appear as an item – they’re more like a navigational feature. However, if you run a site about those entities, you’d want to rank when someone clicks one. For instance, if you have a page about “LeBron James” and the user clicks his name in a “NBA players” carousel, the next SERP is basically “LeBron James” – you’d want to be ranking there. Another scenario: sometimes carousels are of actual results (like Top Stories or certain video carousels) – those we cover separately. The generic “Carousel” feature often means a set of related topics. For SEOs, one benefit is that if your page is part of a list (like “top 10 X” article and Google makes a carousel of the items in that list), your site might indirectly benefit if Google sometimes shows a link to the source (though often they don’t – they just use your content to build a carousel). An example: A carousel titled “Best Android games” might show games and when clicking one, among the results might be the article that originally listed them, but not guaranteed. Strategically, you should note when your target queries trigger a carousel of entities – it means the user might bypass your site and click into some entity page instead. You could adjust by creating content targeting those specific entities as queries. Carousels also often indicate that the query is broad, and Google is offering a refinement. It’s similar to related searches, but in a more visual way. If you write about broad topics, consider how you might also cover the specific items that a carousel surfaces. From a CTR perspective, carousels (especially image-heavy ones) can attract clicks or swipes, meaning less attention on the standard results.

AI overview interaction: An AI overview might reduce the need for a carousel by summarizing the group of entities. For example, instead of a carousel of “best horror movies”, the AI might directly list a few top horror movies in its answer (“Some of the best horror movies include The Exorcist, Halloween, Get Out, etc.”) along with context. That essentially is what a carousel would have offered, but now in text form with links. If the AI lists those movies (and perhaps even provides links or a dropdown), a user might not interact with the old carousel interface. However, Google could also integrate carousels into the AI result – maybe the AI says “Here are a few options” and presents them visually. It’s uncertain, but we do know Google’s AI can output lists and could make carousels somewhat redundant for certain queries. Another thing: carousels that are about exploration (like different categories) might be replaced by the AI breaking down the topic. Google has a feature called “Things to know” (which is like an AI-lite feature) that breaks a topic into subtopics. AI could expand on that idea, giving a structured overview rather than a flat carousel. If AI overviews cover multiple angles, Google might show fewer generic carousels. That said, some carousels are very useful for navigation (like scrolling through actors or albums). Possibly Google will keep those for visual appeal. For SEOs, if AI is listing out entities that were formerly in a carousel, you want to ensure if possible that your brand or content is associated with those entities in a positive way (for example, if AI lists “top products” that used to be a carousel, maybe it cites a review site – you’d want to be that review site). In summary, AI might absorb or replace many carousel functions by providing the grouped answers directly.

Trackability: Not directly trackable as a result. Carousels themselves aren’t something your site “occupies” (unless it’s a carousel of actual content like Top Stories, which is covered separately). You can track if a carousel feature appears for a keyword (SEO tools note the presence of a carousel), but there’s no performance data for you unless the user clicks into something that leads to your site. In Google Search Console, you wouldn’t see “position 1 in carousel”; you’d just continue to see how you rank for queries that might be one click away. If your site’s impression comes after a user clicks a carousel item (like user searches broad query, clicks an entity, then your site shows up), that’s a second query – only that second query would appear in your performance data, not the first one. So carousels can indirectly funnel traffic to you, but it’s hard to measure the connection. They mostly alert you to how Google is structuring results.

Multi-carousel (Multiple Carousels)

What it is: A Multi-carousel is essentially when Google presents several carousels, usually stacked, each with a different theme or facet, under a broader topic. It’s like breaking down a broad query into subtopics and giving each subtopic its own horizontal list. For instance, a search for a famous person might show a section like “Songs”, “Albums”, “Movies” each as a separate carousel if that person is a multi-talented artist. Or searching something like “Elon Musk tweets” (example from Google’s documentation) might show multiple carousels categorized by topic or time. Another example: searching a broad category like “dinner recipes” might yield multiple carousels such as “Chicken dinner recipes”, “Vegetarian dinner recipes”, etc. Essentially, multi_carousel = a set of illustrated search suggestions grouped by categorydataforseo.com. Each carousel is an array of related items, and together they cover multiple angles of the query.

SEO/Visibility impact: Multi-carousels take up a lot of real estate. They can dominate the results page, especially on mobile where you scroll through each. If Google thinks a query is broad, they might push lots of these categories before even showing normal results. For SEOs, this means the user is being encouraged to refine their query via those categories instead of clicking your general page. It segments the traffic. On the other hand, if you have content that fits into those specific categories, you’ll want to rank when the user clicks on one of those carousel items (since each typically leads to a new query). For example, if “Athletes from Spanish-speaking countries” is a carousel category for a broad sports querydataforseo.com, and your site has content about famous Spanish-speaking athletes, you’d aim to appear when that becomes the active query. Multi-carousels basically telegraph what the sub-intents of a broad search are. They’re telling SEOs: “People searching X might actually want one of these Y or Z categories.” If you notice a multi-carousel for an important keyword, consider creating targeted content for each subtopic if relevant. From a brand perspective, multi-carousels can be a barrier – the user might never see your generic page about the broad topic because they’ve immediately dived into a subtopic. So to capture them, meet them in that subtopic. It’s like needing content one level deeper in the funnel. Additionally, each carousel item might have an image and title – these often come from other sources (like an image from a site, but not necessarily credited clearly). It’s hard to directly get your branding into those, except via having recognized entities on your site or structured data.

AI overview interaction: Multi-faceted topics are exactly what AI summaries are getting better at handling. Google’s AI could present a structured answer that covers multiple aspects (in paragraphs or bullet points) instead of multiple separate carousels. For instance, instead of showing “NBA players” and “Athletes from Spanish speaking countries” as carousels for a sports querydataforseo.com dataforseo.com, an AI answer might say “Results for your query span multiple areas: one aspect is NBA players like A, B, C; another aspect is international athletes such as X, Y, Z.” That’s essentially the AI giving a multi-part answer. This could diminish the need for Google to use a multi-carousel UI, since the AI can integrate the subtopics in one coherent response. On the other hand, Google might choose to maintain some visual separation – possibly the AI could even output something like a list of categories with examples (functionally similar to multi-carousel but in text). If the AI becomes the main way to navigate broad topics, multi-carousels might appear less often for those using AI. However, not all users will engage with AI, and some queries might still lend themselves to the classic interface. For SEOs, the underlying challenge remains: broad queries require broad coverage. With AI, to be included, your content might need to cover multiple subtopics (or one of them really well). It’s possible the AI might cite different sources for each subtopic – which means being the authority on a specific subtopic could get you cited even if you don’t cover everything. In contrast, the current multi-carousel forces a user to pick a path. AI might attempt to satisfy all paths at once. If that happens, some of those subtopic queries may see less search volume (because the AI answered them without the user explicitly searching). For example, a user might not click “Athletes from Spanish-speaking countries” carousel because the AI already mentioned a couple in the main answer. As such, traffic that would have gone to the second-step queries might drop. It’s complex, but the key is AI aims to reduce extra searching. Multi-carousel exists to encourage extra searching. So they are somewhat at odds. We might see either one or the other dominating a given result page, but likely not both heavily at the same time.

Trackability: No direct tracking for the carousel itself. Like the single carousel, you can’t see “your site was in multi-carousel.” It’s purely a SERP UI element. You can track whether a query triggers this feature. If you rank for one of the subtopic queries that a carousel leads to, that’s normal tracking (for that subtopic keyword). One thing to watch: if you notice certain subtopic queries suddenly getting more impressions, it might be because users are clicking a carousel that leads to them. There’s no straightforward way to attribute it, but a spike in those could hint at a multi-carousel driving interest.

Images (Image Pack)

What it is: The Images or Image Pack feature is a block of images that appears within the web search results. It’s usually a row of images (or a grid of images) that link into Google Images search for that query. For example, searching “modern kitchen designs” might show a row of image thumbnails because Google guesses you might be looking for visual inspiration. The image pack often has a title like “Images for modern kitchen designs” and clicking any image takes you to the Google Images results page for that query (or directly opens the image viewer). The images displayed are essentially the top results from Google Images for that query. This feature is common for queries with a visual intent – e.g., product searches, travel destinations, fashion, art, etc. As one description notes, images can be displayed as a separate block for many queries that can be illustratedseranking.com.

SEO/Visibility impact: When an image pack appears, it’s a clue that visual content matters for that keyword. If you have compelling images (properly optimized with alt text, etc.) on your site that rank in Google Images, you could be featured here. If your image is one of the few shown in the pack, it’s a great visibility boost; users might click it and then eventually click through to your site from the Google Images viewer. However, a lot of image searches result in the user just browsing through Google’s image results without necessarily clicking to the source page (especially after Google changed the interface to allow high-res previews). So while being in the image pack can drive some traffic, it’s not always a ton – it’s somewhat analogous to a featured snippet but for images: it gives a quick answer (in this case a visual answer). Still, for certain industries (e.g. e-commerce with product photos, travel with destination pics), image visibility can translate to brand awareness and some referral traffic. From an SEO standpoint, to optimize for image packs you should focus on image SEO: use descriptive filenames, alt attributes, captions; ensure images are relevant to the topic; and ideally get them on a page that itself is relevant to the query. Also, using schema like ImageObject might help, and making sure your images are accessible to Google (not lazy-loaded in a way Google can’t see, etc.). Keep in mind that images can also appear in featured snippets sometimes, and Google might take an image from one site and text from anotherseranking.com, so having high-quality relevant images could get you into multiple SERP features. If an image pack is present, it does push one or two organic results further down. It’s typically mid-page or top. Users who specifically are looking for visuals will likely click it. So ensure that if that’s an important keyword, you have a presence in Google Images for it.

AI overview interaction: An AI overview might incorporate images in the future (currently, Google’s SGE is mostly text with maybe some small images or icons). If Google decides to present images alongside the AI summary (for instance, showing a photo for a location being described), that could either complement or replace the need for the separate image pack. Or the AI might not handle images at first, and the image pack will remain a distinct element for visual queries. Over time, it’s plausible the AI could say “Here are some examples” and show a few images with captions as part of the answer, citing the sources. If that happens, it’s effectively moving the image pack into the AI section. If not, the image pack will still appear where it normally does. In either case, image optimization remains important – if AI uses images, it will likely use ones that Google Images considers high-quality and relevant (so the same factors that get you in the image pack). Another point: if the AI gives a thorough answer, a user might not scroll further to see the image pack, unless the query inherently demands visuals (like “show me designs…”). Possibly, Google might trigger AI less for queries where visual browsing is important, sticking to the traditional image pack. For SEOs and marketers, continue treating image SEO as a parallel track. Even in an AI world, people will want pictures; the mediums will coexist. If anything, as AI generates more content, original images might become a differentiator for human-created content. Also, note that Bing’s AI (for example) will often include images in its answers – if Google follows, they might draw on Google Images index for that. You’d want your images to be among those the AI could pick (i.e., rank well in images search).

Trackability: Partially. Google Search Console has a separate section for Google Images impressions and clicks. If your image appears in an image pack on web search, that counts as a Google Images impression (if the user clicked “Images” or if the image result was served via web?). Actually, it might count in the web results too as an impression for that page if the user then clicks to your site? This is a bit unclear. Typically, Search Console’s Performance report lets you filter by “Search type = Web” vs “Image”. If you get traffic via an image search or image pack click, it might show up under “Image” search type. It won’t show as a normal web click because the click technically goes to Google Images first. Once on Google Images, if they then click “Visit page”, that’s a referral from images. So you might need to look at your analytics referrers (they’ll show something like google.com as referrer but possibly with something indicating it was from images). Some SEO tools can tell you if an image from your site is in the pack, but it’s not as straightforward as tracking a web ranking. In short: you can see how your images perform (impressions, clicks) via the Google Images search type in GSC. But you won’t get a simple “Position in image pack” metric on the web search. If image search is important, check those GSC stats and optimize accordingly.

Video Results (Video Thumbnails)

What it is: Google often includes Video results in the SERP, especially for queries that imply the user might want a video tutorial, music video, or other video content. These can appear as a special Video carousel (multiple videos you can scroll) or as individual results with a video thumbnail. The most common is a video carousel with three videos shown (from YouTube or other platforms), often titled “Videos”. Each item shows a thumbnail image, the video title, the source (e.g., YouTube.com), duration, and sometimes the upload date. Google might also show a single video result within the organic listings with a thumbnail, particularly if one video is very relevant (like a how-to video for a how-to query). These stand out because of the thumbnail. It’s mentioned that the video feature adds a thumbnail video to search snippets, usually from YouTube or big video sites, with details like duration and uploaderseranking.com.

SEO/Visibility impact: Video results can be highly engaging – users are often drawn to the thumbnail. If you have video content, the dream is to have your video appear in that carousel or as the featured video result. YouTube videos dominate here, given YouTube is Google’s own and heavily crawled. For a marketer, this means consider investing in video content for topics where videos are popular. For instance, if “how to tie a tie” has video results, creating a video might give you a chance to appear. If you already have a high-ranking page, adding a video (and marking it up with VideoObject schema) can sometimes get a thumbnail next to your result or get you into the carousel. When your video appears, it can channel traffic either to YouTube (if the user clicks and watches on YouTube) or to your site if the video is hosted and indexed from your site. Keep in mind, a user might get their answer just by watching the video on YouTube and never visit your site (though you might have branding in the video or a link in description). So, one SEO approach is to use YouTube as a vehicle for traffic: publish videos there with links to your site in the description, etc. As far as organic competition: video results take up space, but they are counted among the 10-ish results sometimes (like a video carousel might be in position 3 pushing others down). If you don’t have video content and the SERP is full of videos, you might struggle to get clicks even if you rank, because many users will prefer the video. Also note, Google sometimes features a key moment (chapters) from videos directly on SERP (with a timeline showing segments) – enabling that by adding chapters to your videos or letting YouTube auto-chapter them can enhance how your video is displayed. In short, for any query where a video can answer the query effectively, consider that part of SEO is maybe video SEO.

AI overview interaction: If Google’s AI overview can provide step-by-step instructions or detailed explanations, it could reduce the need for some “how-to” video clicks. For example, if someone asks “how to tie a tie” and the AI outlines the steps clearly, maybe fewer people will click the videos. However, for many, a visual demonstration (video) is still preferable. AI can’t easily replace the actual footage of doing something (yet). What it might do is summarize what videos cover. It might even cite a video or offer to play a clip (this would be advanced, but perhaps “here’s a relevant part of a video that shows it”). Google has already integrated some features like showing specific video moments for “how to” queries (e.g., linking to the exact timestamp in a YouTube video where the step is shown). AI could make that more conversational (e.g., “Here’s a video demonstration of step 3”). If AI starts pulling content from videos (like transcribing and summarizing), that content could appear in the overview. But then likely it would still point users to watch the video for full detail. As a marketer, you’d want your video to be the one the AI suggests (which probably means it’s a top-ranked video anyway). Also, AI might show fewer video carousels if it thinks its text answer suffices. It’s query-dependent: something like “listen to cat sounds” – a user likely wants a video or audio, not an AI description of it. So video (and audio) content will still hold unique value. AI might even incorporate multimedia eventually, but that’s a different kind of result. We should also consider that AI might provide an answer and the user might then specifically ask the AI, “Can you show me a video of that?” – not sure if that’s in scope, but conceivably the AI could then highlight a video (maybe even play it in a future UI). If so, being the chosen video would be great, but how to optimize for that remains to be seen (likely similar to regular video SEO: relevance, popularity, schema). For now, anticipate some loss of text traffic for how-to queries, but video content likely remains sought after. So having both text and video content covers both bases – if AI steals some text clicks, maybe your video still gets them or vice versa.

Trackability: Yes, partially. If your video is on YouTube, you track performance via YouTube analytics (for views, etc.) and maybe see indirect traffic to your site from the video description. If the video is on your site, Search Console can show if your page appeared with a video thumbnail (under “search appearance” you might see “Video” or if you filter by rich results). Also, Google has a Video indexing report in GSC that tells you which videos on your site are indexed and if they’re appearing. If a query triggers a video carousel and your video is in it, that counts as an impression for your video page (likely). It might appear as a rich result in GSC. There’s also a filter in GSC Performance for “Videos” (search appearance). Use that to see clicks/impressions when your results had a video feature. In third-party rank trackers, they sometimes list if a video result is present and if it’s your video (especially if it’s on YouTube, they might not tie it to you unless you specify). So tracking is a bit segmented: track your YouTube separately and your website’s video snippets separately.

Twitter (X) Carousel

What it is: Google sometimes shows a Twitter carousel (now technically X carousel, since Twitter rebranded to X) for certain queries, especially those related to trending people, hashtags, or events. This feature displays the latest tweets (posts) relevant to the query, often in a horizontal scrollable format. It’s like an embedded feed of Twitter results on the SERP. For example, searching a celebrity or a conference might show their recent tweets or tweets mentioning them. Each item in the carousel shows the tweet text, who posted it, and the timestamp. The carousel can be interacted with – you can scroll to see a few of the latest tweets and click on one to go to Twitter. A few years ago, Google and Twitter made a deal that allowed Google to index tweets in real-time, which is why Google can show recent tweets for many queriesseranking.com. The partnership means Twitter content is directly piped into Google results for relevant searches.

SEO/Visibility impact: From a pure SEO perspective, you can’t optimize your site to appear in the Twitter carousel – it’s pulling from Twitter’s data. However, it’s a social visibility consideration for marketers. If your brand or executives are active on Twitter, their tweets could appear in search results for your brand name or related topics. That can be a good thing (it shows you’re engaged and up-to-date) or a bad thing (if the tweets are off-message or there’s negative sentiment trending). It’s part of your search presence. For example, if someone searches your company during a live event you’re hosting, seeing your latest tweets about it right on Google could engage them or provide timely info. For individuals (like authors, celebrities, politicians), their latest takes being visible can influence what searchers think. In terms of click-through, a user interested in real-time discussion might click a tweet, which takes them to Twitter (X) – not to your site. So in one sense, it can divert traffic away from websites to Twitter. On the other hand, if your tweet references an article or includes a link, a user might eventually follow that. But the SERP feature itself mainly keeps people on Google briefly to scan the tweets. One practical effect: it can push organic results further down, which might include your site. So let’s say you rank #1 for your brand, but above it there’s a Twitter carousel with three recent tweets about your brand – users’ eyes might go there first. You’d want to ensure the content there is positive or useful. Marketing strategy: Stay active on relevant social discussions, especially on X/Twitter, if you want to capture some of that SERP real estate. Also, if a big news story or trending topic relates to you, be aware that what people are tweeting can show up on Google – traditional SEO can’t control that, but your PR or social team might influence it through engagement or statements on Twitter.

AI overview interaction: For timely, conversational queries, an AI overview might not be as current as the live tweets. Twitter content is real-time; AI models (unless connected live) may not incorporate the latest posts by the second. However, Google’s SGE does have some near-real-time capabilities, but it’s not clear if it would summarize social media sentiment yet. Possibly, if someone asks, “What’s the latest on X topic?” the AI could say “As of today, people on social media are saying…” but that might be risky for accuracy. I suspect that for now, Google will continue to show the Twitter carousel separately for real-time context. The AI overview might coexist, giving a summary of news while the tweets show reaction. If the AI does begin to integrate live content, it might pull in tweets (maybe quoting a relevant one in the answer). But handling the firehose of Twitter in an AI answer might be challenging (moderation, etc.). Another angle: The AI might reduce the need for some users to scan tweets if it summarizes the consensus or main info. But a lot of users enjoy reading actual tweets for tone and nuance. So the Twitter carousel likely remains valuable for engagement and real-time info that an AI can’t fully replicate yet. From a marketer perspective, I’d still treat the Twitter carousel as something mostly separate from AI – i.e., keep your social media presence strong so that whether a user interacts with AI or not, your voice is present. If AI one day decides to quote social media, having authoritative or popular posts could get you mentioned (imagine an AI summary saying “<Celebrity> even joked about it on X: [quote tweet]”). It’s not impossible. At present though, the biggest effect of AI might be that it pushes the Twitter carousel further down if the AI box takes top spot. That could slightly reduce its visibility unless the user scrolls. So time will tell if those social carousels are as prominent.

Trackability: Not in your usual SEO tools. The Twitter carousel is not something you’ll track in GSC or your site analytics (unless a tweet drives traffic to your site). You might monitor it manually for certain queries. If your own tweets are appearing, you can measure their engagement on Twitter itself, but Google doesn’t tell you “X impressions via Google SERP”. It’s more about awareness. There are social listening tools to track mentions etc., but specifically for Google appearance, you just have to see it with your eyes or use a SERP tracker that notes “tweets are present”. If a tweet contains your site link and someone eventually visits, it would show as a referral from Twitter in analytics, not as organic search.

Google Reviews (Reviews in SERP)

What it is: Google Reviews generally refers to the star ratings and review information that appear for businesses or products within certain SERP features. For example, in the local pack or knowledge panel for a local business, you’ll see a star rating (averaged from Google user reviews) and the number of reviews. In product carousels or shopping results, you might also see star ratings aggregated from various sources (including Google Shopping reviews). The term “google_reviews” in a SERP context likely points to the reviews section in a local knowledge panel or an expanded reviews snippet. For instance, if you search a specific restaurant, the knowledge panel on the right (or top on mobile) will show something like “4.3 ⭐ (256 reviews)” and maybe some review snippets. If you click it, you get more Google Maps reviews. In short, whenever Google is displaying rating info from its own review platform, that’s a Google Reviews feature. This isn’t something that appears standalone usually; it’s part of other features (Local Pack, Knowledge Graph for businesses, etc.). It might also refer to the small excerpts of reviews that show up (like three summary quotes of what people say about a place).

SEO/Visibility impact: Reviews (especially star ratings) are highly eye-catching. A business with a good rating might attract more clicks or interest. In local SEO, managing your Google reviews is crucial because those stars show up right in the search results for your business. High rating and volume can improve trust. Even outside of local, star ratings can appear for things like recipes or products if rich snippets are enabled (though those might be from schema and not labeled “Google reviews”). But since the feature is specifically named “google_reviews”, think local/business context. If your business listing has poor reviews, that will be very visible on the SERP – potentially hurting click-through or leading a user to choose a competitor in the local pack. Conversely, great reviews can be a selling point. For strategy: Marketers should actively manage and encourage positive Google reviews for their businesses. This means good customer service, asking satisfied customers to leave reviews, and responding to negative ones. While this crosses into local SEO/Google My Business optimization more than traditional on-site SEO, it’s a vital part of your overall search presence. Also, note that Google may show a blurb like “People often mention coffee” or highlight keywords in reviews. If those are positive or relevant, great; if they highlight negatives, that’s tough. If you’re an SEO for a local client, you might not directly handle reviews, but you should absolutely bring it up because it affects how the business appears on SERPs. Outside of local: For e-commerce, Google has reviews in the Shopping results (like star ratings aggregated). Those can influence click-through for your product ads or listings. Ensuring your products gather reviews (via Google Customer Reviews or other programs) can help those stars show up.

AI overview interaction: If someone asks an AI, “Is Restaurant X good?”, the AI might very well incorporate Google Reviews info: e.g., “It has a 4.3 star rating based on 250 reviews, with many praising the coffee but some saying service is slow.” The AI overview could summarize the sentiment of reviews – something an algorithm can do by parsing review text (Google’s already doing simple versions of that with phrases like “people mention [aspect]”). This means AI could directly use user-generated content from reviews in its answers. For the business, that means the narrative users have written in reviews could be distilled and broadcast by AI. It’s even more critical to have a good reputation because the AI might emphasize either positive or negative consensus. On the SERP, the knowledge panel with reviews might be less needed if the AI states “It’s highly rated on Google and Yelp” etc., but Google might still show it for completeness. Also, if the AI does the summary, fewer people might click “read all reviews”, reducing visibility of individual opinions (both good and bad). It could streamline user decision-making (“The AI says generally good, so I’ll just go there”). For product reviews, similarly, AI might say “This product has an average of 4 stars; common pros are X, cons are Y” gleaned from Google’s review corpus. That could cut down the need for a user to scroll through reviews or even click multiple review sites – again underscoring that the aggregate opinion is what matters. For SEO, while you can’t SEO your way into better reviews, you must align your business/product quality and customer feedback, because AI will likely expose any disconnect (if you have issues that many mention, AI will note them). Also, data retrievability: the user prompt mentioned only organic, paid, featured snippet, local pack return results data. Google reviews info is part of local pack/knowledge panel, but not something that an SEO rank tracker “counts” as a result position. So track it indirectly (monitor rating count).

Trackability: Indirect. You won’t see anything in Search Console about your star rating or reviews count. But within your Google Business Profile dashboard, you can track number of reviews, your average rating, etc. And obviously you can just search your business and see the rating show up. There are APIs (like the Google Reviews API mentioned in DataForSEO docs) to fetch reviews, but that’s more for analysis, not something like a ranking position. So measure success here in terms of rating improvement and review count. In terms of SERP presence, if you improve from 3.5★ to 4.5★, you’ll likely see an increase in conversion (more clicks, calls, etc. from the panel), but Search Console might not easily tell you that. You might infer it from more branded search clicks or from Google My Business insights (they report on actions on your listing). For product ratings in search, if using structured data, Search Console has a Rich Results report that shows if your review snippets are valid, etc.

Local Pack (Map Pack)

What it is: The Local Pack (a.k.a. the “Map Pack” or “3-pack”) is the set of usually three local business listings that appear for queries with local intent (e.g., “pizza near me”, “bookstores Belfast”). It typically shows a small map and three business names with their review ratings, address, phone (or other quick info like hours), and sometimes an image. Each listing may also have a “Website” link or a “Directions” link. Clicking on one or “More places” opens a larger list in Google Maps or the Local Finder. The local pack is powered by Google’s local index (Google Business Profiles). As the DataForSEO guide describes, the local pack’s aim is to give necessary info about local establishments (name, phone, address, hours, rating, and location on map) in a compact formdataforseo.com. It’s one of the most prominent SERP features for local searches.

SEO/Visibility impact: If you are a local business or serve specific locations, appearing in the local pack is arguably more important than regular organic results for local queries. Being one of the top 3 means you have high visibility, likely capturing a large share of clicks or calls (especially on mobile, where users might tap to call or navigate). If you’re not in the 3-pack, you’re essentially “below the fold” for local, because a user would have to click “More places” to find you. Local pack ranking is influenced by different factors than organic SEO – primarily proximity, relevance, and prominence (which includes reviews). SEO strategy for local pack involves optimizing your Google Business Profile: ensure NAP (name, address, phone) consistency, choose proper categories, include keywords in your business description (but naturally), gather lots of positive reviews, and build local citations. Also, good engagement on your listing (photos, posts) can help. If you’re an SEO managing a brand with physical locations, local SEO is key to getting into this feature. For marketers without a physical presence, the local pack can be a competitor if local businesses take attention away from general results. For example, a national e-commerce site might lose clicks on “buy shoes” queries in certain cities because local packs show shoe stores. That’s something to be aware of; maybe you’d adjust by adding “online” or focusing on non-local terms. For those in it, the local pack info like ratings and address is visible – you want those to look good (accurate info, high rating). It’s also a “zero-click” zone sometimes: users might get what they need (like see you’re closed now) and not click anything. So ensure info is complete to convert that impression into an action.

AI overview interaction: For a query like “best pizza near me”, an AI might conceivably try to answer with something like “The top-rated pizza places in your area are X, Y, and Z according to Google Maps, with ratings 4.7, 4.5…” – essentially replicating the local pack in text. Google’s SGE might incorporate local suggestions (though in tests, local queries often still show the map pack prominently rather than an AI paragraph). It’s likely Google will keep the map and pack interface because it’s very useful and interactive (and monetizable with ads in maps). The AI could supplement by summarizing “People say X about this place, Y about that place” gleaned from reviews. That would be new – like a meta-review. Already, one can ask Google’s Bard or Bing Chat “which is the best [type of business] near [location]?” and they’ll often list a few with some details. So AI can do it. But within the SERP, Google might not replace the visually rich local pack with plain text; they might integrate it. Possibly the AI could highlight one or two (“Based on reviews, Luigi’s Pizza is very popular for its authentic taste…”) which might even bias the user towards that one choice – could be powerful. We’ll have to see if they combine them. For now, assume the local pack stays, and AI might either not show for such queries or appear alongside. If AI does encroach, the same local SEO factors remain – the AI will pull from the same data (ratings, etc.). So continuing to have great reviews and complete info ensures the AI “speaks well” of you if it does mention you. Data retrieval: local pack actually returns data in structured form via APIs (as shown in DataForSEO exampledataforseo.com dataforseo.com). Only organic, paid, featured snippet, and local pack were noted as returning results – meaning you can programmatically get the names/links of those. Indeed, local pack items can be tracked (like rank 1 in local pack). Many rank trackers do track local pack presence separately.

Trackability: Yes, in local SEO context. Google Business Profile provides insights (how many views your listing got in search vs maps, how many actions etc.). In Search Console, your website might not show those impressions because the local pack isn’t exactly an organic impression for your site – unless your website is linked and user clicks it (then it would show as a click from query maybe, but actually often it might show as direct or referral traffic because the click goes through Google redirect). There is a bit of ambiguity how GSC counts local pack clicks – often it doesn’t. You might see some branded queries in GSC if people search your name and click the site from the panel. To truly track local pack, specialized tools or Google’s own Business Profile dashboard is used. Additionally, you can use third-party local rank trackers which tell you your position in the local pack. The “organic” rank tracking won’t fully capture that because the local pack is a separate entity. Some SEO tools treat being in the local pack as a separate metric. So yes, track it via local SEO tools. You can manually check by searching in the target area (or use tools that simulate that). The user’s note about “only organic, paid, featured_snippet, local_pack return results” likely means those are the ones they can extract with their tools – local pack does return a list of business results that can be parsed, which is trackable in that sense.

Map (Google Map on SERP)

What it is: Sometimes, Google will display an actual map snippet on the search page. This usually accompanies the local pack – often at the top of the local pack or to the side of it. On desktop, you might see a small map on the right side when a local pack is triggered, showing pins for the three businesses listed. On mobile or certain layouts, a small map might be at the top of the local results block. It’s interactive – you can click it to go to Google Maps. There are also cases where a user query explicitly triggers a map with directions (like if you type an address or “map of [something]”). The description given in one article: “The Map appears at the top of the SERP for a specific geographic query, allowing people to see Google Maps without leaving the SERP”seranking.com. You can interact a bit, like zoom or switch modes, but mostly it’s a visual reference.

SEO/Visibility impact: The map itself doesn’t list additional info beyond the pins and maybe a few labels, but it enhances the presence of the local pack. It grabs attention (visual element). If your business is one of those pins, that visual indicator can help – some users might click directly on the pin or the label on the map, which effectively is another way to reach your listing. However, you can’t optimize to “rank on the map” separate from ranking in the local pack – it’s tied together. The map can also occupy a chunk of space, possibly pushing organic results further down (especially on mobile where it might be big and scrollable). If you’re not one of the businesses, the map doesn’t directly help you; it may draw users toward the local options instead of perhaps the organic results (for example, someone might have clicked an organic Yelp link, but the map drew them into exploring the Google map listings instead). For businesses, being on the map is good but it’s a byproduct of being in the top local results. One specific instance: queries like directions queries or queries like “New York to Boston” might show a map with driving directions – not directly SEO for a site, but if you’re say a transit provider or something, your info might be on a panel. But those are rare cases. Another instance is queries like “restaurants on map” or when using the map view filter from mobile, but those are more user actions than static SERP features.

AI overview interaction: An AI answer might provide location-based info in text form (“The closest X to you is Y, located at 123 Street”). But an AI text can’t fully replicate the utility of a map for someone who actually needs to see where things are or wants to make a spatial choice. Likely, the AI will still defer to the map for full interaction. Perhaps the AI can summarize (“There are 5 coffee shops within 1 mile, here are the top rated”), but the user might then click into maps anyway to see exactly where or get directions. So I suspect the map feature isn’t going away. If anything, AI might integrate with maps more (like Google Assistant already can, “show me on map”). For now in SGE, local queries often just show the map pack and map as usual, sometimes an AI isn’t even given for such queries. Possibly due to trust and real-time data issues. So local is one area where the traditional SERP features might remain quite intact alongside AI. If AI does present something like “I found these places: [names]”, Google would still probably display the map or at least a link “View on map” because users will want it. For SEOs, focus on the standard local SEO to appear; AI won’t change that much immediately aside from summarizing reviews as noted.

Trackability: Not directly trackable. The map is part of the local pack element. If you track local pack presence, that covers it. You can’t track an impression on the map separate from the local pack listing impression. Google Business Profile insights will tell you how many times you were shown in search vs in maps. A search SERP map view likely counts in the “search” column if your listing was in the 3-pack, whereas if someone opened Google Maps fully, then it’s “maps” view. That segmentation exists. So if more people click the map and browse there, you might see some differences in those numbers. But from the SERP perspective, the map is just a component. The user-provided note indicates local_pack returns results; the map itself doesn’t return separate “results” – it’s part of that. Rank trackers note if a map is present but you don’t have a “rank” on the map image aside from your local pack rank.

(Note: We already covered People Also Search For in the context of PASF after clicking a result. However, there is another feature sometimes confusingly named similarly. Possibly the “people_also_search” in the list refers to a specific carousel of related entities that sometimes appears, not the PASF box. But given we addressed PASF, this section can focus on any remaining interpretation or skip to avoid duplication. Since our list had both people_also_ask and people_also_search, likely one is PAA and one is the PASF we did. We’ve done both PAA and PASF. Another possibility: DataForSEO described “People also search” differently (it sounded like a list of items at bottom providing answers which was odd). It might actually refer to a carousel of related people or entities that appears in some knowledge contexts. For example, if you search a famous person, you often see a “People also search for” carousel of other famous people at the bottom of the knowledge panel. That is an entity carousel. Perhaps that’s what DataForSEO meant by “People also search element… appears in bottom area providing short answers to questions” – though that sounded off. However, since we thoroughly covered PASF as triggered on click, let’s consider this feature as the “People also search for” carousel that appears with knowledge panels. It’s often images of related entities, not Q&A. It’s basically a special case of carousel (which we did generically). But let’s clarify it for completeness.)

What it is (alternate view): Sometimes under a Knowledge Graph panel for a person, book, movie, etc., Google will show a horizontal carousel labeled “People also search for”. It contains other entities (with their images or icons and names) that are related. For example, searching an actor might show a carousel of other actors or directors that people also search for. Clicking any of those takes you to that entity’s results. This is not triggered by user behavior (not the back-button thing), but rather it’s part of the initial results page for an entity. It’s essentially another form of related search, but for known entities. In DataForSEO’s taxonomy, they might call this mention_carousel or people_also_search, but given they listed mention_carousel separately, likely this is the people_also_search element they described (though their description sounded like short answers, which is confusing). Nonetheless, it is a feature.

SEO/Visibility impact: If you are, say, the official site or a fan site of one of those related entities, you could benefit when people click that entity. But generally, this carousel doesn’t include any content from your site; it’s just linking to other searches. For a brand, if someone searches your brand and sees “People also search for [competitor brand]” in a carousel, that might lead them to check out competitors – not great. That “People also search for” carousel appears often when someone finds a knowledge panel of one item and might want alternatives. It’s common for products or companies (e.g., search a software, see others in same space). As a marketer, you can’t stop it from showing competitors, but you can be aware of who shows up there (that’s your competitive landscape). Sometimes, through branding, marketing, and differentiation, you can influence what users search – but not directly this feature. It’s more of a user guidance thing. No direct SEO tactic to appear there aside from being a commonly associated entity with others (which is more about user behavior and how things are connected in the Knowledge Graph). For content sites, not much to do here either, except perhaps to optimize your entity presence so that if your entity is searched, you have a knowledge panel and you possibly show up in others’ “people also search for” if appropriate.

AI overview interaction: If the query is an entity that triggers a knowledge panel and this carousel, the AI overview might incorporate information about related entities in a narrative way (like “X is similar to Y and Z in these ways” or “People who look up X often consider Y” etc.), but that’s speculative. More likely, the AI gives info about the queried entity and maybe suggests “If you’re interested in alternatives, you could search for [list]” – though I haven’t seen that yet. The current UI tends to still show those carousels even if an AI result is present. In fact, that “People also search for” entity carousel is a staple of knowledge panels; the AI doesn’t really remove the knowledge panel or its parts (at least currently, the knowledge panel might still show on the right side). So likely those related entity suggestions remain. Perhaps the AI could answer a follow-up like “How does X compare to [related entity]?” but it wouldn’t automatically go there unless asked. So minimal change. Possibly less use if the user is satisfied with the one entity description and doesn’t explore, but many will still explore.

Trackability: No. Like other purely navigational suggestions, there’s nothing for your site to track unless it leads to a query where your site ranks. It’s something to monitor manually for brand queries to see who Google links you with. Marketing teams might track brand affinity by seeing what else users search (for example, Google Ads or Trends data might show “people who search X also search Y”), but that’s not in Search Console. So this is more about knowledge graph analysis than SEO metrics.

(If needed, skip detailed since we covered similar in Carousel and PASF. But since the list explicitly had it, we needed to clarify differences.)

(We already covered this above in its own section, which might suffice. If needed, we ensure it's clear that "related_searches" is the bottom-of-page suggestions, which we did.)

(We might skip rewriting since it’s done, but just ensure our explanation encompassed point 1-4 which it did.)

Mention Carousel (Mentioned In...)

What it is: The Mention Carousel is a relatively new feature Google shows, especially for product queries or “top X” queries. It is a horizontal list of products or items, each with some basic info (name, price, rating), and underneath each item, it says “Mentioned in [Source1]… [Source2]”. Essentially, Google curates a list of products and shows which trusted review sites have mentioned each product. For example, for a query like “best security cameras 2025”, Google might show a carousel titled “Top 16 Surveillance Cameras” with each camera model as a card, and below each model’s name it shows sources like “Mentioned in CNET and Wirecutter”dataforseo.com dataforseo.com. This tells the user that these items were recommended or discussed in those reputable articles. Clicking an item often triggers a new search or a knowledge panel for that product. This feature is Google’s way of answering “best” queries by aggregating multiple review lists from across the web, rather than just showing one site’s list.

SEO/Visibility impact: For affiliate marketers or anyone who creates “best X” lists, this feature is disruptive. Instead of the user clicking through to your blog “Top 10 cameras”, Google may extract the cameras you mentioned and present them in this carousel. The user might then click directly on a camera to see its details (maybe see shopping options or specs), bypassing your site. However, your site does get a sort of credit – its name appears as a source under the product if your article mentioned it. In our example, “Arlo Pro 2 – Mentioned in reviews.org and Safety.com”dataforseo.com. If the user clicks the source name, sometimes it might bring up that article snippet (or if they click the product, they might eventually see those sites listed as references). But the credit is subtle – many users might not click through. So while your content influenced the carousel, traffic can be diverted. On the other hand, being one of the mentioned sources is a mark of authority. If a user notices your site name consistently appearing as “mentioned in” for several products, they might seek it out. But that’s indirect. Strategy-wise, to get your site’s content utilized by this feature, you need to produce high-quality roundup reviews that Google trusts. That means comprehensive lists, maybe using schema (though Google likely uses NLP to parse). It appears Google favors well-known review sites (CNET, Wirecutter, etc.) for populating this, but smaller sites can appear (like Safety.com in the example). If you can’t beat Google at this game, you might adapt: aim queries they aren’t doing this for, or ensure your brand is strong so users recognize it. Also, consider focusing on long-tail queries not captured by such features, or provide unique insights that a generic carousel can’t show. But overall, it’s a sign of Google keeping users on SERP by synthesizing multiple sources. For an e-commerce brand, if your product appears in such a carousel (i.e., people wrote about your product in “best of” lists), that’s good exposure, and you should ensure your product info is correct (price, etc., often Google shows an approximate price). But the user may then search your product specifically after seeing it.

AI overview interaction: The mention carousel is very similar in spirit to what an AI overview could do for a “best products” query: aggregate multiple sources and give a summary or list. In a way, the mention carousel is a structured approach, whereas an AI could produce a narrative like, “The best security cameras are A, B, C. A was recommended by CNET for its image quality… B was highlighted by Wirecutter for ease of use…” This might even be more user-friendly than the carousel. So, I suspect that AI overviews will likely replace or heavily modify these mention carousels for broad “best” queries. If Google’s SGE can synthesize the consensus of multiple review articles, it can present a ranked list or a few top picks with reasoning. That’s essentially what a mention carousel offers, but AI could do it in sentences. However, Google might still show links or a mini carousel within the AI answer for completeness. Hard to say. For SEOs, this means the same thing: whether it’s mention carousel or AI summary, Google is layering an extra step between your content and the user. So the key is to be one of the sources the AI or feature draws from. That means creating authoritative, well-structured content that clearly identifies the top picks (so Google can parse it). Also possibly using structured data like FAQ or item lists might help Google understand your content. Another thought: if AI provides a summary, it might still list some sources (like “according to Site A and Site B”), in which case having your site name drop in that context is valuable. It might even link to you, similar to how it cites in other answers. So the focus remains on being the go-to source that feeds these aggregated answers.

Trackability: Not directly, beyond normal rankings. The mention carousel doesn’t count as a traditional result for your site. Your site’s link might not even appear on the first page (the carousel is effectively replacing your site’s listing). If a user clicks your name in “mentioned in”, that might not even navigate to your site – it might just show info or a search for your site. (In tests, clicking the source name often just triggered a search for that source and product, not directly opening it, which is odd.) You’d primarily notice this feature by monitoring the SERP manually. You might see a drop in traffic for “best X” keywords even if you’re still technically ranking, because users interact with the carousel instead. Search Console might show your page’s average position dropped (maybe because it’s now on page 2 or the “mentioned” not counting), or even if it’s page1, CTR could drop. But it won’t specifically tell you “we showed your site as a mention but not a normal result.” Some SEO tools are starting to note when content is used in features like this. But the best “tracking” is to observe if your referrals for those queries drop when a mention carousel appears. It’s an area where SEO metrics aren’t straightforward – you might rank #5 organically (which normally is okay), but Google didn’t show the organic #5 at all because it put a carousel there. Such nuances might not be captured well in GSC (if your impression wasn’t served, it might not count an impression at all). So track your keyword positions and actual traffic; if there’s a discrepancy, check if a feature like this is present.

Recipes (Recipe Carousel/Results)

What it is: Recipes is a SERP feature specifically for food recipe searches. It often appears as an expandable recipe carousel or list with recipe cards. For queries like “chocolate chip cookie recipe” or “how to make lasagna”, Google might show a block titled “Recipes” with several recipe results including an image, the recipe name, rating, cook time, and sometimes calories. Users can often filter by ingredients or other criteria right on the SERP. On desktop, it might appear as a horizontal carousel or a vertical list; on mobile, often a swipeable list. When you click one, it goes to that recipe page (or sometimes opens a preview within Google). As per DataForSEO, “Recipes feature is displayed for queries related to food/dishes. It’s an expandable block with recipe cards including image, rating, cook time, and ingredients.”dataforseo.com.

SEO/Visibility impact: If you run a food blog or any site with recipes, this feature is crucial. Google effectively showcases recipe content right on the results page with rich info. To be included, you almost must use structured data (Recipe schema) and have all the details (reviews, cook time, etc.) in your content, because Google uses that to populate the card. A well-optimized recipe with schema, good image, and strong SEO can get pulled into this carousel. That means high visibility and likely good CTR, since users see an appetizing image and might click yours out of the set if it looks appealing or has great ratings. If you’re not in the recipe pack, you might be buried below it. The presence of this feature has largely transformed recipe SEO: it’s not enough to rank organically, you need the rich snippet. Strategy: use Recipe markup, include user ratings on your site (so your snippet shows stars), provide total time, etc. Also, ensure your photo is enticing (as it will show as thumbnail). Many users do compare by rating and time directly in that carousel. If your recipe has a significantly longer cook time than others, a user might skip it. Not exactly SEO, but something to consider (maybe target terms like “slow cook” vs general, etc.). Also, having “x reviews” on your snippet helps (Social proof). A unique aspect: this feature sometimes includes a drop-down to “Show more recipes” or refine by ingredient (“with chicken” or “without nuts”, etc.). If Google can parse ingredients lists (via schema), it may allow users to filter – meaning if your recipe doesn’t meet a filter (e.g., it has nuts and user filters “no nuts”), yours could get hidden. So it’s hard to game that except by being aware of common dietary filters. Another effect: If the recipe carousel satisfies the query, a user might not scroll to see non-recipe results (like articles about the history of chocolate chip cookies). So it captures the audience that wants actual recipe content.

AI overview interaction: An AI overview for a recipe query might do something like: “Here’s a basic chocolate chip cookie recipe: [list ingredients], [brief steps].” That could potentially reduce the need to click on a full recipe. However, cooking queries are often ones where people might still click to get the full details, reviews, tips, etc. Also, recipes involve preferences (some want one with oatmeal, or one that’s vegan, etc.), so one AI answer may not suit all. Google might avoid just spitting out a full recipe because of liability (e.g., if AI gets a measurement wrong, that’s a poor user experience). Instead, they might continue to present the curated recipe cards. Possibly, the AI might complement: e.g., “I found a couple popular recipes, one from SiteA (5 stars, takes 1hr) and one from SiteB (quick 30min version).” This would actually be a nice summary, then user could choose which to follow. If Google’s AI does that kind of summary, it will likely cite the sources (which might actually drive clicks to those sources via the links). But if the AI just gives the actual recipe content, that’s problematic because it’s essentially plagiarizing multiple recipe creators and could hurt those sites’ traffic drastically. Given recipe bloggers are a huge portion of the web ecosystem (and often complain about Google already scraping via features), Google might tread carefully. I suspect the recipe carousel stays, maybe with some AI enhancements (like “this one is the fastest, this one is most reviewed”). From an SEO perspective, continue to focus on being the chosen recipe (which remains structured data, good content, etc.). AI could highlight certain features – like if your recipe is “quick” or “healthy”, the AI might mention that if it deems it noteworthy. So highlighting unique angles in your recipe content (in the description, or title) could make it stand out to both AI and users (e.g., “30-Minute Lasagna” or “Vegan Lasagna” might get picked for a “fast” or “vegan” highlight).

Trackability: Yes, via rich results tracking. In Search Console, there is a Recipe search appearance filter. You can see impressions/clicks when your result appeared as a rich recipe result. Also, the Rich Results/Schema report in GSC will show if your pages have valid recipe markup. Third-party tools might note if you have a rich snippet and your rank. When you appear in the recipe carousel, it usually corresponds to having a high organic rank, but not always – sometimes Google can show more than 10 results by making it a scrollable list. However, DataForSEO output suggests they treat “recipes” as a special element with multiple itemsdataforseo.com. So you would want to track whether your site’s recipes are showing up. The metrics might show increased impressions due to being in carousel even if actual rank was low (because maybe the carousel gave additional exposure). If your site’s recipe is included, GSC counts that as an impression (likely as position 1 or so if it’s in the carousel’s first view). But if the user has to scroll within the carousel to see yours, not sure if that counts immediately or only if scrolled (likely only counts if the carousel is loaded fully, which might be immediately on search). In any case, GSC’s performance data with “search appearance = rich result / recipe” is your friend. Keep an eye on CTR – a good CTR means your snippet (title/image) is attractive.

Top Sights (Things to Do carousel)

What it is: Top Sights (sometimes labeled “Popular attractions” or “Things to do”) is a travel-related SERP feature. When you search for a city or tourist destination (especially with keywords like “things to do in [City]”), Google often shows a carousel of notable attractions, landmarks, or points of interest in that area. Each card typically has a photo, the name of the place, an aggregate rating, and maybe a short descriptor. It’s basically like a mini guide to the city’s highlights pulled from Google’s travel database. DataForSEO describes it as triggered by location queries, showing a carousel of places to visit with name, rating, short descriptiondataforseo.com. Clicking on one usually takes you to a Google Travel page or a new search focused on that sight (sometimes Google Maps info for that sight).

SEO/Visibility impact: If you are in the travel/tourism content business (say you have a travel blog or local guide site), this feature competes with you by giving users a quick list of attractions without needing to click a “10 things to do in X” article. However, the carousel items themselves often don’t answer all a user needs – they might click one to learn more (and at that point, perhaps your site could rank with detailed info on that attraction). For local tourism boards or businesses (like a museum), being listed as a top sight means your attraction is popular enough to be auto-suggested. But if you specifically maintain a site listing sights, users might skip your site and just use Google’s list. It’s similar to the mention carousel logic but for travel: Google aggregates points of interest. The user might choose to use Google’s travel guide rather than an organic blog. For marketers like tourism boards, ensure your attraction has a good presence on Google (via Google Maps listing, reviews, images) because that’s where this info is pulled. If you run a travel blog, you might pivot to providing more detailed info or specialized info not in the basic summary (e.g., “hidden gems in X” or personal experiences). Strategy: accept that basic attraction lists might be answered by Google’s feature; focus on content that either feeds that feature (ensure any descriptions you have on Wikipedia or such are accurate, since Google might use Wikipedia lines in descriptions), or content that goes beyond (like detailed itineraries, offbeat places that aren’t in the “Top sights” etc.). Also, note that top sights often link to Google-owned pages (Google Travel or Maps), meaning zero-click is likely; measure traffic impact accordingly.

AI overview interaction: For a query like “things to do in Paris”, an AI overview can shine: it might list out major attractions with a sentence about each, essentially an AI-curated travel guide. That directly competes with the top sights carousel by providing a narrative rather than just a list of names. It might say, “In Paris, popular sights include the Eiffel Tower (iconic city views), the Louvre Museum (world’s largest art museum), Notre-Dame Cathedral (gothic architecture), etc.” – that’s the sort of summary a travel blog would give. If AI does that, it’s pulling from the same knowledge base, likely listing the same places (Eiffel Tower etc.), but with added details. Google may still show the visual carousel because images are compelling for travel. Possibly both will exist: the AI text plus the image carousel right below it, giving users a quick visual to complement the text. If AI becomes the primary answer, travel websites that rely on those queries might see less traffic because the AI satisfied the user’s curiosity about what the top sights are. However, users planning travel may still click through to get more info such as ticket details, tips, etc. If your site is authoritative (say you have the top Google organic content), the AI might cite you or use info from you (hard to verify, but possible if you have unique facts about a place). So one approach is to include distinctive information or up-to-date tips that might get picked up. For example, if your content mentions “Note: Notre-Dame is currently under restoration,” the AI might include that nuance, citing you as a source for current status. That could be a way to slip in – but speculative. In general, travel SEOs should brace for AI and focus on either niche content or being so thorough that AI can’t easily summarize everything (like an article “50 things to do” with personal anecdotes – AI might not attempt to summarize all that beyond the main ones).

Trackability: Not directly as your site. The items in the top sights carousel link to Google’s own pages, not yours. So you won’t see impressions or clicks for your site from that feature. If your site has content about each attraction, you might still rank when the user clicks the attraction and does a follow-up search (like searching that museum specifically). That could appear as traffic for those specific pages. But that’s a second-order effect. From the first query, you likely either get traffic if your site’s organic listing still appears below and gets clicked (which might happen if users want a textual guide rather than clicking through each attraction individually). Check GSC for your “things to do in X” pages – if impressions drop and coincide with AI rollout or changes, you can suspect features like this. The travel segment also has Google’s “Things to know” and “Plan a trip” features (like the “Plan a trip” we saw in SE Ranking articleseranking.com – that’s another thing that can push down organics). So it’s a tough space with many SERP features. Use GSC and analytics to watch key queries.

Scholarly Articles (Academic Results)

What it is: Scholarly Articles is a SERP feature that appears for academic or research-oriented queries. It provides a preview of academic papers or literature via Google Scholar results directly on the main SERP. Typically, if you search something that looks like a research topic or has scholarly intent (e.g., a medical research topic, or just include “scholarly articles” in the query), Google might show a box listing 2-3 academic papers, with titles, authors, year, and a snippet like “Cited by X”. It often has a heading like “Scholarly articles for [query]”. Essentially, Google is pulling data from Google Scholar (scholar.google.com) and embedding it. DataForSEO notes: It provides a preview of results from Google Scholar – showing title, author, snippet, citation countdataforseo.com dataforseo.com. Clicking usually takes you to Google Scholar or directly to the paper if available.

SEO/Visibility impact: If you’re an academic publisher or your site hosts research papers (or even if you have highly authoritative content on a topic), this is relevant. Most often, it’s actual scholarly publications (journal articles, conference papers). For those, appearing in this feature means extra visibility to regular Google searchers who might not explicitly go to Google Scholar. Optimizing for Google Scholar is somewhat separate from normal SEO (it involves things like providing PDF files, meta tags like citation_title, etc., which many universities do). If you’re an academic, ensure your papers are indexed in Google Scholar to even be considered here. For general SEOs, this feature can push down normal results. For instance, a student searching a concept might see these first and scroll past blog explanations. That could reduce traffic to your explanatory article if your audience ended up clicking a paper (though lay searchers might avoid the papers because they’re technical). If your site is not a scholarly source, you can’t directly appear here. But if you might have an easier to read piece, a user might prefer your site after seeing the dense academic titles. It’s a mixed bag. If you do scientific content or you’re, say, a company with whitepapers, maybe get them recognized by Scholar. Also, note: if scholarly articles show, Google likely interprets the query as academic, which might affect what other results rank (it might favor .edu or .org content more). So plan accordingly for content – maybe incorporate references to papers (showing you’re authoritative too).

AI overview interaction: An AI could answer a complex query by summarizing what academic literature says. For example, if someone asks “what do studies show about X?”, an AI might output a summary like “According to a 2019 study by Smith et al., X is... Another 2021 paper found Y.” It might even cite those studies. This is both a challenge and an opportunity. The challenge is that if the AI gives the key findings, the user might not click to read the actual papers (which they might not have access to anyway). The opportunity is if your site publishes accessible summaries of research, the AI might use those (or you can become a cited source if you have analysis). Google might still show the scholarly articles box for those who want to dive deeper. Possibly AI will coexist by summarizing and then under the hood those scholar results are references. For researchers, having their paper cited by the AI would be nice exposure (though no clicks, just recognition). For SEO, if you produce research or data, definitely label it and publish in ways that Google can identify as such. If you don’t, then think if the AI is now answering questions with information that used to require reading a blog (like citing data), how can you adjust? Possibly by providing commentary or context that AI might not capture easily. Or focusing on queries that require more than just factual recall (like methodological queries, etc.).

Trackability: Minimal from SEO side. If you have academic content on your website (like a PDF or an HTML of a paper), Search Console might show its performance, but often these papers are PDFs and might not show up in normal performance (or they show as PDF ranking). Google Scholar has its own metrics (like in Scholar profiles you see citations count). But you won’t get a direct “impression” stat from the main Google SERP for being in a scholarly articles box. Maybe if it’s counted as a result position 1 with search appearance “Scholarly article” – not sure if GSC differentiates that. DataForSEO indicates they treat it as a separate element with items including title, URLdataforseo.com. Possibly no, since it goes to scholar.google.com link in many cases (which then redirects to content). So you likely won’t see it in your GSC unless Google linked directly to the PDF on your site (it might do that if it has a direct PDF link). But mostly Google might link to itself (scholar). In any event, academics track impact differently (citations, downloads). If SEO, perhaps track if your content (like educational pages) see traffic changes for those queries – maybe a sign that this feature or AI took some clicks.

Popular Products (Product Carousel)

What it is: Popular Products is a shopping-oriented SERP feature that showcases products related to a query, in a carousel format that isn’t purely ads (though it’s closely tied to Google’s Shopping data). It typically appears for product category searches or broad product searches (e.g., “running shoes” or “best DSLR camera”). It shows a horizontal scroll of product listings with images, names, sometimes price ranges, brands, and maybe rating. It’s essentially Google’s organic product listing feature (as opposed to the sponsored Shopping ads that also show images). Google launched free listings in the Shopping tab, and some of that data feeds into this “Popular Products” unit on web search. It’s meant to help users explore products and filter by things like style, department, etc., right on the SERP. Per DataForSEO: triggers on transactional intent queries, displays as carousel of product items on desktop or expandable on mobiledataforseo.com. Each product card can be clicked to show details or search that product specifically.

SEO/Visibility impact: This is big for e-commerce SEO. Even if you rank organically, users might see this product carousel and click into a product that leads them to Google’s Shopping interface or directly to a retailer’s listing (could be your competitor). It’s somewhat like an organic version of shopping ads. If you run an online store, you want your products to appear here. To do so, you likely need to have your product feed in Google Merchant Center (even for free listings) and have good product schema on your pages. Google uses product schema and Merchant Center data (like reviews, price, availability) to populate these. If you’re an SEO for a retail site, coordinate with your Shopping feed team – the free exposure can be valuable. If your products show up, a user might click and then see options “Available at: [YourSite], [Amazon], [OtherSite]” and could click to your site if your price is competitive or they trust you. If you’re not showing up, you might lose out even if your category page is ranking, because a user might jump to a product directly from the carousel. Strategy: Ensure your structured data is correct, consider using Merchant Center even if not doing ads, gather lots of reviews (stars make you stand out in the product cards), and maintain up-to-date pricing. Also optimize product titles and descriptions (as those might influence whether your product is deemed relevant for the category query).

AI overview interaction: For shopping queries, an AI overview might list some product recommendations directly (like “The top running shoes are X, Y, Z, known for comfort...”). Google might be cautious to not favor specific products without clear sources, but they could base it on popularity and reviews. If AI did that, it’s similar to the mention carousel for products – summarizing multiple review sources. But the Popular Products carousel is more about letting the user browse options visually. Possibly Google will keep that because shopping is visual and the AI could come off as making choices for you (which could be controversial if not transparent). Instead, AI might be used more in the shopping context for query refinement (“what are the best for budget under $100?” and then update the carousel or results accordingly). Or the AI might highlight considerations rather than specific models (like “Consider these factors when choosing... here are some popular models”). This is speculative; e-commerce is an area Google monetizes, so they might not fully hand it to AI without ads integration. They could integrate sponsored placements into AI answers eventually (e.g., “We recommend [Product], available on [Store]”), but that’s tricky. For now, assume the carousel remains prominent. As SEO, still focus on feed and schema to get in that carousel. If AI becomes a factor, it will likely rely on the same product data – so accurate data and good reviews will serve you either way.

Trackability: Partially. If your product appears and someone clicks it and ends up on your site (through the “available at” link), that would come as a referral from Google (likely with some tracking parameters). It might not count as an “organic search” click in the traditional sense because the click path might be Google -> Google Shopping detail -> your site. You might need to look at Google Analytics and see referrals from google.com with something like /shopping or parameters. Google Merchant Center provides performance metrics for free listings (impressions, clicks from surfaces across Google). That data is crucial to see how often your products are surfacing and being clicked. Search Console might not fully capture this under the “Web” search type, because the click doesn’t go directly from web search to your site – it goes through a product listing interface. There is a “Google Shopping” search appearance in GSC if I recall for Merchant Center. But possibly not in the Search Console unless they integrated it. The DataForSEO perspective shows it as structured items including price etcdataforseo.com dataforseo.com. If they treat it as part of SERP extraction, they identify if your product’s URL is present in that JSON. However, in many cases, the product card URL might be a Google.com URL that then leads to yours. So track via Merchant Center and Analytics (for referral traffic). Also monitor your organic if those category queries drop in CTR or impressions.

Podcasts (Podcast Carousel)

What it is: For queries related to podcasts or maybe certain topics that have podcast episodes, Google may show a Podcast carousel. This feature displays playable podcast episodes directly on the results page. It often appears if you include “podcast” in the search, or sometimes for a person or show name (e.g., “Planet Money podcast”). It shows episode titles, the podcast name, and a play button/timestamp. Google can play these via the web (Google Podcasts platform). DataForSEO: triggered when query includes “podcast”, shows a carousel of episodes from Google Podcasts relevant to the topicdataforseo.com.

SEO/Visibility impact: If you produce a podcast, this is a great way to get listeners. Google indexing audio means your episodes can be discovered via search queries (especially if you have good titles and descriptions, or if Google transcribes them for content). If someone searches a topic that your podcast covers in an episode, they might see your episode and play it instantly. That’s a “click” in a sense, but instead of visiting your site, they’re consuming via Google’s player (which might not hit your site at all if it’s served from the feed). This could bypass your website (traffic lost) but gain you a listener (which might be the goal for many podcasters who care about audience more than site traffic). For marketing, ensure your podcast is listed on Google Podcasts (which means having a proper RSS feed and possibly adding your podcast to Google’s index via their Podcast Manager). Optimize episode titles and descriptions with relevant keywords (without being clickbait). Also, if you have a site, embed the podcast there too with an audio player; you might then get the rich result (though Google’s approach has been to show the episodes themselves). If you’re not a podcaster, this feature might take some attention away if the query clearly is looking for audio content. But it typically appears when user intends it (e.g., they included “podcast” or it’s a known show). Not usually random.

AI overview interaction: If someone’s looking for an informational answer that’s in a podcast, AI might provide the info itself rather than directing to the podcast. But if someone specifically wants a podcast, they might ask the AI “find me a podcast about X.” The AI could then list some recommended podcasts or episodes. That would be akin to the current feature but in text form. It might even directly link to episodes. Hard to know if they’d integrate the playable function into AI answers (possibly eventually). For now, the podcast carousel likely remains for those queries. The AI might not often invoke it unless asked specifically. In general, AI might not recite content from a podcast unless it has transcription and quotes, which is possible if Google processes it. That could be another angle: AI might answer a question by quoting a podcast discussion if it’s in its training data (less likely for proprietary episodes unless transcriptions are on web pages). For now, podcasters should focus on making content accessible (transcripts on site, which also helps SEO, or at least good metadata). If transcripts exist, AI might use them, which could mean an answer is given without playing the episode. But at least it might cite the podcast. We’ll see.

Trackability: Yes via Podcast Manager and some extent GSC. Google has a Podcast Manager tool which shows how your podcast is performing on Google (including how many plays from search, etc.). That’s the best way to track impressions/plays from the SERP carousel. It’s outside of typical SEO tools, but important if you have a podcast. In GSC, if you also have a page for each episode, those pages might rank or get impressions (though if Google just shows the playable episode, it might not click through to your page). Possibly GSC’s Performance might show queries where your feed/episode got impressions (maybe under “Google Podcasts” search appearance or something), not sure if GSC integrates that data. But treat Podcast Manager as your “Search Console” for audio. Also keep an eye on referrals if any from google.com/podcasts (if someone clicks through to your site link from the podcast interface, but that’s rare, as they typically just listen).

Questions & Answers (Q&A on SERP)

What it is: The Questions & Answers feature refers to a Q&A section that Google sometimes shows for certain queries, often pulling content from Q&A platforms or forums (like Stack Exchange, Quora, etc.) in a special format. It could also refer to the Q&A that appears in certain knowledge panels (for places on Google Maps, users can ask questions and others answer, which appear on the panel). However, since our context is SERP features, it likely means the feature where Google shows a snippet of a question and an answer from web pages directly in the search results. DataForSEO describes: appears when searches are looking for answers/solutions, and Google extracts Q&A pairs from pages marked up as Q&A (schema)dataforseo.com dataforseo.com. We saw in the JSON an example from a site where a question and a short answer were pulleddataforseo.com. So basically, if a site has a Q&A format (like forums or Q&A schema), Google might list a question and expandable answer snippet on the SERP.

SEO/Visibility impact: This is somewhat like an enriched snippet that gives more than just the page title. It’s similar to People Also Ask, but coming from one site’s Q&A content. If your site has Q&A structured data or format, you might benefit by getting an expanded snippet that directly shows an answer. That could increase click-through if the snippet is intriguing (or possibly decrease if it fully answers the question – though usually it’s partial). For example, a StackExchange answer might be shown; users might be satisfied or might click for details. If you manage a forum or Q&A site, implementing the Q&A schema could help Google feature your Q&As. Also, clear question phrasing and concise answers at top of answers might lead to being featured. For general sites, perhaps having a FAQ section (with Q&A schema) could sometimes get picked up similarly (though Google often treats FAQ differently, showing multiple FAQs under your result). The difference: Q&A schema is meant for user-generated single-question pages (like “How do I fix X?” with best answer). If your content addresses a specific question clearly, you might see this feature. As an SEO, it’s beneficial if you run such sites – it’s a rich result type. If you don’t, this feature might appear for queries and push the actual organic link down by showing Q&A snippet(s). It can be competition in results if, say, Quora or Stack Overflow appears with an expanded answer. In that case, if you had content targeting that query, you might be outranked or overshadowed.

AI overview interaction: AI can definitely answer a lot of these specific questions directly, possibly using the same sources (like Stack Overflow answers). For coding questions, Bing’s AI is known to just give you the answer (often drawing from Stack Exchange without explicitly saying so). Google’s AI might do similarly – provide a direct answer or steps. If AI reliably answers these how-to or factual Q&A queries, users might not click the forum results as much. However, some Q&A are subjective or need multi-person perspectives, where an AI might summarize but the user could still benefit from reading the thread. It’s tricky. But I suspect many straightforward Q&As (especially technical ones) will see reduced traffic as AI gives the consolidated answer. For site owners, if a lot of your traffic comes from people seeking quick answers (like programming solutions), you might want to adapt by providing tools, deeper analysis, or community aspects that encourage people to click beyond just the accepted answer text. Also, if AI uses your content, hopefully it cites (maybe not the individual answerer but the platform) – that might not drive traffic but at least gives credit. Google might continue to show the Q&A snippet below the AI or skip it if the AI covers it. We’ll see.

Trackability: Yes, if your site appears. In Search Console, if you use Q&A schema, there is a “Q&A” search appearance filter. You can see impressions/clicks where your site was shown as a Q&A rich result. This data can tell you how effective it is. Also, if you run a forum, track overall traffic. If AI starts eating into it, you’d notice drops in long-tail Q&A visits. But specifically, GSC’s search appearance is useful to know how often Google is extracting your Q&A. Also make sure your schema is implemented correctly, or else Google might not identify the format to show it.

Find Results On (Other Sites Carousel)

What it is: “Find results on” is a carousel/box that Google began showing (especially in Europe due to antitrust) which lists alternative search providers or specific site searches for the query. For example, above the local pack it might say “Find results on: Yelp, TripAdvisor, Facebook” for a restaurant query. Or for products, “Find results on: Amazon, eBay…”. It’s basically a prompt linking users to competitor search engines or specialized sites to find what they want outside of Googleseroundtable.com. It’s typically small, with the logos of other websites. It’s more common in EU (as per the referenceseroundtable.com, introduced in 2020 after EU pressure). It’s not about your site’s content but rather pointing to other search services.

SEO/Visibility impact: This feature can potentially divert traffic away from Google (which was its intention in EU). If a user decides to click “Find results on [Amazon]” instead of clicking an organic result, that means one less visitor via Google to the web. For SEO on your site, if you are one of those alternate platforms, it’s great – e.g., if you run a vertical search or directory, being included here can send you traffic. But only big ones are typically included (like Yelp etc.). If you’re just a regular site, this feature doesn’t directly involve you except that it might cause the user to leave Google. For instance, if your e-commerce site ranks on page 1 but the user instead clicks “Find results on Amazon” at the top, they’ll go to Amazon’s search for that product, skipping your site. That could mean lost opportunity. However, user has to intentionally choose those, and it’s often labeled clearly, so mostly those very brand-loyal or dissatisfied with Google’s results might use it. From a strategy view: not much you can do to directly leverage it unless you happen to own one of those directory sites. If so, ensure you’re eligible (in EU, I think there was a signup process to be included as an alternate provider). But for most, it’s just something to be aware of. In the context of user note “EU Only”, if you have European presence, know it exists.

AI overview interaction: If AI makes search easier, users might not need to consider going to another site. The “Find results on” is more of a regulatory remedy. If AI overviews become widespread, regulators might question them too, but currently, that box might persist separately. It’s unclear if AI results will incorporate suggestions like “you can also check on Yelp or others” – probably not unless mandated. If anything, the presence of AI could overshadow this box even more. But as an SEO, since you can’t really optimize for it, AI doesn’t change how you handle it. Possibly fewer people will use the alternate providers if AI gives an answer (for example, they might not go to Amazon if the AI already suggests a product right on Google – which ironically could raise new antitrust concerns). We’ll see how that plays out policy-wise.

Trackability: No, except by monitoring traffic from Google vs others. If you are one of those providers, you could track how much referral you get from Google through that box (likely appears as something in the referrer string). But Google doesn’t report it in Search Console because it’s not your site’s impression/click on Google’s SERP – it’s a link out. A normal website won’t see anything here, except maybe a slight difference in user behavior metrics if in Europe vs elsewhere. If you suspect users might be leaving via that, you could see if your Google traffic is lower in regions where that feature is displayed heavily (EU countries) compared to where it isn’t (like US). But there are many variables.

Conclusion:

In summary, Google’s SERP features range from purely informational to direct answer to navigational aids, and now AI overviews add a new dynamic. Marketers and SEO professionals need to adapt by optimizing for these features when possible (via structured data, content format, etc.), focusing on providing value beyond what Google can directly show, and ensuring their data is integrated (like feeds for products, Business Profiles for local, etc.). Also, analyzing how AI overviews might pull content and striving to be a source for those (by being authoritative and well-ranked) will become part of SEO strategy. And where direct tracking is not available, using surrogate metrics (like Google’s own platform insights or structured data reports) is key to understanding performance in these features.

Mastering Google SERP Features in an AI-Powered World

Google’s search results page has evolved far beyond 10 blue links. It now includes a rich variety of SERP features – special result types like answer boxes, carousels, image packs, and more – that can significantly affect your SEO strategy. With Google introducing AI-generated overviews at the top of some searches, it’s more important than ever to understand these features. Below, we break down key SERP features, explaining what each one is, how it appears, its impact on SEO, how Google’s new AI overviews might interact with it, and whether you can track or optimize for it.

(Table of Contents style listing of features could go here for quick navigation if it were a webpage.)

Featured Snippet (Quick Answer)

What it is: A Featured Snippet is a highlighted answer box that appears at the top of the organic results (often called “Position 0”). It contains a summary of an answer to the user’s query – usually extracted from a top-ranking webpage – along with a link to that page. It can be a paragraph, list, or table. For example, ask “What is meta description in SEO?” and you might see a boxed excerpt directly answering the question, sourced from a site, before the normal resultsemrush.com】.

Why it matters: Featured snippets steal the spotlight on the SERP. They often get a high share of clicks (and voice search answers) because they satisfy the query immediately. If your content lands the featured snippet, you gain major visibility and credibility. However, if a snippet fully answers the query, some users may not click through to your site – a double-edged sword. Overall, winning a snippet can be a huge traffic boost, especially on queries where users need more detail beyond the snippet. It also indicates Google trusts your content.

SEO strategies: To capture featured snippets, answer the question clearly and concisely in your content. Use the query (or a close variant) as a question or heading, and follow it with a succinct answer (one to three sentences or a bulleted list). Structuring your page with clear Q&A or definition sections helps. Google often takes snippets from pages already ranking on page 1, so solid organic ranking is a prerequisite. Monitor what queries trigger snippets in your space and how those answers are formatted, then aim to do better. Tools like SEMrush or Ahrefs can identify if you’re the snippet source or if competitors are. Keep in mind: snippet content should be to-the-point and factual – fluff won’t get picked up.

AI overview interaction: Google’s AI-generated overview (in the Search Generative Experience) is like a super-snippet that blends information from multiple sourceseranking.com】. In tests, if an AI summary appears, the featured snippet might appear below it or not at all. The AI overview might diminish the importance of featured snippets by providing its own aggregated answer. However, the AI box also cites sources. The good news: pages that often win featured snippets are exactly the kind of high-quality sources the AI might cite. In effect, ranking in the top results (and having snippet-worthy content) could land you a mention and link in the AI summary. The bad news is the AI might satisfy the query, potentially reducing clicks on the featured snippet or your link. Prepare by continuing to craft snippet-optimized content – this helps both traditional snippets and increases the chance of being an AI-cited source. Also, consider more in-depth content beyond the snippet, to entice users who see the snippet/AI answer and want to learn more.

Tracking & measurability: You can track featured snippet performance in Google Search Console under “Performance > Search results” by filtering for the query and checking if your average position is 1 even when you’re not rank 1 (a clue you held the snippet). Some tools explicitly flag if you own the snippet. Only four types of features (organic, paid, featured snippet, local pack) are reported as actual “results” in many SEO tools, so snippets are trackable. Watch your click-through rate: if you have a snippet but CTR is low, users might be getting their answer without clicking. You may need to provide a teaser in the snippet to encourage the click (answer the question but suggest there’s more to learn).

Answer Box (Direct Answer, Knowledge Card)

What it is: An Answer Box is a result that directly answers the query within the SERP, often without needing to click any result. It’s typically drawn from Google’s Knowledge Graph or public domain data. These can appear as knowledge cards (simple facts), calculators, unit converters, dictionary definitions, etc. For instance, search “30°C in °F” and Google shows the converted temperature instantly. Or ask “What’s the capital of Australia?” and you’ll just see “Canberra” in a box. Unlike featured snippets, answer boxes usually don’t cite a specific external website – the answer comes from Google’s own data or a partner (like Wikipedia for some facts).dataforseo.com】

Why it matters: From an SEO standpoint, answer boxes are a double-edged sword. They provide users instant gratification – great for user experience – but they can result in a zero-click search, meaning the user got what they needed without visiting any site. If the answer comes from Google’s data, no site gets that click. If it’s something like a dictionary definition or a calculator result, there’s no opportunity for your site on that query at all. However, if you’re the authoritative source feeding the Knowledge Graph (e.g., your organization’s info appears in a knowledge panel), it reinforces your brand credibility even if it doesn’t always drive clicks.

SEO strategies: For many answer-box queries (dates, math, conversions, famous facts), there is no SEO angle – Google will show its own info. Focus your efforts on queries that don’t have absolute answers or where you can provide additional value. If you have factual content (like a dataset or your own published info that Google might use), ensure it’s accurate and marked up (schema, etc.) because Google might pick it up for its Knowledge Graph. For example, if your site has structured data about your company (address, founders, etc.), Google’s knowledge panel for your brand might show that. That’s indirectly SEO – it’s more about managing your knowledge panel via Google Business Profile, Wikipedia, etc. In cases where answer boxes are sourced (like sometimes a weather site might be credited for weather info), those are special partnerships – not typical SEO. The key strategy with answer boxes is to target longer-tail queries around those topics. For example, Google will directly answer “What’s the capital of Australia,” but for a query like “Why is Canberra the capital of Australia instead of Sydney,” Google might not have an instant answer – that’s where your content can rank.

AI overview interaction: AI overviews often handle simple factual queries directly, much like answer boxes. If anything, the AI is an even more advanced “direct answer” system. For straightforward questions (definitions, factual data), the AI box might just provide the fact (with a citation if from a source). In those cases, the presence of an AI overview or an answer box similarly leaves little room for SEO-driven traffic – the user’s need is met. However, AI might sometimes provide additional context around a fact, whereas a static answer box is usually bare-bones. From a strategy perspective, there’s not much change – queries that were going to be zero-click due to answer boxes will likely remain zero-click with AI. One thing to watch: if AI overviews start handling more complex questions (that previously a user might click a result for), that could encroach on territory that wasn’t fully covered by answer boxes before. In short, continue focusing on questions that require explanation, nuance, or depth – those are less likely to be fully satisfied by a one-line answer in an AI or answer box. And if you notice AI giving a short answer plus citing a source, that could be an opportunity: perhaps provide a slightly more detailed answer on your site that the user will click for.

Tracking & measurability: Answer boxes themselves are not something you “rank” for – they’re not an organic result with your URL (except in some cases like a definition from your site, but that’s effectively a featured snippet or dictionary result). So you won’t see “Position 0” in Search Console for an answer box. Either you’re the featured snippet (trackable) or it’s a pure knowledge answer (no direct tracking). Monitor your overall impressions and clicks for quick-answer queries. If you rank below an answer box, you might see impressions but low CTR. You can’t remove the answer box, but you might try to target the broader query or a related question where you can compete. Keep an eye on the “People Also Ask” and related queries for those – often, answer boxes appear for the main query, but users then click a PAA question that you can rank for. In summary, measure indirectly: if you have content on a query that suddenly dropped in clicks and now you notice Google gives an answer box or AI answer, that’s the cause – time to pivot keyword targeting.

Knowledge Graph Panel (Knowledge Panel)

What it is: The Knowledge Graph panel is the information box that appears on the right side of desktop results (or top on mobile) for known entities – like companies, people, movies, etc. It’s also simply called a Knowledge Panel. It’s powered by Google’s Knowledge Graph database. For example, search a famous person’s name and you’ll see a panel with their photo, birthdate, profession, and other facts. Search a business (especially one with a Google Business Profile) and you get a panel with address, hours, reviews, etc. It’s highly visual and factual. On desktop, it’s separate from the main list of results, though some elements (like “People also search for” carousels) may appear within it. Important: The knowledge panel is not drawn from one site – it aggregates data from many sources (Wikipedia, official websites, Google My Business, data providers). It does not directly link to your website except maybe via an official site link or social media links.dataforseo.com】

Why it matters: Knowledge panels dominate the screen on the right (or top on mobile), especially for brand searches or entity searches. They reinforce credibility and brand presence by showing that Google recognizes the entity. For marketers, having a robust knowledge panel for your brand means users can immediately see key details (logo, description, contact info, reviews) which can influence perception and conversions (for local businesses, this is crucial – it shows maps, call button, etc.). However, since it’s not directly part of the organic “10 links,” you’re not getting traffic from it unless the user clicks through one of the links (like the website or a specific action button). In fact, a strong knowledge panel might keep a user from needing to click your site for basic info (they got the phone number or hours right there). So the impact is more about visibility and user behavior than referral traffic.

SEO strategies: While you can’t “rank” a knowledge panel, you can influence it. Claim your Knowledge Panel (if it’s for a person or brand and Google offers claiming via your Google account) or, for businesses, claim and optimize your Google Business Profile. Fill in all details, add photos, get Google reviews – these all populate the panel. Ensure your Wikipedia page (if one exists) is accurate and up-to-date; Google often pulls the description from there. Use schema markup on your site (Organization, Person, Product, etc.) to feed the Knowledge Graph reliable data about your entitdataforseo.com】. For example, the panel might show “Founded: 2010” for a company – that could be coming from schema on the official site or Wikipedia. Also, encourage common search queries that trigger the panel: e.g., people searching your brand plus keywords like “headquarters”, “CEO” – if your site and other sources consistently provide that info, Google will include it. Another tip: answer common questions about your entity on your site (FAQ schema) – sometimes Google will show a “People also ask” about your brand, or even include a brief Q&A in the panel. Bottom line: optimizing for knowledge panels is about providing consistent, factual data across authoritative sources. It’s more digital PR and brand management than classic SEO, but it falls under the SEO umbrella to ensure Google has the right info.

AI overview interaction: In an AI-dominated results page, you might have an AI summary about the entity and a knowledge panel. For example, if you ask “Who is Elon Musk?”, the AI overview might give a few sentences, but Google will still show a knowledge panel with detailed data and links. In early SGE demos, the knowledge panel often still appears alongside the AI chat resulsemrush.com】. The AI might even pull info from the knowledge panel/Wikipedia to formulate its answer. So, if your brand or entity is searched and an AI blurb appears, it will likely use Knowledge Graph info (which you helped curate). The knowledge panel will remain a key reference point for users wanting verified facts, while the AI might provide a narrative. Opportunity: The AI overview might not include everything in the panel – e.g., it might not list your address or stock price. So users will still glance at the panel for those specifics. Continue to optimize the panel info (that feeds both the panel and potentially the AI summary). If the AI summary cites a source (like Wikipedia or your site for a particular fact), that’s added visibility. Make sure those sources (Wikipedia, official site) are well-maintained. We might also see AI suggest “Learn more about [Brand] on its official site or Wikipedia” – which could drive clicks. Thus, a well-structured site with clear about pages can indirectly benefit.

Tracking & measurability: Knowledge panels themselves aren’t something you track via Search Console impressions or rank. They’re a separate knowledge result. However, you can track indirect metrics: for example, monitor searches for your brand in Search Console – if impressions go up but clicks don’t, it could be that more people are seeing the panel and not clicking your site because they got info (like phone number) right there. Track Google Business Profile insights if you have one – it shows how many people saw your listing and took an action (click to website, call, directions). That’s effectively measuring engagement with the knowledge panel for local. Also, track the volume of branded searches (via Google Trends or Search Console) – a healthy, info-rich panel might encourage more people to search your brand (because Google shows you nicely). If you make changes (like adding schema or getting a Wikipedia update), you may eventually see the panel update; note those changes for your records. While you can’t get a “Knowledge Panel CTR,” qualitatively assess if users find what they need. For example, if you notice many users still clicking your site for a common fact that could be in the panel, you might want to update the panel info so they don’t have to. Conversely, if your panel shows something unfavorable or incorrect, that can hurt user trust – so work to correct it via the source (e.g., suggest an edit to Google or fix the Wiki data).

Understanding Google’s SERP Features (and AI Overviews) – A Guide for SEOs and Marketers

Featured Snippet

Answer Box (Direct Answer)

Knowledge Graph Panel (Knowledge Panel)

People Also Search For (PASF)

Organic Results (Classic Blue Links)

Paid Results (Google Ads)

Carousel (Horizontal Carousel Results)

Multi-carousel (Multiple Carousels)

Images (Image Pack)

Video Results (Video Thumbnails)

Twitter (X) Carousel

Google Reviews (Reviews in SERP)

Local Pack (Map Pack)

Map (Google Map on SERP)

(If needed, skip detailed since we covered similar in Carousel and PASF. But since the list explicitly had it, we needed to clarify differences.)

(We already covered this above in its own section, which might suffice. If needed, we ensure it's clear that "related_searches" is the bottom-of-page suggestions, which we did.)

(We might skip rewriting since it’s done, but just ensure our explanation encompassed point 1-4 which it did.)

Mention Carousel (Mentioned In...)

Recipes (Recipe Carousel/Results)

Top Sights (Things to Do carousel)

Scholarly Articles (Academic Results)

Podcasts (Podcast Carousel)

Questions & Answers (Q&A on SERP)

Find Results On (Other Sites Carousel)

Conclusion:

Mastering Google SERP Features in an AI-Powered World

(Table of Contents style listing of features could go here for quick navigation if it were a webpage.)

Featured Snippet

Answer Box (Direct Answer)

Knowledge Graph Panel (Knowledge Panel)

People Also Ask (PAA)

People Also Search For (PASF)

Related Searches (Search Suggestions at Bottom)

Organic Results (Classic Blue Links)

Paid Results (Google Ads)

Carousel (Horizontal Carousel Results)

Multi-carousel (Multiple Carousels)

Top Stories (News Carousel)

Images (Image Pack)

Video Results (Video Thumbnails)

Twitter (X) Carousel

Google Reviews (Reviews in SERP)

Local Pack (Map Pack)

Map (Google Map on SERP)

People Also Search (Related Entity Carousel)

Related Searches (Bottom Queries)

Mention Carousel (Mentioned In...)

Recipes (Recipe Carousel/Results)

Top Sights (Things to Do carousel)

Scholarly Articles (Academic Results)

Popular Products (Product Carousel)

Podcasts (Podcast Carousel)

Questions & Answers (Q&A on SERP)

Find Results On (Other Sites Carousel)

Mastering Google SERP Features in an AI-Powered World

Featured Snippet (Quick Answer)

Answer Box (Direct Answer, Knowledge Card)

Knowledge Graph Panel (Knowledge Panel)

People Also Ask (PAA)

Understanding Google’s SERP Features (and AI Overviews) – A Guide for SEOs and Marketers

Featured Snippet

Answer Box (Direct Answer)

Knowledge Graph Panel (Knowledge Panel)

People Also Ask (PAA)

People Also Search For (PASF)

Related Searches (Search Suggestions at Bottom)

Organic Results (Classic Blue Links)

Paid Results (Google Ads)

Carousel (Horizontal Carousel Results)

Multi-carousel (Multiple Carousels)

Top Stories (News Carousel)

Images (Image Pack)

Video Results (Video Thumbnails)

Twitter (X) Carousel

Google Reviews (Reviews in SERP)

Local Pack (Map Pack)

Map (Google Map on SERP)

People Also Search (Related Entity Carousel)

Related Searches (Bottom Queries)

Mention Carousel (Mentioned In...)

Recipes (Recipe Carousel/Results)

Top Sights (Things to Do carousel)

Scholarly Articles (Academic Results)

Popular Products (Product Carousel)

Podcasts (Podcast Carousel)

Questions & Answers (Q&A on SERP)

Find Results On (Other Sites Carousel)

Mastering Google SERP Features in an AI-Powered World

Featured Snippet (Quick Answer)

Answer Box (Direct Answer, Knowledge Card)

Knowledge Graph Panel (Knowledge Panel)

People Also Ask (PAA)

Search Intent Types and Their Impact on Google’s AI Overviews

Optimising Content for AI-Driven Search: Theoretical Insights for the LLM Era