scraping
Definisjon
Handlingen eller prosessen med å fjerne et overflatelag ved å gni eller skrape med et skarpt eller slipende verktøy.
Synonymer4
Antonymer3
Eksempler på bruk1
The scraping of paint from the old wall took several hours; She heard the scraping sound of metal against metal; The scraping of ice on the windshield was necessary before driving.
Etymologi og opprinnelse
Derived from the verb 'scrape,' which originates from Old English 'scrāpian,' meaning 'to scrape, scratch, or shave,' related to Old Norse 'skrapa' and Middle Low German 'scrapen.' The suffix '-ing' forms a noun indicating the action or process.
Relasjonsmatrise
Utforsk forbindelser og sammenhenger
Growth hacking platform
is a tool for
Ad monitoring software
Ad monitoring software systematically collects and analyzes competitors' or market-wide advertising data to inform strategic decisions in marketing and business. Scraping is often the underlying technical method enabling this process by automatically extracting ad content, metadata, placement, and performance indicators from various digital platforms (websites, social media, ad networks). Without scraping, ad monitoring software would struggle to gather timely, large-scale, and diverse ad data efficiently. Specifically, scraping scripts or tools crawl through competitor websites, social media feeds, or ad libraries to capture live or historical ad creatives, copy, targeting parameters, and frequency. This scraped data is then processed by ad monitoring software to identify trends, benchmark performance, detect shifts in competitor strategies, and optimize campaign targeting or messaging. Thus, scraping acts as the data acquisition engine that powers the actionable insights generated by ad monitoring software, making their relationship both practical and operationally critical in digital strategy and competitive intelligence.
ad exchange
An ad exchange is a digital marketplace where publishers sell ad inventory programmatically to advertisers in real-time auctions. Scraping, in the context of marketing and digital strategy, involves extracting large volumes of data from websites or platforms, often including competitor pricing, ad placements, or audience behaviors. The relationship between ad exchanges and scraping emerges primarily in data intelligence and competitive analysis. Marketers and businesses may scrape data from ad exchanges or associated platforms to monitor real-time bidding prices, identify trends in ad inventory availability, or analyze competitor ad strategies. This scraped data can then inform bidding strategies, budget allocation, and targeting decisions within the ad exchange environment, enhancing campaign effectiveness. Conversely, ad exchanges may implement anti-scraping measures to protect proprietary data and maintain marketplace integrity. Thus, scraping acts as a tool to extract actionable insights from ad exchanges, enabling more informed digital advertising strategies, while ad exchanges serve as a critical data source for scraping activities focused on market intelligence and optimization.
Ad creative testing
Ad creative testing involves systematically experimenting with different versions of advertisements to identify which elements (such as images, copy, or calls-to-action) perform best in driving engagement or conversions. Scraping, in this context, refers to the automated extraction of competitor ad creatives, audience engagement data, or platform trends from social media, ad libraries, or other digital sources. The relationship between the two lies in how scraping can provide a rich dataset of real-world ad examples and performance signals that inform and accelerate the ad creative testing process. By scraping competitor ads and their engagement metrics, marketers can identify high-performing creative patterns, messaging strategies, or visual styles to incorporate into their own test variants. This reduces guesswork and enhances the relevance of test creatives, enabling more targeted and data-driven experimentation. Furthermore, scraping can reveal emerging trends or shifts in audience preferences, allowing marketers to adapt their creative tests proactively rather than reactively. In essence, scraping acts as a continuous intelligence feed that refines the hypotheses and creative directions tested in ad creative experiments, making the testing process more efficient and aligned with market dynamics.
a/b-testing
In marketing and digital strategy, A/B testing and scraping intersect through the use of scraped data to inform hypothesis generation and optimization targets for A/B tests. Scraping enables marketers to collect competitive intelligence, such as pricing, promotional offers, content formats, and user engagement signals from competitor websites or industry benchmarks. This external data can be analyzed to identify patterns or elements that perform well in the market, which then become variables or variants to test in A/B experiments on their own platforms. For example, scraping competitor landing pages to extract headline styles or call-to-action phrasing can inspire test variants that aim to improve conversion rates. Additionally, scraping user-generated content or reviews can reveal customer pain points or preferences that shape the design of A/B tests focused on messaging or feature prioritization. Conversely, results from A/B tests can guide what data to scrape next by highlighting which competitor tactics are worth monitoring more closely. Therefore, scraping acts as a data sourcing mechanism that feeds into the ideation and refinement process of A/B testing, making the experimentation more targeted and contextually relevant to the competitive landscape.
Ad copy
In digital marketing and business strategy, scraping is often employed to collect large volumes of competitor ad copy from platforms such as Google Ads, Facebook, or other digital ad networks. By programmatically extracting this ad copy, marketers can analyze messaging trends, keyword usage, call-to-action effectiveness, and creative strategies that competitors use. This data-driven insight enables marketers to craft more compelling and targeted ad copy by identifying gaps, successful angles, or underutilized value propositions in the market. Additionally, scraping ad copy at scale allows for continuous competitive intelligence, enabling rapid iteration and optimization of one’s own ad copy based on real-time market dynamics. Thus, scraping acts as a foundational research method that directly informs the development and refinement of ad copy, making the relationship between them a practical feedback loop where scraped data guides creative decisions and testing in digital campaigns.
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