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Advertising expenditure in e-commerce reached record levels in 2024, while conversion rates stagnated or even declined in many areas. Behind this discrepancy lies a massive problem that increasingly challenges retailers financially: click fraud through automated bots. According to the Imperva Bad Bot Report 2025, 59 percent of all traffic on retail websites is generated by malicious bots. This figure makes clear that online retailers are not only competing against real competitors but increasingly against digital attackers who systematically devalue their advertising budgets.
The economic impact is substantial. When more than half of all website visitors are not potential buyers but automated programs, massive budget losses occur. Every click on an advertisement costs money, regardless of whether a human or a bot is behind it. For e-commerce companies, this means paying for traffic that can never generate revenue. Average budget savings through effective click fraud prevention range from 10 to 15 percent, though in particularly affected cases, losses can be significantly higher.
The New Dimension of the Bot Problem in E-Commerce
The e-commerce sector is experiencing a fundamental shift in the threat landscape in 2024. The analysis documents that the share of advanced bot attacks in retail increased from 52 percent in 2023 to 59 percent in 2024. This development shows that attackers are continuously refining their methods and increasingly relying on sophisticated techniques that can bypass conventional protection mechanisms.
Particularly noteworthy is the role of artificial intelligence in this development. According to the report, automated traffic has overtaken human-generated traffic for the first time in a decade and now accounts for 51 percent of all internet traffic. Of this automated traffic, 37 percent consists of malicious bots, a significant increase from 32 percent the previous year. The availability of powerful AI tools such as ChatGPT, ByteSpider Bot, and ClaudeBot now enables even less technically skilled actors to develop and deploy bot attacks.
The consequences for online retailers are multifaceted. Bot traffic not only leads to direct financial losses through wasted advertising expenditure but also impairs the quality of marketing analytics. When more than half of website traffic comes from bots, metrics such as bounce rates, dwell time, and conversion funnel analyses are systematically distorted. Marketing managers then make decisions based on flawed data, leading to inefficient budget allocations and missed growth opportunities.
Concrete Attack Scenarios and Their Financial Impact
The methods by which bots attack e-commerce websites are diverse and target different vulnerabilities. The analysis identifies several main attack vectors that together represent a significant financial risk.
Data scraping accounts for approximately 31 percent of all bot attacks. Automated programs mass-extract product data, prices, and inventory information from online shops. Competitors use this information to undercut prices or copy assortments. For affected retailers, this means a direct loss of competitive advantages and often declining margins when forced into price wars.
Payment fraud, the second most common form of attack at 26 percent, directly targets checkout processes. Bots manipulate payment transactions to conduct fraudulent transactions or misuse promotional campaigns. The financial consequences are immediate: stolen money, chargebacks, and damaged customer relationships. Added to this are increased costs for fraud prevention and customer service.
Account takeover attacks account for approximately 12 percent of bot activities and have increased by 40 percent year over year. Bots take over legitimate customer accounts through credential stuffing. Attackers use stolen credentials from data breaches to gain access to customer accounts. For retailers, this not only creates direct financial losses through fraudulent orders but also massive reputational damage and loss of customer trust.
Scalping, which accounts for approximately 11 percent of attacks, particularly affects retailers with limited products or time-sensitive offers. Bots purchase or reserve large quantities of coveted items in seconds before real customers even have a chance to access them. This leads to frustrated customers, negative reviews, and ultimately customer attrition.
Intensification Through AI-Powered Attack Tools
The integration of artificial intelligence into bot attacks represents a new level of threat. The data shows that an average of two million AI-powered cyberattacks were blocked per day in 2024. These attacks are characterized by significantly higher sophistication and adaptability.
ByteSpider Bot, an AI-powered tool, was responsible for 54 percent of all AI-based attacks in 2024. The widespread availability of these tools dramatically lowers the barrier to entry for attackers. While previously comprehensive technical knowledge was required to conduct effective bot attacks, modern AI tools now enable even actors with minimal technical understanding to launch complex attacks.
This development also explains the observed increase in simple bot attacks from 40 percent in 2023 to 45 percent in 2024. AI automation makes it possible for even basic bot attacks to be conducted on a large scale and with high frequency. For e-commerce companies, this means they must defend not only against highly specialized attackers but against a broad mass of actors who can cause significant damage with minimal effort.
The bots learn from failed attempts and continuously adapt their strategies. They analyze which security measures led to their blocking and return with refined techniques. This adaptability makes traditional, rule-based protection mechanisms increasingly ineffective and requires dynamic, AI-powered countermeasures.
Hidden Costs Through Distorted Marketing Metrics
In addition to direct financial losses through wasted advertising expenditure, bot traffic causes considerable indirect costs through the distortion of marketing metrics. When decisions are based on false data, the damage multiplies.
A concrete example from practice impressively illustrates this problem. A global staffing agency invested several hundred thousand dollars in digital marketing campaigns and recorded high traffic on their website but practically no results. An analysis revealed that 83 percent of website traffic was generated by malicious bots. Marketing analytics showed seemingly successful campaigns, but in reality, almost all traffic was worthless.
For e-commerce companies, this data distortion has far-reaching consequences. Conversion rates are systematically distorted downward when the denominator is inflated by bot visits. This leads to false conclusions about the performance of landing pages, product pages, or checkout processes. Marketing managers then possibly optimize areas that are not problematic while real weaknesses remain undetected.
Budget allocation between different advertising channels is also distorted by bot traffic. When certain campaigns are disproportionately clicked by bots, they appear in analytics as particularly traffic-heavy, even though they actually generate little qualified traffic. Budgets are then reallocated to the wrong channels, undermining the efficiency of the entire marketing strategy.
Customer journey analytics also suffers from bot contamination. When bots systematically take certain paths through the website, they distort the picture of how real customers behave and which touchpoints are actually purchase-decisive. This can lead to misguided investments in content, design, or functionality.
Strategies for Defending the Advertising Budget
Given the dimension and complexity of the bot threat, e-commerce companies need a multi-layered approach to defending their advertising budgets. Various concrete measures have proven particularly relevant for reducing click fraud.
Risk identification is at the beginning of every effective strategy. Retailers must understand which areas of their website and which marketing activities are particularly vulnerable to bot attacks. Product launches with limited quantities particularly attract automated attackers. Similarly, login areas, checkout forms, and gift card functions are preferred attack targets. Identifying these vulnerabilities enables targeted reinforcement of security measures at critical points.
Monitoring traffic patterns provides valuable indications of bot activity. Sudden, unexplained traffic spikes, especially on specific URLs, are often indicators of bot attacks. Unusually high bounce rates or low conversion rates can also indicate non-human traffic. Defining a baseline for normal traffic behavior enables rapid detection and response to anomalies.
Deploying specialized click fraud protection systems has become indispensable. Traditional measures such as simple CAPTCHAs are no longer sufficient to stop sophisticated, AI-powered bots. Modern solutions like Ads Defender use machine learning, behavioral analysis, and advanced detection methods to distinguish between real users and bots. These systems continuously learn and adapt to new attack methods, typically saving 10 to 15 percent of advertising budgets on average.
A dynamic, event-based approach to implementing protection measures can increase effectiveness. Instead of permanently activating all defense mechanisms, certain techniques should be reserved for critical moments, such as product launches or major sale events. After the event, these measures can be deactivated again, preventing attackers from analyzing protection mechanisms and developing circumvention strategies.
Awareness of global data breaches and credential dumps is also important. When large amounts of access credentials become available on the darknet, the risk of credential stuffing attacks increases dramatically. Multi-factor authentication for login areas, payment processes, and password resets provides an additional protective barrier against these attacks.
Continuous monitoring and adjustment of protection measures is crucial. Bots are constantly evolving, and what works today may already be ineffective tomorrow. Regular audits of bot activity, analysis of attack patterns, and adjustment of security strategy are necessary to remain protected in the long term.
For e-commerce companies that want to effectively protect their advertising budgets from click fraud, it is essential to recognize the extent of the problem and act proactively. The current figures make clear that bot traffic is not a marginal phenomenon but a central challenge for the entire online retail sector. With the right strategies and tools, however, significant budget savings can be realized while simultaneously improving the quality of marketing data. In an increasingly competitive market, this can make the decisive difference.
