Filament Logo
free audit

Advertising Technology

Back to main blog
Demand Gen vs. Video Campaigns

Optimizing Demand Gen vs. Video Campaigns for Specific Business Goals

To get the most from your video campaigns, align the algorithm’s objective with your business goals. Use Demand Gen for lower-funnel actions like leads and conversions, where intent and data signals drive performance. Choose audience-targeted video for upper-funnel goals like brand awareness and reach. Use Contextually targeted video for mid-funnel consideration, especially in privacy-first environments. A blended approach often works best; Demand Gen delivers results, while contextual video expands visibility and trust. Let your objectives shape your media mix.
Read more
Measuring and Comparing Video Campaign Success Across Platforms Cross-Platform Metrics Guide

Measuring and Comparing Video Campaign Success Across Platforms | Cross-Platform Metrics Guide

Not all video views are created equal, and neither are the platforms they live on. This blog unpacks what it really means to measure success in a multi-platform world, where YouTube, TikTok, Instagram, and others each play a unique role across the funnel. From awareness to conversion, we explore which metrics actually move the needle, think watch time, click-through rates, cost per completed view, and how to track them meaningfully, depending on your goal and industry. It's not just about collecting data; it's about interpreting performance in context so you can make smarter, faster, creative, and media decisions.
Read more
Audience Segmentation Strategies for High-Impact YouTube Ads

Audience Segmentation Strategies for High-Impact YouTube Ads

YouTube’s fragmented audience landscape demands smarter segmentation strategies that move beyond simple demographics. By combining intent-based targeting, contextual alignment with brand-safe content, behavior-driven retargeting, and creative tailored to specific audience preferences, advertisers can reach the right viewers with greater precision. Leveraging machine learning alongside human oversight and tracking results through tools like Brand Lift ensures ad spend is focused on the most impactful segments for stronger campaign performance.
Read more
The Rise of YouTube's Viewership on CTV Devices

The Rise of YouTube’s Viewership on CTV Devices: Why Every Media Buyer Should Pay Attention

YouTube has become a major player in the CTV space, now accounting for around 12% of total viewing time and rivaling traditional TV with long-form, immersive, sound-on, full-screen content that captivates viewers. This shift creates a prime opportunity for advertisers to reach highly engaged audiences. Contextual targeting on YouTube CTV, focusing on what viewers are watching rather than who they are, offers precise, privacy-friendly ad placement with better performance and lower CPMs.
Read more
The Evolution of YouTube Ad Formats

The Evolution of YouTube Ad Formats: Skippable, Non-Skippable, and Bumper Ads

Explore how YouTube's ad formats, including skippable in-stream, non-skippable in-stream, bumper, and overlay ads, have evolved into a precision tool for marketers. AI now dynamically optimizes delivery based on user behavior, content context, and campaign goals. Brands are encouraged to match ad formats with viewer habits by using skippable ads with strong hooks for engagement, non-skippable ads for emotional storytelling (especially on CTV), bumper ads for concise brand messages, and overlays for subtle desktop targeting. YouTube’s data-driven features such as ad break timing, sequenced delivery, and performance forecasting help shape effective, multi-format strategies with both efficiency and brand impact.
Read more
Machine Learning and Human Oversight in Optimizing YouTube Ad Placements

Machine Learning & Human Oversight in Optimizing YouTube Ad Placements

Discover how combining machine learning with human oversight generates smarter YouTube ad placements. This hybrid approach enables fast, scalable campaign setup while ensuring brand safety and contextual accuracy. ML automates content classification, sentiment detection, engagement scoring, and risk assessment, then human experts verify results to fine-tune targeting. This method empowers advertisers to reach the right people, in the right context, without wasting budget on unsafe or irrelevant inventory and is backed by case studies showing up to 5× lifts in brand awareness.
Read more