A new report from Akamai Technologies has unveiled alarming statistics about the prevalence and impact of web scraper bots on businesses, particularly in the e-commerce sector. An astounding 42 percent of overall web traffic is now generated by bots, according to the cloud computing giant.
The report reveals that as the internet becomes increasingly dominated by automated traffic, businesses are facing a growing threat from malicious bots. Akamai Technologies, a leading cloud company, has released its latest State of the Internet (SOTI) report, titled “Scraping Away Your Bottom Line: How Web Scrapers Impact e-commerce,” shedding light on the pervasive issue of web scraping bots and their detrimental effects on online businesses.
The report’s findings are striking: bots now account for a staggering 42 percent of overall web traffic, with 65 percent of these bots classified as malicious. This surge in bot activity is particularly concerning for the e-commerce sector, which relies heavily on revenue-generating web applications and is therefore most vulnerable to high-risk bot traffic.
Patrick Sullivan, CTO of Security Strategy at Akamai, emphasized the seriousness of the issue, stating, “Bots continue to present massive challenges resulting in multiple pain points for app and API owners.” He highlighted the various ways in which scraper bots can harm businesses, including data theft and brand impersonation.
The report identifies several key ways in which scraper bots are being weaponized against businesses. These include competitive intelligence gathering, inventory hoarding, and the creation of imposter sites. Such activities not only impact a company’s bottom line but also degrade the customer experience.
One of the most concerning developments highlighted in the report is the rise of AI botnets. These advanced bots have the capability to discover and scrape unstructured data and content, even when it’s presented in inconsistent formats or locations. Moreover, they can leverage business intelligence to enhance their decision-making processes, making them increasingly difficult to detect and mitigate.
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