A huge amount of information, which is needed to understand potential customers and competitors, can already be stored on the Internet. But how to get it, and then process it? For a long time, the only methods were inefficient manual collection and complex development of custom applications to retrieve data from web resources. But with the advent of automated tools, you can do without coding training and independent development.
In the partner text with Bright Data, we tell you what tools they can do and how to use them.
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Why do you need to collect data from web resources
To the parsing tools 
automated collection of public information from the Internet often succeed when it is necessary to analyze large data sets while solving professional work tasks. But web data collection is also effective in some cases. It is used if information is needed for the following purposes:
- Sales forecasting. The automated data collection tool allows you to build a company’s marketing strategy based on objective indicators: sales volume, pricing, CA, etc.
- Price monitoring. By tracking how the price of the same or similar product from competitors changes, you can adjust your pricing policy to the market.
- SEO promotion. Parsing will help to identify flaws made when working with metadata of web resources, tags, keywords.
- Product management. The data obtained with the help of parsing tools will help to learn about the dynamics of product metrics, evaluate statistical significance, and organize A/B tests.
- Updating data, filling the site. Parsing allows you to automate the process of updating prices in online stores, adding content from wholesalers.
If we evaluate the overall potential of the parsing tools, they will be suitable for both large manufacturing companies and private individuals.
Data collection tools: “manual” and automated
To analyze competitors’ sites, you can create your own parser – a program that collects and organizes data from web pages. In particular, Python is suitable for developing such tools. But writing parser code on it requires programming skills. Knowledge of proxy server management, data extraction and willingness to wait for results will also be required.
The community of active users of the Python programming language is quite large, so you can find free source code for parsing tools online. But in order to adjust them for yourself, you need to dive into the topic. Although this does not guarantee a good result. Therefore, it is often necessary to hire third-party executors who are able to quickly understand the task when developing a parser.
There is also an alternative option – to turn to platforms with automated solutions for collecting and analyzing web resources. In this case, you don’t have to write a single line of code. Using ready-made templates or applications with simple interfaces, you can quickly create a parsing tool for your purposes. This service is easy to use regardless of whether the company has employees with programming skills.
With automated site data collection tools, you don’t need to manually process and analyze the reports generated by parsing.
How to use ready-made parsers
Avoiding self-scripting isn’t the only simplification provided by frameworks with parsing templates. The process will become easier at all stages. Here’s a standard sequence of steps you need to take to get data for your business goals:
- Specify the web resource from which you want to collect data.
- Adjust the frequency of data provision: you can set a schedule or choose online display. Also define the data retrieval format: CSV, HTML, XSLS and others.
- Choose where the prepared reports will be sent: Microsoft Azure, email or through another service.
Major platforms with an automated data collection tool have thousands of parser templates, as well as the ability to quickly create your own parser. Optionally, data preparation is available, in which the information passes through AI algorithms and reaches the customer in a form convenient for study.
Legal automated parsing
Part of the data collected by the parser usually affects the personal information of users. In order not to face claims from human rights organizations, it is important not to violate the rights of site visitors.
Large platforms with automated tools for collecting and analyzing data on sites take into account the regulatory framework of the EU, GDPR and the California Consumer Protection Act CCPA. In particular, they do not allow:
- DDoS attacks to facilitate data collection;
- content theft;
- obtaining data that is a state or commercial secret;
- theft of important personal data specified during registration and in personal contacts.
When the parser can be disabled
Parsing allows you to view data that is in the public domain and is not classified as prohibited for collection and analysis. Despite this, some resources have reasons to prohibit the operation of automated services for collecting site data. For example, they can be blocked because the parser affects the functioning of the site: frequent requests can slow down the response speed or lead to “crashing” of pages.
But such bans are rarely established. Alternatively, they can be bypassed using proxy services that easily integrate with parsers. Therefore, you can order data collection from most sites and receive them in the form of a database prepared for analysis by AI algorithms.
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