Anomaly Detection as a Tool for Media Operations

The digital advertising market has experienced incredible growth in recent years, becoming a crucial component of the global economy. This growth can be attributed to the shift from analog to digital and the programmatic management of channels such as Digital-Out-of-Home, Audio, TV, and Print. 

The Ambivalence of Growth

Digital marketers and participants in the programmatic ecosystem are excited about these developments. However, with growth comes new challenges and risks, particularly in terms of anomalies that can compromise the integrity of the advertising industry.

Anomalies, also known as outliers, are unusual or abnormal events within data streams. They can occur due to technical or human errors in campaign setups or throughout their lifecycle, leading to overspending or wasted budgets.

The combination of rapid budget growth and the integration of traditional channels into the programmatic ecosystem has contributed to the emergence of costly anomalies. Additionally, as the workload of digital units increases, the role of media managers becomes increasingly technical, yet digital experts remain in short supply. Therefore, alternative solutions are needed to meet the rising demand for digital resources with sufficient capacity.

Software-Based Solutions to Address the Talent Shortage

The talent shortage is a cross-industry societal challenge, partly attributed to demographic changes. Finding young talents, especially in digital professions, is a problem. According to the Institute for the German Economy, there will be a shortage of over 106,000 workers in digital professions by 2026. This is a significant issue in digital marketing.

Channels that have experienced rapid growth in recent years and are expected to continue growing are particularly affected by this “talent shortage.” The holistic digital realization of the media mix has led to increased demand for specialists in SEM/SEO, Paid Social, and Programmatic.

Software-based solutions mitigate the talent shortage by enabling more efficient resource utilization, both in terms of time and money. In the digital advertising industry, the talent shortage can be viewed not only as a challenge but also as an opportunity for software solutions as they alleviate the entire campaign realization value chain. Otherwise, the talent shortage could become a major contributor to the increased risk of anomalies in digital campaign management due to errors or understaffing.

Consequences of Anomalies and Their Causes

Human errors and technical hurdles are responsible for many overspends, deviations from media standards, and other anomalies in campaign realization.

In the media-buying ecosystem, these issues can have significant effects on campaign outcomes, including:

  • Budget and resource loss: Incorrectly placed or qualitatively incorrect campaigns can waste advertisers’ or agencies’ money and time.
  • Damage to brand image and loss of trust: Placing ads in inappropriate or unethical contexts can harm a brand’s image and reduce the target audience’s trust in the company.
  • Lack of transparency: Insufficient information about the media-buying process or a lack of insight into actual placements (e.g., Supply Path Optimization) can lead to problems.
  • Reduced campaign effectiveness: Delivering ads to the wrong audience or in inappropriate contexts can diminish campaign effectiveness (Brand Safety, Viewability, Position).
  • Ad Fraud: Fraudulent practices such as bot traffic, ad stacking, or viewability fraud can reduce advertising effectiveness.

To prevent these consequences from burdening digital marketing unnecessarily, anomaly detection serves as a tool for more intelligent resource utilization.


Anomaly Detection in Digital Advertising

Anomaly detection is a method used to identify unusual patterns or events in data. This technique has been employed for various applications for a long time, including credit card fraud detection, anomaly detection in industrial processes, and network monitoring to detect hacker attacks or technical malfunctions.

By applying this technology, advertisers and advertising networks can identify and take measures to minimize or prevent unwanted activities. This contributes to improving the quality of advertising campaigns and maximizing advertising expenditure efficiency. Anomaly detection not only identifies deviations but also enables higher quality media operations and replaces the traditional “two sets of eyes” principle.

In addition to qualitative aspects, the technology also enables time savings. Campaign managers can quickly respond to changes in user behavior, protect against faulty campaign setups, or address unexpected events without extensive manual analysis. Moreover, it can uncover relationships within data streams that the human mind may not recognize.

Apart from the factors mentioned above, anomaly detection serves additional purposes:

  • Historical campaign data for advertisers can be translated into deterministic data, forming a framework of media-buying patterns. Anything that deviates from this framework can be identified as an anomaly. This pattern recognition not only protects advertisers but also ensures strict adherence to defined media standards.
  • Performance outliers can be identified, making anomaly detection a tool for optimizing campaigns, regardless of whether it involves Search, Paid Social, or Programmatic – the principle remains the same. Ad fraud can also be identified with this technology. Supported by all these potential risks, anomaly detection helps strengthen the relationship between clients and agencies.
  • These intelligent solutions can also be used in campaign management to software-based responses to the talent shortage. By automating processes for monitoring marketing campaigns and detecting deviations from normal patterns and behaviors, substantial time savings are achieved. Agencies and advertisers can shift their resources to meet customer needs and focus more on marketing strategy tasks. This move reduces the daily grind of analyzing Excel files or double-checking DSPs and leverages existing technologies.
Facilitating Day-to-Day Operations Through Process Automation in Campaign Management

Anomaly detection can be understood as one component of automating campaign management. However, employees who operate media planning tools, set up campaigns in DSPs, create reports, make optimizations, or attend regular meetings will remain the primary resource in digital campaign management. To address the ambivalence of growth and the increasingly complex digital ecosystem, possibilities for automating these processes must be explored.

In addition to anomaly detection, other building blocks may involve pushing media plans into DSPs via API interfaces to largely eliminate human error sources in setup. Anomaly detection can then focus more on identifying technical errors and, for example, shifting budgets between available and sold-out products. Anomaly detection can be used polyvalently within media planning tools, ad servers, DSPs, and SSPs. This contributes to media professionals coping with the increasing workload and the need for efficiency in parallel.

In the recent report from DMI with The Economist titled “Perpetual Evolution,” 74% of senior marketers say that marketing companies face an alarming talent gap due to a lack of digital capabilities. New platforms, technological advances, and executive tools are constantly being introduced to the digital advertising industry. Many professionals find it harder and harder to keep up with the rapid pace of these developments as they acquire new skills. Digital advertising requires a variety of skills, including content creation, social media management, programmatic advertising, SEO, and more. Traditional education may not fully prepare individuals for the complexities of digital marketing. The supply of qualified candidates frequently outnumbers the demand for skilled digital marketers. Unfilled positions and higher demands for skilled workers result from the talent shortage. A survey from Forbes revealed that 62% of companies had unfilled job positions in digital marketing due to a lack of qualified candidates.

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