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What is Price Scraping?

In the digital-first economy, where consumers use comparison tools and websites to compare prices for the products and services they wish to buy, it is becoming increasingly challenging for businesses to acquire price conscious customers.

Price scraping has emerged as an effective tool that enables businesses to monitor a competitor’s pricing strategy and use this information to offer lower prices in order to attract more customers.

The process of using bots for automated extraction of pricing data and other valuable information including picture, product descriptions, categories of products, usually from eCommerce, travel, and hospitality websites is called price scraping.

Who uses price scraping?

Both businesses and consumers engage in price scraping. While consumers scrape prices to find cheapest rates for a specific product of interest, businesses use price scraping to automatically scan competitors’ product prices and adjust the prices of their own products.

For instance, travel companies gather information about hotel prices offered by their competitors; financial services providers engage in price scraping to understand the business model of an organization or to aggregate information about stock prices, credit ratings, government decisions, market sentiment analysis; eCommerce platforms collect pricing information about a range of products such as clothes, accessories, sportswear, furniture, and so forth. A start-up may scrape data to improve the product it is trying to create.

Uses of price scraping

Given the tremendous competition among digital businesses to expand their consumer base, they need market and pricing intelligence that can help them price their products in such a way that can attract price-sensitive customers and help increase revenues.

Price scraping allows them to harvest data and use insights from this data to tweak their own pricing strategies and offer products at reduced prices as compared to their competitors. Using price scraping, digital businesses can:

  • Analyze customer behavior: To create pricing strategies based on the consumers’ purchase behaviors and the prices they are likely to pay for specific products.
  • Analyze competitor strategies: To tweak pricing strategies according to the competitor’s techniques for competitive advantage.
  • Build customer loyalty: By offering lower prices, businesses can build a positive price perception that can help build customer loyalty.
  • Gain competitive advantage: By offering lower prices to customers and negotiating better deals with business partners and vendors.

How does price scraping work?

Manual scraping is a tedious and time-consuming exercise which is now being replaced with automated price-scraping. The easy availability of bots-as-a-service is not only enabling faster price scraping but also at scale. Attackers can use specialized bots to quickly scrape prices of specific product categories, maintain real-time price repositories of several products, and track the price changes so that the entire data is current.

Several tools are also available to facilitate price scraping, which usually involves two steps:

  • Attack the target website: Using bots-as-a-service or botnets, attackers can program their bots to access the target website and track price changes at specified intervals, ranging from seconds, minutes, hours to days.
  • Scrape data: The bots not only extract data but also engage in data scraping by creating databases and keeping them updated. More advanced bots can be instructed to automatically use this pricing information and undercut prices, say on a comparison website.


Price scraping tools reduce the time and effort

Businesses engaging in price scraping can choose to build in-house software that allows them to create bespoke price scrapers that can harvest relevant data according to their marketing and pricing strategies.

However, given the costs and the technical skills required to create in-house price scraping scripts, bots are becoming more popular to scrape prices from targeted digital platforms.

These bots can be programmed to download the file with the list of URLs and access them to extract data into spreadsheets. On platforms that require human interaction, advanced bots with human-like capabilities are used. These advanced bots not only scrape pricing data but can also compare the data with other databases, update them, and send the data to specific users.


In addition to bots-as-a-service, that allow businesses to outsource price scraping services, there are several tools that facilitate automated price scraping. Some of these tools allow free price scraping for a certain number of competitors and web pages while others are available at subscription. They often use artificial intelligence and machine learning that make it easy to analyze the harvested data. They may include features such as IP rotation, scheduling, and email notifications, and even bypass anti-scraping mechanisms. Many price scraping tools are accompanied by online support apart from demos and tutorials.

Some of the common price scraping tools include: HTTrack, Scrapy, Prisync, Scrapingdog, ScraperAPI, Zyte, ProWebScraper, Octoparse, and Price2Spy among others.

Price scraping is a growing challenge

Price scraping is a growing challenge for digital businesses. This is because bad bots accessing a digital platform can result in the compromise of the overall security of the platform. Price scraping can:

  • harm price-sensitive industries such as ecommerce, travel and hotels, as it can lead to unfair advantages for the competitors if pricing strategies of certain platforms are breached
  • overwhelm websites and slow them down to the point where it becomes difficult for genuine consumers to access the website. This lack of access can impact conversion rates and eventually the revenues for the impacted businesses
  • lead to loss of time and effort in reviewing and revising the marketing and pricing strategies
  • increase operational costs

To protect their platforms from automated price scraping attacks, businesses are using measures to restrict the extent of scraping on their websites. These include banning IPs, using dynamic content, and CAPTCHAs among others. However, these measures may prove counterproductive as they may reduce the brand exposure to crawlers.

How can businesses prevent price scraping?

To protect their digital platforms – websites, apps, APIs – from bot-driven price scraping, businesses need robust bot management solutions that can effectively block bots of various sophistication levels. This is especially essential in view of the advanced human-like capabilities that bots continue to gain.

Using legacy or dated bot detection tools will only add to the challenge as these subpar solutions cannot keep pace with the evolving bot technology.

Put a stop to price scraping with Arkose Labs

Fighting a moving target is never easy. As bots become increasingly intelligent and acquire human-like capabilities, businesses need an effective approach that blocks these bad bots for good.

Arkose Labs empowers its partners to instantly stop bot-attacks with the proprietary challenges of Arkose MatchKey, designed to meet modern threats head on, including human-assisted bots. Instead of blocking any user, Arkose Labs uses context-based 3D challenges to accurately identify bots and deter them permanently without damaging user experience. With thousands of variations, these challenges are easy and fun for genuine human users, whereas bots and automated scripts fail instantly.

These context-based challenges are hard to solve and would require more than 100 days of human effort to solve using machine learning. This means automating the solution for each of the unique challenges would need attackers to spend disproportionate amounts of time, effort and resources, rendering the attack economically worthless. With such high barriers to entry, price scrapers would be forced to move on to an unprotected target.

Further, to help our partners make efficient data-backed decisions and protect their digital platforms from bot-driven price scraping, we share detailed and actionable insights complete with details of why a session was scored risky and the anomalies found. These insights empower security teams to ward off complex bot attacks and ensure long-term protection from price scraping, while preserving great consumer experience.


The process of automated extraction of pricing data and other valuable information from a digital platform is called price scraping.

Consumers use price scraping to find cheaper products and services for purchase. Businesses engage in price scraping to get insights into their competitors’ pricing strategies and price their products accordingly.

Price scraping is considered legal if the prices are available in the public domain. That said, depending on the use of the extracted data, the activity may be considered illegal. Further, if the ‘terms of use’ of a digital platform – website, app, API – prohibit scraping of their publicly available pricing data, then it is illegal.

Prices can be scraped either manually or using bots. Since manual price scraping requires enormous amounts of human effort and time, bots are used to speed up the process and achieve scale.

Price scraping can sometimes result in overwhelming the website, preventing customers from accessing it. This can result in bad user experience and in worst cases, customer churn.

Using digital intelligence such as IP address, browser details, and user behavior, among others websites can detect suspicious activity and take appropriate countermeasures.

Businesses can define the ‘terms and conditions’ of using their digital platforms – websites, apps and APIs. They can clearly state prohibition of accessing their data. Further, to prevent price scraping, businesses can use robust bot management solutions such as Arkose Enforce that identify and block bots with the greatest accuracy.

GDPR in the European Union and CCPA in the US prohibit illegal price scraping.

Arkose Labs uses proprietary challenges to deter bot-driven price scraping for good. Bots of various capabilities instantly fail when faced with these challenges. To clear them at scale, attackers would need to spend enormous amounts of effort, time and resources trying to automate the solution for each of the challenges. This delay and increased costs render the attack not worthwhile, forcing adversaries to move on to other targets that are less protected and leave our customers alone for the long-term.