Search API Deep Dive: Get Real-Time Google SERP Results and AI Overview (SGE) Data

Why Scrape Google SERP Data?

Google remains the primary demand channel for most businesses. Understanding what appears on the search results page for your target queries is foundational to SEO, content strategy, and competitive intelligence.

Three use cases dominate.

SEO rank monitoring. Tracking where your pages rank for target keywords over time is the most common application. Automated SERP extraction replaces manual checking and enables daily or hourly tracking across thousands of keywords. Position changes, new competitors entering the SERP, and featured snippet gains or losses become immediately visible.

Competitor analysis. Beyond rankings, SERP data reveals which competitor content Google rewards with visibility. By extracting organic results alongside AI Overview citations, you can identify which sources Google's algorithm considers authoritative for any given topic. This intelligence directly informs content strategy and link-building priorities.

AI Overview analysis. With AI Overview now present in a significant percentage of search results, understanding how it works is no longer optional. Teams need to know whether their content is being cited in AI Overview responses, which competitors are being referenced, and what types of sources Google draws from. None of this is available through traditional SEO tools. Programmatic extraction of AI Overview data is the only way to analyze it at scale.

For GEO (Generative Engine Optimization) teams specifically, SERP data is the raw material for measuring AI visibility. You cannot optimize for what you cannot measure, and AI Overview citations require systematic data collection to track.

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Understanding Google's SERP Components in 2026

Google's search results page is no longer a simple list of ten blue links. It is a composite of multiple result types, each with different implications for visibility and traffic.

Organic results remain the core of search. These are the standard listings ranked by Google's algorithm, each with a title, URL, snippet, and position. They are the primary traffic driver for most queries and the focus of traditional SEO.

AI Overview (SGE) appears at the top of many search results, providing a synthesized answer generated by Google's language models. AI Overview responses include text blocks (paragraphs, lists, and occasionally tables), cited references linking to source pages, and follow-up query chips suggesting related searches. For a growing number of queries, AI Overview captures user attention that previously went to the first organic result.

Shopping results appear for commercial and product-related queries, displaying product images, prices, merchant names, and ratings. Google Shopping results have become increasingly prominent and are a separate visibility channel from organic search.

Knowledge panels appear on the right side of desktop SERPs for entity-based queries, pulling structured data from Google's Knowledge Graph. They display facts about people, organizations, places, and things.

People Also Ask (PAA) boxes contain expandable question-and-answer pairs related to the search query. They reveal the semantic space Google associates with a topic and provide content ideation signals.

Featured snippets are selected as the direct answer to a query and displayed prominently above organic results. They draw from a specific page and drive significant traffic.

Understanding these components matters because your optimization strategy needs to account for all of them. Ranking first organically means less if AI Overview satisfies the query without sending traffic to your site. AntsData's Search API extracts all of these components in a single request, giving you a complete picture of SERP composition.

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What Data Does the AntsData Search API Return?

AntsData provides two SERP endpoints, each targeting a different facet of Google's search results.

Endpoint	Purpose	Key Inputs	Key Outputs
google-search	Extract organic rankings, AI Overview content, image results, and pagination data from web search	query, searchType, gl, hl, location, device, num, start	totalResults, organicResults[], imageResults[], aiOverview, pagination
google-shopping	Extract product listings, pricing, merchant data, and ratings from Google Shopping results	query, gl, hl, minPrice, maxPrice, condition, sortBy, resultsLimit	totalResults, products[]

The google-search endpoint is the primary tool for SERP analysis. It returns up to 100 organic results per request, with full AI Overview extraction including text blocks, cited references, and follow-up queries. This is the endpoint SEO teams and GEO analysts will use most frequently.

The google-shopping endpoint is purpose-built for e-commerce intelligence. It returns up to 60 product listings with pricing, merchant information, ratings, and product URLs. It supports price range filters and condition filters, making it suitable for competitive pricing analysis and product assortment tracking.

Both endpoints handle anti-bot bypass, geo-targeting, and locale configuration through the API interface. You do not need to manage proxies, browser sessions, or CAPTCHA solving.

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How to Scrape Google Search Results

Step 1: Set Up the API Call

The AntsData google-search endpoint accepts a JSON payload via a POST request and returns structured SERP data. You authenticate using a Bearer token in the request header. The key parameters are query (your search term), gl (country code such as "us" or "gb"), hl (interface language), location (city-level geo-targeting like "New York,NY,US"), device ("desktop" or "mobile"), and num (number of results, up to 100).

Here is a typical curl request:

curl -X POST "https://api.antsdata.com/v1/google-search" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "searchType": "web",
    "query": "best project management software 2026",
    "gl": "us",
    "hl": "en",
    "location": "New York,NY,US",
    "device": "desktop",
    "num": 20
  }'

The device parameter matters because mobile SERPs often differ in layout and result composition from desktop. The location parameter enables city-level geo-targeting, which is critical for local SEO analysis where results can vary significantly between nearby cities.

Step 2: Parse Organic Results and Rankings

The response contains an organicResults array with the core ranking data. Each result object includes a position (its rank on the SERP), title (the page title as displayed in search), link (the full URL), snippet (the descriptive text shown below the title), and date when available.

For rank monitoring, the critical fields are position and link. By storing these values over time, you build a position history for each tracked query. The snippet field is useful for detecting changes in how Google presents your page, including whether your content is being used in featured snippets or other SERP features.

The response also includes a totalResults field showing Google's estimated total number of matching pages. While this number has limited precision, it is useful for gauging overall competition level for a query.

Step 3: Extract AI Overview (SGE) Content and References

When AI Overview is present on the SERP, the response includes an aiOverview object with three sub-components.

The textBlocks array contains the paragraphs, lists, and structured content that Google generated in response to the query. These are useful for understanding what Google considers the authoritative answer to a given topic.

The references array is the most actionable component for GEO teams. Each reference includes a title and link, revealing exactly which sources Google cited when generating the AI Overview. If your domain appears in these references, your content is being used by Google's AI systems. If competitor domains appear consistently, those are the sources you need to compete against.

The followUpChips array contains suggested follow-up queries that Google presents to users. These reveal the semantic space Google associates with your target queries and are valuable for content planning. If AI Overview is not present for a particular query, the aiOverview field will simply be absent from the response.

Step 4: Handle Pagination for Deep SERP Analysis

For comprehensive SERP analysis, you often need results beyond the first page. The start parameter enables pagination by specifying the result offset. Each request can return up to 100 results, so setting start to 0, 100, 200, and so on pages through the SERP.

This approach is essential for competitive analysis where you need to identify all ranking domains for a query, not just the top 10. The response also includes a pagination object that indicates whether additional results are available, allowing you to build dynamic pagination logic rather than hardcoding page counts.

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How to Scrape Google Shopping Results

For e-commerce teams and product marketing, Google Shopping data requires the dedicated google-shopping endpoint. This endpoint extracts product listings with pricing, merchant information, and ratings in a structured format.

You send a POST request with your search query, geo-targeting parameters (gl, hl), and shopping-specific filters. The minPrice and maxPrice parameters enable price range filtering for competitive pricing analysis within specific market segments. The condition parameter accepts "new" or "used", and resultsLimit controls how many products to return, up to 60.

The response contains a products array where each item includes position, title, price, currency, merchant, rating, reviewCount, imageUrl, and productUrl. The productId field enables cross-query tracking of the same product across different search terms. Combined with merchant, price, and rating data, this supports competitive pricing dashboards, product assortment analysis, and marketplace positioning reports.

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Using SERP Data for GEO and AI Visibility Optimization

AI Overview has changed the visibility equation. Ranking on page one of organic results no longer guarantees the attention it once did. For teams focused on GEO (Generative Engine Optimization), the question is not just where you rank, but whether your content is being cited in AI-generated answers.

The aiOverview.references data from the AntsData Search API is the foundation of AI visibility measurement. Here is how to use it.

Build a citation tracking system. Query your target keywords weekly and extract the references array from each AI Overview response. Track which domains appear most frequently as cited sources. This gives you a clear picture of which publishers and websites Google's AI systems consider authoritative for each topic.

Identify citation gaps. Compare the domains cited in AI Overview against your own domain. If competitors consistently appear as AI Overview sources and you do not, your content is not being recognized by Google's AI systems. This gap requires content strategy changes, not just traditional SEO.

Analyze content patterns in cited sources. Examine the pages that receive AI Overview citations. Look for structural patterns: do they use specific heading structures, include data or statistics, provide direct answers to questions, or follow particular content formats? These patterns inform how you should structure your own content for AI visibility.

Track follow-up queries for content expansion. The followUpChips in AI Overview responses reveal the questions Google associates with your target topics. These are high-value content opportunities because they represent verified user interest that Google has already validated through its own query data.

Monitor SERP feature distribution over time. Track the percentage of your target queries that trigger AI Overview versus traditional organic-only results. As AI Overview coverage expands, your traffic projections and SEO strategies need to account for the shift.

This workflow requires regular, automated SERP extraction. Manual checking cannot provide the frequency or breadth needed. The AntsData API enables you to run this analysis across hundreds of keywords with minimal engineering effort.

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Comparison: AntsData SERP API vs. Google Custom Search API vs. Other SERP Providers

Feature	AntsData Search API	Google Custom Search JSON API	Typical SERP API Providers
AI Overview (SGE) extraction	Full extraction: textBlocks, references, followUpChips	Not available	Limited or unavailable
Organic results per request	Up to 100	Up to 10	Varies (typically 10-100)
Google Shopping endpoint	Dedicated endpoint with filters (price, condition, sort)	Separate Product Search API (deprecated)	Varies
Location targeting	City-level via location parameter	Country-level only	Varies (most offer country-level)
Device targeting	Desktop and mobile	Desktop only for most endpoints	Varies
Anti-bot handling	Managed by AntsData (proxy rotation, CAPTCHA bypass)	N/A (official API)	Varies (most handle basics)
Result freshness	Real-time	Real-time	Near real-time (some cache)
Pricing model	Per-request, volume tiers	Free tier (100 queries/day), then paid	Typically subscription-based
Image results	Included in google-search response	Separate Image Search API	Varies
Pagination	start parameter for deep extraction	start parameter with limits	Varies

The critical differentiator is AI Overview extraction. Google's own Custom Search API does not return AI Overview data. Most third-party SERP APIs have not yet built reliable AI Overview parsing. AntsData returns the full AI Overview structure including cited references, which is essential for GEO analysis.

The location parameter also distinguishes AntsData from most competitors. City-level geo-targeting matters for local SEO analysis and location-specific SERP monitoring, where results can vary significantly between nearby cities.

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FAQ

1. Does the AntsData Search API return AI Overview data for every query?

No. Google does not trigger AI Overview for every search query. AI Overview appears for queries where Google determines a synthesized answer is appropriate, which is more common for informational queries and less common for navigational or highly specific commercial queries. When AI Overview is present on the SERP, AntsData extracts the full content. When it is not present, the aiOverview field will be absent from the response. Your monitoring system should account for this variability.

2. How accurate are the organic result positions returned by the API?

The positions reflect the actual SERP at the time of the request, including the effects of personalization, geo-targeting, and device type. Positions are determined by the parameters you send: gl (country), hl (language), location (city/region), and device (desktop or mobile). For rank tracking, consistency in these parameters is essential. Changing location or device settings between checks will produce different position data even for the same query.

3. Can I use this API to monitor SERP changes for hundreds of keywords?

Yes. The API supports high-volume usage with per-request pricing and volume tiers. A typical rank monitoring workflow queries each keyword daily (or at your preferred frequency) and stores the results in a database. With up to 100 organic results per request and pagination support, you can capture comprehensive SERP data for each keyword. The main constraint is your API usage volume, which scales with the number of keywords and check frequency.

4. How does the Google Shopping endpoint differ from extracting shopping results from the web search endpoint?

The google-search endpoint may include some shopping results within its response, but these are mixed with organic results and lack structured product data. The dedicated google-shopping endpoint returns only product listings with standardized fields: productId, title, price, currency, rating, reviewCount, merchant, imageUrl, and productUrl. It also supports shopping-specific filters like minPrice, maxPrice, condition, and sortBy. For any serious product or pricing analysis, the dedicated endpoint is the correct choice.

5. What is the difference between SEO rank tracking and GEO analysis?

SEO rank tracking measures where your pages appear in traditional organic search results. GEO (Generative Engine Optimization) analysis measures whether your content is cited in AI-generated answers like Google's AI Overview. These are related but distinct objectives. Your page can rank first organically and still not be cited in AI Overview, or your page can be cited in AI Overview while ranking lower in organic results. Both matter for visibility, and the AntsData Search API returns data for both analyses in a single request.