Web scraping is a valuable tool for marketers as it enables the extraction of relevant data from websites, facilitating market research, competitor analysis, and trend identification, ultimately aiding in informed decision-making and strategy development.
Web scraping for competitor research involves extracting data from competitor websites to analyze product details, pricing strategies, and content structures. This helps you stay competitive by following industry trends and understanding their rivals’ online presence.
Learn how to build your own product reviews dataset with a simple API call in just a couple of minutes.
We’ll explore how to collect data from the biggest ecommerce marketplace, how to unlock your products’ growth potential, and a simple way to scrape Amazon data at scale.
In this tutorial, we’ll walk you through how to scrape eBay product reviews with Python and BeautifulSoup, allowing you to collect hundreds (or thousands) of reviews automatically without getting blocked.
In this article, we’ll show you how to scrape Walmart product reviews and build a historical dataset to help you make better marketing and business decisions.
In this tutorial, you’ll learn how to use Python and BeautifulSoup for extracting data from Trustpilot.
In this article, we’ll show you how to collect product reviews from G2 without risking a ban from the site, allowing you to export data into a JSON file for easy analysis.
In this tutorial, we’ll build a simple Google Trends scraper using PyTrends, an unofficial Google Trends API.
In this article, we highlight how web scraping is a scalable approach for PPC research, prospecting, and overall trend analysis. We’ll show you how to build a Google Ads data scraper so you can confidently compete online – without burning out your team (or your pocket)
With sentiment analysis, you can understand the emotional aspect behind the message. In this blog post, we’ll explore what is sentiment analysis and why is it so important.
In this guide, we are going to break down the 7 best social media and TikTok proxy providers sharing with you their individual pros, cons and what tasks use cases suits them best.
Scraping keyword rankings means pulling data on how certain words or phrases perform in search engine results, showing how well a website ranks for those terms. This information helps assess a website’s SEO performance and competitive standing in online searches.
If you offer services or products online, you already know the importance of search engine optimization (SEO). Being in the top spots of search results provide your company with higher brand awareness and revenue, but getting there requires a lot of planning and effort.
To help you decide, we’ve listed the seven best APIs for Google SERP scraping. We took into consideration things like response time, data quality, reliability, scalability, extra features, and pricing.
In this article, we’ll show you how to scrape Google Maps in 5 simple steps without getting blocked, helping you build local business databases from anywhere in the world.
So, in today’s article, we’ll show you how you can monitor SERP data in two easy-to-follow methods: the first method requires no coding skills and provides you with clean, structured data; the second method is for tech-savvy teams that want complete control of every phase of the pipeline
In today’s article, we’ll show you how to scrape hotel prices from one of the biggest aggregators: Google!
In this tutorial we’ll use Python’s Scrapy in combination with ScraperAPI to build a scalable and undetectable spider to collect data from millions of search queries and turning them into structured JSON data.
Providing search engines (or any other apps using our web pages) with structured data makes things much easier, and allows for very interesting applications and usage of our data.
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