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Developing a Highly Effective SEO Strategy with an AI-Powered SERP API

Combine Nimble’s AI-powered SERP API and Python to efficiently improve SEO.

Whether it’s to shape brand narratives, influence customer decisions, or to inform and educate, in today’s digital age, the relevance of online content is self-evident. However, the online space is oversaturated with information that users must navigate. In this fiercely competitive landscape, distinguishing your content from the multitude and driving traffic to it is no easy feat.

This is where the implementation of Search Engine Optimization (SEO) can be extremely helpful for businesses and individual content creators alike. When your content is SEO-optimized, it helps search engines to recognize the relevance and significance of your content, ensuring it surfaces prominently in search results. By improving the visibility of a website or online content in the Search Engine Results Page (SERP), SEO helps your content to attract more organic traffic.

SERP APIs can be crucial to this SEO-optimization strategy, providing a gateway to real-time data from search engine results, and offering invaluable insights into user behavior, keyword trends, and competitor positioning. This helps you stay updated with the top results in various fields, which plays a crucial role in the context of SEO competitiveness.

Most performant SERP APIs effortlessly integrate with programming languages like Python and JavaScript, letting you collect data from various search engine results pages, and streamline it into a structured and comprehensive format. This enables developers to build powerful SEO frameworks that can continuously optimize websites or content to outperform rivals.

In this article, we’ll look at how to use a SERP API and implement the data gathered from it in your SEO strategy. To this end, we’ll be using Nimble’s AI-powered SERP API, which provides a range of API configurations that allow for multiple queries across various search engines and locations. Let’s dive in.

The Ultimate SERP API to Scrape Search Engines - Nimble

Understanding SEO and SERPs

Search engines are the primary tool people use to locate the information they seek. The websites that appear first on the results page tend to be the ones with the most traffic. That’s why businesses try to find strategies to optimize their content and bring visibility. This process is known as Search Engine Optimization or SEO.

Google Search Engine

SEO techniques are in constant mutation for a multitude of reasons such as:

  • Algorithm Changes: Search engines are constantly changing their algorithms to provide the best possible content for their users and keep up with trends. Hence, a website's ranking can fluctuate significantly from week to week due to the constant influx of new content that search engines consider when evaluating websites.
  • Competition: Websites are being created at an extremely high rate, making the search engine algorithms continuously evolve and adapt. New and better content, according to the algorithm, can easily replace your golden spot.
  • Website Design: While informative content is crucial, search engines also prioritize websites with optimal design and functionality. A website with slow loading times, limited interactive elements, or unstable visual presentation may struggle to attract visitors and maintain visibility.
  • Keywords: For SEO, keywords are extremely important, and knowing how to use them in the context of your website is crucial. However, several pages might be using the same keywords as you do, which triggers a competition, where the algorithm must decide which pages will be ranked first.
  • Titles and Descriptions: As competition arises with keywords, it also can be extrapolated to titles and meta descriptions. Striving for uniqueness without deviating from the subject is a critical yet challenging task.

The Search Engine Results Page (also called SERP) is the page containing the results you see after entering a query on the search engine. This page is usually separated into advertising and organic results. As SERP is highly sensitive to search query keywords, it highlights the ability to utilize SERP APIs which are ultimately great tools for SEO optimization.

SERP results in Google Search Engine

Here are some key reasons why using SERP APIs is crucial for SEO optimization:

  • Real-Time Data: SERP APIs provide up-to-date information on search results, enabling real-time adjustments and continuous optimization for higher SEO rankings.
  • Track keywords: Knowing which keywords are being used to rank query results can be achieved through SERP APIs, this allows you to increase traffic by using them in your content, title and description.
  • Analyze Competitor Landscape: SERP APIs provide access to comprehensive competitor data, including keywords, titles, descriptions, website URLs, and more. This valuable information can be used to develop strategies that surpass your competitors' rankings.
  • Automation: SERP APIs can be integrated with SEO workflows, allowing you to streamline data collection and analysis, which saves time and resources and enables you to focus on more strategic aspects of your SEO optimization.

These are just some examples of the use cases of SERP APIs that can help overcome the challenges mentioned before. Lately, with the rise of Artificial Intelligence, SERP APIs can make use of Natural Language Processing (NLP) and Large Language Models (LLMs) to provide fine-tuned output data to the customer. We will discuss how this works in more detail in the next section.

The Power of AI in SEO

The power of AI in SEO lies not only in its advanced analysis capabilities but also in its ability to provide actionable insights, streamline data processing, and more. Let’s look at some of the ways AI can benefit with SEO-optimization.

  • AI can leverage Natural Language Processing (NLP) and Large Language Models (LLMs) to transform the way SEO strategies are crafted. NLP enables machines to comprehend and derive meaning from human language, allowing for a deeper understanding of the context behind search queries and content.
  • AI's capability to analyze Search Engine Results Pages (SERP) in real-time provides a dynamic and up-to-the-minute assessment of the digital landscape. This real-time analysis ensures that SEO strategies can swiftly adapt to changing trends, giving businesses a competitive advantage in staying ahead of the curve.
  • AI can help discern semantic relationships, user intent, and the contextual relevance of content within SERP results. This allows for the creation of more targeted and contextually rich content, aligning with user expectations and search engine algorithms.
  • The integration of AI streamlines the often laborious process of cleaning and preprocessing data. You can save valuable time and resources that would otherwise be spent on manual data cleaning, allowing for a more efficient and effective utilization of SEO insights.

However, leveraging AI in your SEO-optimization strategy is not always easy. It can come with several challenges:

  • Lack of Accuracy: The quality and reliability of the data are extremely important when it comes to the accuracy of the model. Inaccurate or outdated data can lead to wrong analysis and predictions.
  • Difficult Integration: If you pretend to use an AI model to be integrated with an existing SERP API, it can become a real challenge at some point, due to compatibility issues and the need for advanced technical resources.
  • Struggle to Adapt: Search Engine algorithms are constantly evolving. Which forces the AI models to adapt to the changes without compromising performance. Models that lack real-time adaptation capabilities are prone to inaccurate predictions.
  • Scalability Issues: AI algorithms can be computationally demanding, and without adequate storage and computing infrastructure, the scalability of AI-powered solutions can be compromised.

If your strategy for integrating AI into SEO faces one or several of the challenges mentioned above, it can become an issue instead of an opportunity to leverage SEO optimization. Addressing these challenges and developing a superior solution can be a costly and time-consuming endeavour. In the next section, we’ll take a look at a solution that addresses these challenges while allowing the utilization of an AI-powered SERP API. 

How to Revolutionize SEO Efforts with Nimble’s AI-Powered SERP API

Nimble's AI-powered SERP API emerges as a comprehensive solution that not only overcomes the challenges of SEO optimization but also capitalizes on them through NLP techniques, resilient infrastructure, and seamless integration with cloud storage solutions, which effectively eliminates the concerns associated with the use of AI-powered SERP APIs.

With Nimble’s SERP API, collecting search engine data becomes a breeze, due to the following capabilities:

  • Real-Time Search Requests: Real-time queries can be done on the following engines: Google, Bing and Yandex. The data is gathered at lightning speed to the user.
  • Local Data: Geographical restrictions are put apart, with Nimble IP which hosts a premium pool of peers with the best reputation, fastest performance, and highest availability in the world.
  • Delivery Methods: Nimble's SERP API provides the option to promptly deliver data directly to the user (real-time), to a preferred cloud storage solution, or it can be stored at Nimble’s servers, and later downloaded via git.
  • Batch Processing: Data can be collected at a massive scale with Nimble’s API batch processing. Requests can go up to 1000 URLs per batch, and You can scrape SERP results with multiple queries at a time, on several search engines.
  • Structured Data: Nimble’s SERP API uses AI and NLP techniques to provide you with the most structured and organized output. Making it easy to navigate through the results, and save hours of processing time.

In addition, Nimble offers comprehensive documentation, facilitates integration with multiple programming languages like Python and JavaScript, and includes a user-friendly Playground front-end feature for effortless information scraping using basic inputs.

👉 Explore and learn more about Nimble’s SERP API and its functionalities

We’ve looked at how Nimble’s SERP API can address the AI and SEO-related challenges mentioned earlier. But there’s no better way to prove its reliability than trying out the API in action by integrating it with Python, and also, in the process, looking at a practical use case for SERP APIs. 

However, to make use of Nimble's SERP API, you must first create a Nimble account. You can sign up for an account here (click on ‘Start Free Trial’ under the ‘Free Trial’ option or any other plan of your choice), and once you’ve done that, you need to login with your account details.

Proxies and Web Scraping APIs - Nimble

Once done, let’s dive into the actual code.

Gather SERP results for SEO optimization: The Code

Below, we’ll dive into Nimble’s SERP API while integrating it with Python. In this example, we’ll harness the power of the API by querying a search engine, navigating through the results, and getting insightful information to optimize the SEO of the following article written by me:

The query we’ll be using is the following: “Scrape Infinite Scroll Websites with Python”

The steps:

  1. Import necessary libraries and configure Base access authentication.
  2. Query from Google search engine and specific locations.
  3. Use the Python requests library to make an HTML request to Nimble’s SERP API, and we’ll extract the information in .json format.
  4. Look for organic results and extract meaningful information for SEO optimization.

Let’s start by reproducing the first step on a Python script:

import requests
import base64

username = '<your_nimble_username'
password = '<your_nimble_password'
token = base64.b64encode(bytes(f"{username}:{password}", 'utf-8'))
token = token.decode('utf-8')  # convert bytes to string

In the script above, we start by importing the necessary libraries. The requests library will serve to make an HTML request to the Nimble’s API and the base64 provides functions for encoding binary data to printable ASCII characters. The latter is important because Nimble APIs use Basic access authentication with a credential string (token) generated from the username and password.


In Python, the encoding is achieved with the function base64.b64encode() and the strings username and password are converted to bytes with the encoding utf-8. This output is then decoded to a string which will be the token used with the Basic access authentication.

url = ''
google_engine = 'google_search'
query = "Scrape Infinite Scroll Websites with Python"

headers = {
    'Authorization': f"Basic {token}",
    'Content-Type': 'application/json'

data = {
    "query": query,
    "country": "FR",
    "locale": "en",
    "search_engine": google_engine,

Nimble’s SERP API URL is the one you see in the url variable. As for the search engine, we’ll be using Google, but Bing and Yandex are also available.

The headers dictionary contains the Content-Type and the Authorization, which takes the token previously generated with base64.

The data dictionary has several keys to define the process. The query, the country, the search engine and the locale, which is the language at the output.

Finally, we use the requests instance, to make a POST HTML request with the provided API URL and the dictionaries.

response = requests.get(url, headers=headers, json=data)

We’re now ready to run the script, we just need to save the .json file somewhere in our directory. For that, we can use the following:

import json

with open('data.json', 'w', encoding='utf-8') as f:
   json.dump(response.json(), f, ensure_ascii=False, indent=4)

Once the script is launched, we’ll get a data.json filled with all the search results captured by the API. To easily navigate through the file, I recommend using a JSON extension. Let’s for instance get the information of the first page of organic SERP results:

import json

with open('data.json') as f:
    data = json.load(f)

search_results = data["parsing"]["entities"]["OrganicResult"]


This is the output of the organic results for the provided query:

        'displayed_url': ' > questions > scrape-website...',
        'entity_type': 'OrganicResult',
        'position': 1,
        'snippet': 'Sep 20, 2012 -- ',
        'title': 'scrape websites with infinite scrolling - python',
        'url': ''
        'displayed_url': ' > analytics-vidhya > using-python...',
        'entity_type': 'OrganicResult',
        'position': 2,
        'snippet': 'Jun 26, 2020 -- ',
        'title': 'Using Python and Selenium to Scrape Infinite Scroll Web ...',
        'url': ''
        'displayed_url': ' > blog > how-crawl-infini...',
        'entity_type': 'OrganicResult',
        'position': 3,
        'snippet': 'Jan 2, 2021 -- ',
        'title': 'How to Crawl Infinite Scrolling Pages using Python',
        'url': ''
        'displayed_url': ' > scraping-from-a-website-with-in...',
        'entity_type': 'OrganicResult',
        'position': 4,
        'snippet': 'Scraping from a website with infinite scrolling. · Open the page in Google Chrome · Then go to console ; right click and enable LogXMLHttpRequests. · Now reload\xa0...',
        'title': 'Scraping from a website with infinite scrolling.',
        'url': ''
        'displayed_url': ' > learn > how-to-scrape-infinite-...',
        'entity_type': 'OrganicResult',
        'position': 5,
        'snippet': 'In the sixth part of our Scrapy tutorial you will learn how to find and use underlying APIs that power AJAX-based infinite scrolling mechanisms in web pages.',
        'title': 'Scrapy Tutorial: Scraping Infinite Scroll Pages With Python',
        'url': ''
        'displayed_url': ' > 3-ways-to-scrape-infin...',
        'entity_type': 'OrganicResult',
        'position': 6,
        'snippet': 'The first is the easiest to implement, by simply scrolling down and up the page to load items. However, these loaded items may not necessarily be accessible for\xa0...',
        'title': '3 Ways to Scrape Infinite Scroll Websites with Python',
        'url': ''
        'displayed_url': ' > tutorials > how-to-han...',
        'entity_type': 'OrganicResult',
        'position': 7,
        'snippet': 'One of these techniques is the infinite scroll. In this tutorial, we will see how we can scrape infinite scroll web pages using a js_scenario, specifically\xa0...',
        'title': 'How to handle infinite scroll pages in Python - ScrapingBee',
        'url': ''

As we can see, my Medium article is positioned at the 6th place in France, which is a good SEO ranking. I’ve tried the same for US, and I got the same position. As for Spain, my position gets even better (3rd).

        'displayed_url': ' > 3-ways-to-scrape-infin...',
        'entity_type': 'OrganicResult',
        'position': 3,
        'snippet': 'The first is the easiest to implement, by simply scrolling down and up the page to load items. However, these loaded items may not necessarily be accessible for\xa0...',
        'title': '3 Ways to Scrape Infinite Scroll Websites with Python',
        'url': ''

The goal now would be to look at articles that have a better ranking than mine and look for strategies to overcome them. For instance, the third place uses a title that might conflict with the title I’ve used in my article’s SEO settings. So I could start by changing that, and check the updated results.

Nimble’s SERP API uses its AI-powered NLP engine to output related searches, which is important because it allows us to see if the article is also ranking at the top for similar queries. Hence, I’m now going to try two of the related queries provided by Nimble’s SERP API on United States (US) location.

"RelatedSearch": [
        "entity_type": "RelatedSearch",
        "query": "Scrape infinite scroll websites with python example",
        "url": "/search?sca_esv=582242121&hl=en&gl=fr&q=Scrape+infinite+scroll+websites+with+python+example&sa=X&ved=2ahUKEwj2uZmUsMOCAxXETKQEHa7zCroQ1QJ6BAgoEAE"
        "entity_type": "RelatedSearch",
        "query": "scraping infinite scrolling pages python beautifulsoup",
        "url": "/search?sca_esv=582242121&hl=en&gl=fr&q=Scraping+infinite+scrolling+pages+Python+BeautifulSoup&sa=X&ved=2ahUKEwj2uZmUsMOCAxXETKQEHa7zCroQ1QJ6BAglEAE"

For these two queries, my article jumped to the 5th place, and they are as meaningful as the first one provided.


This article has examined Nimble’s AI-powered SERP API and its usefulness as an SEO optimization tool. Most of the SEO challenges that were addressed at the beginning can be mitigated with the use of Nimble’s API which retrieves real-time SERP results at lightning speed and constantly adapts to the search engine algorithm changes. You can use it to stay updated about competitors’ rankings and apply strategic solutions to increase your SERP position by making changes to website design, changing keywords and trying out different titles and descriptions.

Nimble’s SERP API uses AI to provide related queries and gather data in a meticulously organized and structured way. It does not face storage and scalability issues as other AI solutions do, thanks to its seamless integration with external storage solutions or even in-house storage, for later downloading. Additionally, with Nimble IP, which hosts a premium pool of residential IPs, you can leverage their SEO optimization around the globe.

Nimble SERP API - Scrape and Collect Data from Search Engines

Nimble’s SERP API also comes with a free trial so you can give it a spin at no extra cost and see if it suits your needs.

The example in the Medium article shows some of the potential benefits of using the API. My article was already ranking well, thanks to Medium’s great SEO, but even a simple data extraction revealed that my SEO title could conflict with another article’s title, so I was able to apply a simple change.

We also tried querying from different locations and using related queries provided by the API, which resulted in significantly different results. As a technical writer constantly involved in refining my writing skills, I can make good use of Nimble’s SERP API, to constantly track the performance of my articles in SERP and edit them to increase my SEO ranking.

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