Moat’s exit from the brand safety and verification market comes at a pivotal time for the industry. For years, the triumvirate of IAS, DV, and Moat dominated this space, adhering to a common technological framework centered on risk elimination. Their mantra was clear: block ads from unsafe environments, whether it be non-human traffic, non-viewable placements, or brand-unsafe content. But this approach, while necessary, has reached its limit. It’s time for a paradigm shift in ad verification – one that moves from mere risk mitigation to active value creation; from avoiding the environments where brands shouldn’t appear to finding the ones where they should.
Change is already on the horizon. A recent TechValidate survey revealed that 17% of marketers are now using Mediaocean’s verification solution, Protected, signaling a growing appetite for new approaches that align with this paradigm shift.
The limitations of the risk-averse approach
The current model of ad verification can be likened to building an impenetrable fortress around a brand. While it keeps the threats at bay, it also isolates the brand from potentially valuable interactions. This risk-averse strategy has led to several unintended consequences:
- Over-blocking:
In the quest to avoid all risk, current systems often cast too wide a net, excluding safe and relevant content that could have been valuable to advertisers, while publishers see their inventory misclassified and unfairly demonetized – all because of an arbitrary keyword match.
Advertiser-Publisher Friction:
Traditionally, brand safety has been used as a point of leverage for the buy side, creating an imbalance between advertisers and publishers. The friction caused by makegoods and short-term adjustments is unsustainable for the long-term publisher-advertiser relationship.
Stagnant Innovation:
The dominance of IAS and DV has stifled innovation. With few alternatives, these companies haven’t needed to evolve. They’ve remained entrenched in an outdated model, and the lack of competitive pressure has kept the entire industry from moving forward.
Missed Opportunities:
By concentrating solely on what to avoid, the industry has overlooked the potential to actively seek out and capitalize on high-value placements.
The path forward: from risk avoidance to value creation
Moat’s exit presents a rare chance to redefine ad verification and shift away from a narrow focus on risk. We now have the technology to make this shift possible. Advancements in AI and machine learning enable us to analyze content with much greater depth and nuance than ever before, providing a more sophisticated understanding of context and quality. This foundation allows us to move beyond the question of “What should we avoid?” and instead ask, “What can we actively pursue to enhance outcomes?” Here’s how this paradigm shift can unfold:- Embracing Context and Quality:
It’s time to move beyond basic keyword blocklists. With advancements in AI and machine learning, verification providers can evaluate content with greater depth, taking into account both context and quality. This will enable more precise placements, allowing brands to reach audiences in environments that are not only safe but also highly relevant.FosteringCollaboration, Not Conflict: Verification should no longer be a tool that pits advertisers against publishers. Instead, it should be a shared resource that empowers publishers to improve content quality and meet advertiser expectations. A collaborative approach will lead to a healthier ecosystem for all stakeholders.
Incentivizing Premium Content: A positive, quality-driven model incentivizes publishers to produce premium content that attracts top-tier advertisers. The rise of “Made-for-Advertising” (MFA) sites – low-quality, AI-generated content designed to pass through existing verification filters – is a symptom of the current system’s flaws. A more nuanced model should reward high-quality content and help reward human creativity and hard work – especially in the form of journalism, which is often unfairly demonetized by the old approaches.
Measuring Positive Impact: Instead of focusing solely on risk metrics (eg fraud rates, brand safety violations), the industry should develop new KPIs that measure the positive impact of ad placements. This could include metrics like content relevance scores, audience engagement rates, and brand lift indicators.
Adopt Context-Aware Safety Standards: Safety is not a one-size-fits-all concept. What is appropriate for one brand may not be suitable for another, depending on context, audience, and campaign goals. Moving toward context-aware standards allows for flexibility and better alignment with specific brand needs.
