{"id":2724,"date":"2026-03-04T00:00:00","date_gmt":"2026-03-03T23:00:00","guid":{"rendered":"https:\/\/humes.pl\/slownik\/web-scraping\/"},"modified":"2026-08-04T09:20:33","modified_gmt":"2026-08-04T07:20:33","slug":"web-scraping","status":"publish","type":"slownik","link":"https:\/\/humes.pl\/en\/glossary\/web-scraping\/","title":{"rendered":"Web scraping"},"content":{"rendered":"<p>Web scraping is a technique for automatically collecting data from websites for further analysis. In market research, web scraping makes it possible to turn publicly available online information into structured analytical material &#8211; useful, among other things, for monitoring prices, product assortments, brand visibility, reviews, and changes in the competitive environment.<\/p>\n<h2>What is web scraping?<\/h2>\n<p>Web scraping is the process of automatically extracting and structuring data from websites using scripts, crawlers, or specialized software tools. It most often involves reading elements visible on web pages, such as product names, prices, descriptions, specifications, ratings, number of reviews, review content, availability information, or promotional messages, and then saving them in a format that allows further analysis.<\/p>\n<p>In a research context, web scraping is not just a technical solution. It is a method of collecting secondary data from the digital market environment. Its value lies in enabling observation of real market activity and commercial communication at a scale that is difficult to achieve through manual desk research. For this reason, web scraping for market research data is used wherever an up-to-date, comparable, and repeatable view of the market is needed.<\/p>\n<p>What is web scraping from the perspective of how it works? It usually includes several stages:<\/p>\n<ul>\n<li>identifying data sources and the structure of websites,<\/li>\n<li>defining the fields to be extracted,<\/li>\n<li>automatically collecting content from web pages,<\/li>\n<li>cleaning and standardizing the data,<\/li>\n<li>combining the data with other analytical sources,<\/li>\n<li>interpreting the results in the context of the research question.<\/li>\n<\/ul>\n<p><\/br> <\/p>\n<p>In market research, web scraping is especially useful when online data changes dynamically and needs to be tracked on a recurring basis. This applies in particular to e-commerce, marketplace platforms, classified ad services, price comparison sites, manufacturers&#8217; websites, forums, review portals, and industry media. This makes it possible to study the market not only on the basis of respondents&#8217; declarations, but also on the basis of digital traces and publicly observable phenomena.<\/p>\n<p>It is also worth emphasizing that web scraping does not mean unrestricted downloading of content from the internet. The scope and method of using the data must take into account applicable laws, website terms of use, personal data protection requirements, and ethical principles. In research practice, this means assessing the legality of the source, the purpose of processing, and the level of data identifiability.<\/p>\n<h2>Application of web scraping in practice<\/h2>\n<p>Web scraping is used wherever business decisions require a regular view of the market based on data updated in near real time. The method is used by market researchers, pricing analysts, marketing teams, e-commerce departments, product managers, and organizations monitoring the activity of competitors and business partners. The Hume Institute uses web scraping in projects where it is necessary to combine declarative data with observation of actual market offerings and communication.<\/p>\n<p>The most common applications of web scraping for market research data include:<\/p>\n<ul>\n<li>monitoring prices and promotions in online stores and marketplaces,<\/li>\n<li>analyzing assortments, availability, and changes in product portfolios,<\/li>\n<li>tracking the position of a brand and its competitors in search results or product categories,<\/li>\n<li>analyzing consumer opinions and product reviews,<\/li>\n<li>mapping ways of communicating offers, benefits, and marketing claims,<\/li>\n<li>identifying product trends and signals of changing demand,<\/li>\n<li>observing the job market, partnerships, geographic expansion, or the activity of new market entrants.<\/li>\n<\/ul>\n<p><\/br> <\/p>\n<p>In practice, the question of how to use web scraping in market analysis most often concerns not the data collection itself, but how to embed it meaningfully in the decision-making process. For example, in the retail industry, web scraping can be used to build price and promotion trackers. In the FMCG sector, it allows comparison of product visibility, descriptions, and the presence of packaging variants across different sales channels. In B2B research, it can support the analysis of supplier offers, technology categories, value communication, and changes in competitive positioning.<\/p>\n<p>Web scraping can also be an important complement to qualitative research. If a hypothesis emerges in individual interviews or focus groups about, for example, informational chaos in a category, ambiguous messaging, or promotional pressure, data collected from websites can verify that hypothesis and place it in a broader market context. In mixed-methods projects, this combination increases the validity of interpretation by confronting the respondents&#8217; perspective with observation of the actual shopping environment.<\/p>\n<h2>Web scraping and related methods<\/h2>\n<p>Web scraping operates within a broader ecosystem of data collection and analysis methods. It does not replace classic quantitative or qualitative research, but provides a different type of material &#8211; observational, behavioral in the sense of reflecting market activity, and embedded in the digital environment. This distinction is important, because a respondent&#8217;s declaration is not the same as a publicly available market trace recorded on websites.<\/p>\n<p>Web scraping is most often combined with the following approaches:<\/p>\n<ul>\n<li>desk research &#8211; when internet data serves as a structured extension of secondary source analysis,<\/li>\n<li>social listening &#8211; when, alongside data from websites and stores, user statements from social media are also analyzed,<\/li>\n<li>content analysis &#8211; when extracted descriptions, reviews, or messages are coded qualitatively or processed linguistically,<\/li>\n<li>tracking studies &#8211; when data collected cyclically shows changes in prices, offers, or market narratives over time,<\/li>\n<li>survey research &#8211; when respondents&#8217; declarative data is compared with the actual presentation of market offers,<\/li>\n<li>data triangulation &#8211; when different sources are used to cross-check conclusions.<\/li>\n<\/ul>\n<p><\/br> <\/p>\n<p>It is also worth clarifying how web scraping differs from similar concepts. It is not the same as web crawling, although the two terms are sometimes used interchangeably. Web crawling mainly refers to automatically navigating across pages and indexing resources, whereas web scraping focuses on extracting specific data from those resources. It is also not the same as API data collection, because with an API the data is made available by the system owner in a defined format, whereas in web scraping the data is extracted from the page interface or its code.<\/p>\n<p>From the point of view of market research methodology, web scraping has another important feature: it often generates unstructured or semi-structured data that requires normalization. This means that its value does not depend solely on extracting the content, but on the quality of preparing the data for analysis. Only at that stage can brands, categories, product variants, or price levels be compared reliably across sources.<\/p>\n<h2>Limitations and conditions for the proper use of web scraping<\/h2>\n<p>Web scraping is useful, but it should not be treated as an automatic substitute for other research methods. Its limitations result both from the nature of online sources and from legal and interpretive issues. In practice, this means that the quality of conclusions depends on a correctly designed analytical process.<\/p>\n<p>The most important limitations of web scraping are:<\/p>\n<ul>\n<li>the changing structure of websites, which can disrupt continuity of measurement,<\/li>\n<li>varying quality and comparability of data across services,<\/li>\n<li>the risk of misinterpreting data taken out of context,<\/li>\n<li>lack of access to some information hidden behind login walls, dynamic interfaces, or technical protections,<\/li>\n<li>the need to take website terms and legal requirements into account,<\/li>\n<li>limited usefulness when the key question concerns users&#8217; motivations, attitudes, or emotions.<\/li>\n<\/ul>\n<p><\/br> <\/p>\n<p>Therefore, the answer to the question of how to use web scraping in market analysis should always take the research objective into account. If the goal is to understand what is offered, how it is communicated, and how the online market is changing, web scraping can be very effective. If, however, the research is meant to explain why customers make certain decisions, it usually needs to be supplemented with interviews, surveys, or other data sources.<\/p>\n<p>A good practice is also to document the method of data extraction, the scope of sources, the collection frequency, and the data cleaning rules. Such transparency increases the credibility of the analysis and makes it possible to assess whether the results actually reflect market phenomena or merely the specifics of a given online source. That is why in mature research projects, web scraping is treated not as an end in itself, but as an element of a broader analytical process.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Web scraping is the automated collection of data from public websites for analysis. It allows prices, assortment and reviews to be observed faster and at a greater scale than manually.<\/p>\n","protected":false},"template":"","slowa_kluczowe":[],"class_list":["post-2724","slownik","type-slownik","status-publish","hentry"],"acf":[],"_wp_attached_file":null,"_wp_attachment_metadata":null,"wpml_media_processed":null,"_wpml_media_usage_in_posts":null,"_wp_attachment_context":null,"_oembed_35c905c64c03156f243b94f18c4eb80f":null,"_wp_attachment_image_alt":null,"rank_math_description":"Concept definition: Web scraping. Application in market research and methodology. Check the Hume's Institute glossary.","rank_math_focus_keyword":"Web scraping","rank_math_contentai_score":null,"_wpml_post_translation_editor_native":null,"_menu_item_type":null,"_menu_item_menu_item_parent":null,"_menu_item_object_id":null,"_menu_item_object":null,"_menu_item_target":null,"_menu_item_classes":null,"_menu_item_xfn":null,"_menu_item_url":null,"_wp_page_template":null,"rank_math_og_content_image":null,"_wp_trash_meta_status":null,"_wp_trash_meta_time":null,"_wp_desired_post_slug":null,"rank_math_primary_category":null,"_acf_changed":null,"wp_pattern_sync_status":null,"_form":null,"_mail":null,"_mail_2":null,"_messages":null,"_additional_settings":null,"_locale":null,"_hash":null,"_config_validation":null,"_wp_old_slug":null,"rank_math_internal_links_processed":"1","_top_nav_excluded":null,"_cms_nav_minihome":null,"_thumbnail_id":null,"_last_translation_edit_mode":null,"_wpml_word_count":"1535","_dp_original":null,"_edit_last":"9","_edit_lock":"1785828048:9","rank_math_seo_score":"70","_wpml_location_migration_done":null,"_wpml_media_duplicate":null,"_wpml_media_featured":null,"_wp_old_date":"2026-07-21","copied_media_ids":[],"referenced_media_ids":[],"rank_math_title":"Web scraping - definition | Hume's Institute","job_department":null,"_job_department":null,"job_location":null,"_job_location":null,"job_offer_external_link":null,"_job_offer_external_link":null,"footnotes":null,"inline_featured_image":null,"blog_podtytul":null,"_blog_podtytul":null,"blog_czas_czytania":null,"_blog_czas_czytania":null,"blog_dalsza_lektura":null,"_blog_dalsza_lektura":null,"slownik_krotka_definicja":null,"_slownik_krotka_definicja":null,"slownik_cytat":null,"_slownik_cytat":null,"slownik_na_stronie_glownej":"1","_slownik_na_stronie_glownej":"field_slownik_na_stronie_glownej","slownik_slowa_kluczowe":null,"_slownik_slowa_kluczowe":null,"slownik_w_praktyce":null,"_slownik_w_praktyce":null,"slownik_powiazane":"","_slownik_powiazane":"field_slownik_powiazane","slownik_kluczowe_punkty":null,"_slownik_kluczowe_punkty":null,"_links":{"self":[{"href":"https:\/\/humes.pl\/en\/wp-json\/wp\/v2\/slownik\/2724","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/humes.pl\/en\/wp-json\/wp\/v2\/slownik"}],"about":[{"href":"https:\/\/humes.pl\/en\/wp-json\/wp\/v2\/types\/slownik"}],"version-history":[{"count":1,"href":"https:\/\/humes.pl\/en\/wp-json\/wp\/v2\/slownik\/2724\/revisions"}],"predecessor-version":[{"id":2725,"href":"https:\/\/humes.pl\/en\/wp-json\/wp\/v2\/slownik\/2724\/revisions\/2725"}],"wp:attachment":[{"href":"https:\/\/humes.pl\/en\/wp-json\/wp\/v2\/media?parent=2724"}],"wp:term":[{"taxonomy":"slowa_kluczowe","embeddable":true,"href":"https:\/\/humes.pl\/en\/wp-json\/wp\/v2\/slowa_kluczowe?post=2724"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}