by Filippo Gramigna
Q: With 20+ years of experience in programmatic advertising space, what specific pain points do you think advertisers encounter in the ad tech ecosystem?
Advertisers in the programmatic advertising ecosystem face numerous significant challenges. First, ensuring ad quality and brand safety is a never-ending challenge, with issues such as low viewability, ad fraud, and difficult-to-measure campaign impacts. Transparency is another major issue, as complex supply chains with multiple intermediaries frequently result in inflated costs and low ROI. Data fragmentation exacerbates the problem, making it difficult to gain unified insights or accurately track performance across channels. Regulatory pressures, particularly evolving data privacy laws and the phase-out of third-party cookies, force advertisers to develop new, compliant methods of targeting and tracking audiences. Furthermore, creative and ad fatigue – when users become disengaged with repetitive ads – remains a concern, requiring advertisers to find new, personalized content that resonates.
Q: How does the Smart Curation platform address and eliminate major problems in the ad tech industry?
Our Smart Curation platform effectively addresses key ad tech industry challenges by improving ad quality, transparency, and efficiency. It combats ad fraud by curating inventory from reputable sources and incorporating advanced fraud detection tools. The platform also ensures high ad viewability by prioritizing quality placements, providing improved performance insights, and providing real-time filtering to ensure brand safety. In terms of transparency, it eliminates unnecessary intermediaries via supply chain optimization (SPO), lowering costs and increasing ROI. The platform adheres to privacy regulations by utilizing cookieless solutions such as contextual targeting and first-party data, ensuring compliance while retaining effective targeting. Furthermore, it reduces programmatic complexity by automating processes, reducing manual work, and providing user-friendly tools for better campaign management.
Q: What are the common causes of ad wastage, and how can they be prevented?
Common causes of ad wastage include poor targeting, low viewability, ad fraud, over-frequency, and ineffective budget allocation. When ads are shown to irrelevant or overly broad audiences, engagement and conversions drop. Ads placed in non-visible areas or on low-quality sites lead to wasted impressions. Ad fraud, such as bots and fake traffic, further drains budgets. Over-exposure causes ad fatigue, and misaligned creative leads to low engagement. Additionally, overspending on low-performing channels or poorly timed ads results in poor ROI. To prevent ad wastage, advertisers should use granular data and intent-based targeting to reach the right users. Optimizing ad placement by choosing high-quality inventory with good viewability and using viewability tracking tools is essential. Adopting anti-fraud measures and controlling ad frequency with frequency caps can help avoid overexposure and keep ads fresh. Lastly, regularly adjusting budgets and adopting smart bidding strategies ensures more effective spend allocation.
Q: How do cookieless solutions impact ad targeting and personalization?
Loss of cookie signals impacts ad targeting and personalization by limiting advertisers’ ability to track users across different websites, which affects the creation of unified user profiles and cross-site retargeting. To adapt, advertisers are shifting to first-party data and universal IDs (e.g., Unified ID 2.0) for targeting within their owned ecosystems. Additionally, cookie loss reduces the ability to target based on browsing behavior, so advertisers are increasingly relying on contextual targeting and AI-driven content analysis to ensure relevance based on page content. First-party retargeting within owned domains and publisher-led ecosystems helps maintain some retargeting capabilities. As privacy regulations tighten, data collection is restricted, but solutions like consent-based marketing and privacy-compliant tools, such as Google’s Topics API, allow for group-based targeting while respecting user privacy. Lastly, cookieless identity solutions focus on deterministic data like logins, allowing advertisers to enhance personalization while maintaining privacy through login-based data and data clean rooms.
Q: How can AI enhance the efficiency and effectiveness of ad curation?
AI improves the efficiency and effectiveness of ad curation by automating, optimizing, and personalizing processes at large scale. It ensures contextual relevance by analyzing page content and dynamically adjusting ad placements to increase engagement. AI also allows for precision targeting by analyzing large amounts of user data to create specific audience segments and predict behavior, resulting in more accurate ad targeting. AI uses dynamic creative optimization to personalize ad elements such as headlines and images in real time, increasing engagement. Furthermore, AI automates complex tasks like bidding, reporting, and optimization, allowing for more efficient scaling of ad campaigns and overall performance.
Q: How can the ad tech industry as a whole move towards more sustainable practices?
The ad tech industry can transition to more sustainable practices by implementing measures that reduce environmental impact while increasing transparency and efficiency. One critical step is to optimize energy use by increasing data center efficiency, implementing renewable energy, and utilizing edge computing to reduce energy consumption in ad processing and delivery. The industry can also streamline the supply chain using supply path optimization (SPO), which reduces inefficiencies and wasted impressions. Promoting sustainable metrics, such as carbon footprint transparency and sustainability scores, can help media buyers make more environmentally conscious decisions. Finally, incorporating environmental, social, and governance (ESG) practices into business models and working with regulators can strengthen the industry’s commitment to sustainability.
Original published on: TechEdge AI
