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Price Scraping using API Data Mining is a serious threat
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The information you provide to Verified Visitors is governed by the terms of our Privacy Policy
Price Scraping Bots systematically data mine pricing information from e-commerce websites and APIs, seeking to undercut prices and steal business from competitors. This can harm businesses, distort the market, create price erosion, and undermine consumer confidence. Most ecom websites have APIs that can be systematically data mined at large scale for the latest pricing and shipping data, per Zip code. These bots can then be extremely well targeted to undercut competitors dynamically. Large scale data mining of APIs can hurt the overall API performance, response times and lookups for legitimate customers, but the main effect is on the insidious competitive price erosion.
Consumers will often search for the cheapest deal for white goods with no brand loyalty. Price Scraping Bots, take advantage of this by optimizing pricing strategies to spot pricing gaps and promote their offerings to take maximum advantage of any pricing discrepancies.These automated bots allow them to monitor competitors' pricing strategies in pretty much real-time, which can provide a crucial edge in setting competitive prices, especially when combined with real-time advertising and social media campaigns highlighting the pricing differences.
Retail businesses have always monitored competitive pricing, from the adoption of mystery shoppers, to manually compiling databases. This was time consuming, expensive, and took months to complete, by which time, the pricing data was out-of date. The real-time massive capture of the entire API contents of the pricing database is a game-changer. Arbitrage opportunities can be spotted and instantly promoted with social media campaigns targeting the price differentials.
Most of the price scraping has gone off-page and instead exploits the widespread use of API based pricing engines. The latest bots use Generative AI bots to help fine tune their scripts, scrub and clean the data, as well as helping identify the arbitrage oppotunites with the pricing differentials in each market segment. Fine tuing these large models, offers competitors the ability to micro-target markets with much more precision than was possible.
Old school Bot detection uses fingerprint analysis to determine if the visitors is human or bot Most of the price scraping is API based, and all the visitors to API are automated. The traditional bot protections can’t tell the difference between automated genuine lookups and systematic API abuse. VerifiedVisitors employs behavioral detection to look for the serial data mining abuse and separate out the legitimate users from the abusers.
Hitting the APIs means that the data miners can easily hide in the large volumes of automated traffic hitting the APIs. Although it’s easy to rate limit the API, this affects all the legitimate users of the API, and doesn’t solve the API data mining abuse problem
The benefits extend beyond mere competitiveness. Price Scraping Bots play a pivotal role in optimizing pricing strategies, leading to increased revenue and customer satisfaction. Imagine a world where your pricing aligns perfectly with market demand—Price Scraping Bots make it a reality.
Please see our case study for how VerifiedVisitors helps protect our customers from API abuse from price scraping bots.
Small businesses can be just as much at risk compared to the largest retailers. Although not as frequently targeted, a small business may operate in a smaller geographical area, or with a niche product where competitive pricing is even more of an issue.
Scraping and data mining is nearly always in violation of the web site terms and conditions. In addition, depending on the jurisdiction local laws preventing network computer abuse may be applicable, but there is rarely any enforcement
Dynamic pricing involves adjusting prices based on demand and market conditions. Price Scraping Bots provide real-time data, enabling businesses to implement dynamic pricing strategies effectively.
Ethical considerations pose a challenge. Striking a balance between competitive intelligence and privacy is essential for responsible use.