How to Collect Data from the Web in 2025

By 2025, data has become the flagship driver of the global economy. The daily volume of information generated has exceeded 650 exabytes, 80% of which are reviews, images, videos, and IoT signals. Companies use information to optimize processes and forecast trends. Retailers who have implemented AI scraping to monitor social media are reducing the time it takes to bring new products to market from 18 to 6 months. Algorithms that analyze online transactions reduce the risk of fraud by 40%. In healthcare, data collection makes it possible to predict SARS and flu epidemics 3 months in advance.

The tightening of GDPR in the EU and CPA in the USA requires businesses to fully comply with international and domestic standards. The ability to legalize them, purify them, and turn them into strategic insights is especially appreciated. Companies that invest in ethical scraping and integration with AI analytics are shaping new markets.

Collecting data from the Internet is an indispensable tool for business, science and technology. The volume of information has increased tenfold over the past 5 years. The methods of its extraction have become more difficult due to stricter safety rules and legal regulations. Below, the approaches to the process are presented and briefly analyzed.

1. Manual collection. It is relevant in niches where contextual analysis or small-volume work is required. Market researchers use it to collect data from closed communities in which automation is blocked by the administration and policies of the social network. Marketers manually analyze comments to identify latent trends. Automated algorithms don't pick them up. Limitations: high labor intensity, risk of errors, and inability to scale. In 2025, AI-based tools and assistants began to appear for manual operations. They speed up the process of saving and adding to structured tables.
2. Web scraping tools. Automated data collection is popular among marketers, but it implies legal difficulties. The technology is based on parsing the HTML code of pages using debugged scripts. Scrapy and Selenium are able to process content.
3. JavaScript. The updated CFAA (Computer Fraud and Abuse Act) prohibits access In the United States, which is actively used in e-commerce to track the range of competitors, media analytics, and monitoring. This violates the terms of use of the website.
4. API. Application Programming Interface provides developers with access to information. Using the Instagram Basic Display API, you can get profile and publication data without the risk of being blocked. The advantages of APIs are structured data output and built—in authorization mechanisms. Restrictions: limits on the number of requests, unavailability of certain functions (for example, historical data), and dependence on site policy. In 2025, companies are actively switching to hybrid models, combining APIs with scraping to circumvent restrictions.
5. Cloud platforms. AWS Data Exchange and Bright Data imply a new approach to the process. They offer distributed proxy networks and innovative CAPTCHA circumvention tools. 

By 2025, the market for data collection tools will be fragmented: some solutions are suitable for point—based tasks, while others are suitable for large-scale projects. The choice depends not only on technical capabilities, but also on legal constraints, budget, and the level of expertise of the team. Let's look at which technologies are dominant and in which cases they should be used.

Using libraries like Scrapy or Selenium gives you full control over the data collection process. For example, Scrapy allows you to set up asynchronous requests, which is critical for parsing large e-commerce platforms with millions of product cards. How to collect data from websites, this approach requires deep programming knowledge and time to maintain the code — each update to the site structure can "break" the parser. Selenium, which emulates user actions in the browser, is indispensable for bypassing anti-bot systems, but consumes significant resources. In 2025, it is often combined with AI modules for automatic CAPTCHA recognition, which complicates the setup.

Tools like Octoparse reduce the time needed to launch projects. A marketer without coding skills can set up price collection from competitive websites in an hour. But simplicity has a downside: limited customization and dependence on platform updates. For example, ParseHub, despite its support for dynamic sites, does not always cope with resources where content is generated via WebSocket.

By 2025, No-code solutions have added AI features such as automatic page structure detection. How to gather online data, for complex scenarios (for example, data parsing with authorization), they are still inferior to their programmable counterparts.

Cloud platforms like Bright Data solve two key problems: infrastructure and legality. Their proxy networks and built-in anti-blocking tools allow them to collect data from different regions without risking their IP reputation. 

AI scraping, as in the case of Diffbot, automatically adapts to changes in the structure of sites, reducing the time spent on parser maintenance. Neural networks also analyze behavioral patterns to mimic "human" actions, such as random delays between clicks. But the introduction of such technologies requires not only a budget, but also expertise. Training models on specific data (for example, custom captcha recognition) can take months. In addition, AI solutions consume more computing resources, which increases operating costs.

In 2025, the laws governing data collection in the West and in Russia have become stricter. Technology is developing faster than laws. This creates problems and increases risks for the business.

The Computer Fraud and Abuse Act (CFAA) has been updated in the USA. He treats unauthorized access to information as a criminal offense. This applies to public and private information. In 2025, a California court ruled it illegal to scrape LinkedIn profiles without the official consent of the social network's management.

Ethical standards remain a high priority. Collecting information can damage the company's reputation. Aggressive parsing of news sites with a high frequency of requests slows down the resource. This violates the postulates set forth in F.A.I.R. Data (Findable, Accessible, Interoperable, Reusable). In 2025, an ethical audit is a standard event in large corporations. 

Tips for reducing legal risks:

1. Working through the API. Platforms allow collection on their own terms. 
2. Using a proxy. 
3. Coordination with the management. The email request has long served as a legal shield. In 2025, 30% of startups will use this tool.
4. Monitoring robots.txt Marketplaces prohibit the parsing of price information. Ignoring this requirement can lead to lawsuits.

Automated collection and analysis technologies allow businesses to respond to changes and predict trend changes. Marketing strategies cannot be implemented without analyzing the digital footprints of the audience. Federal and regional networks use social network parsing to identify trends. Algorithms track hashtags, frequency of mentions, and popularity in different regions. Companies adapt their advertising campaigns by offering personalized conditions to potential customers. Brandwatch uses AI to predict audience interests.

Real-time price changes have become the norm in e-commerce. Large retailers use cloud scraping services to monitor and analyze changes in the market. This allows you to instantly adjust your business strategy by offering discounts or bonuses to your customers.

In 2025, innovative plug-ins combining parsing and machine learning were announced. Algorithms predict the impact of external factors on demand, and automatically generate recommendations. 

In 2025, companies are actively using generative AI to automatically respond to reviews. 

Fintech startups use scraping of news feeds and social networks. The approach allows you to more accurately predict the volatility of cryptocurrencies. 

The information collection market is changing rapidly. Specialists need to be aware of innovations in this area. It is better to perform one-time tasks using no-code plugins. AI-enabled cloud services are ideal for large-scale projects. 

Note: We'd like to remind you that the product is used to automate testing on your own websites and on websites to which you have legal access.