Azure Video Indexer: Boost Engagement Using AI-Driven Video Intelligence

Advertisers and media teams face a growing challenge: video is now the dominant format for brand storytelling, yet the intelligence behind ad performance is often limited to surface-level metrics. Impressions, watch time, and click-through rates rarely explain why some creatives resonate and others fade. Teams experiment with new concepts, iterate on copy, try different hooks, and still struggle to understand which visual, audio, and contextual elements truly drive outcomes.
Azure Video Indexer
Azure Video Indexer was built to fill this gap. It’s AI automatically analyzes video and audio content to capture the attributes human reviewers can’t scale—objects, emotions, speakers, topics, transcriptions, translations, scene changes, and more—making it possible to optimize ad creative with granular, multidimensional data. By layering these insights on top of existing performance metrics, marketers gain a deeper understanding of what’s working, why, and how to improve the next iteration.

Azure Video Indexer is a cloud and edge video analytics service that extracts structured, actionable insights from stored video and audio. Through a multichannel pipeline that orchestrates visual and auditory cues, the service creates a unified metadata timeline that teams can analyze, integrate into their tools, or automate across their creative workflows.
Using Azure Video Indexer for Ad Performance Improvement
When advertisers can see exactly which faces, objects, emotions, scenes, keywords, or themes appear at the moments when engagement spikes—or drops—they unlock a level of optimization that used to require costly manual analysis. The platform reveals whether specific product shots correlate with closer attention, whether spoken phrases align with conversions, whether background settings influence retention, or whether multilingual captions drive higher reach across international audiences. By indexing existing ad libraries, marketers can quickly pinpoint winning patterns and replicate them at scale.
Detailed feature data also helps improve dynamic ad insertion, refine contextual targeting, and enhance recommendation engines across owned media properties. This results in better alignment between creative content, audience expectations, and platform behaviors—ultimately improving ROI across paid, owned, and earned channels.
Features Available in Azure Video Indexer
Before reviewing the following features, it’s important to note that each one contributes to a more precise understanding of your video assets, allowing teams to blend content intelligence with performance analytics in powerful ways.

Accessibility Tools: Automatically generate closed captions, transcripts, and multilingual translations to expand audience reach and evaluate how accessibility enhancements affect engagement.
Account Customization: Configure your account with fine-tuned settings, including custom taxonomies and metadata structures aligned to your advertising workflows.
Content Analysis: Identify spoken words, sentiment, topics, entities, and visual text, making it easy to understand how messaging tone and themes affect viewer response.
Content Security: Leverage Microsoft’s enterprise-grade security posture, supported by more than $1 billion in annual cybersecurity investment and over 3,500 security experts, to maintain compliance while working with sensitive media.
Edge Indexing: Run the full indexing workflow on-premises using Arc-enabled deployments, eliminating the need to upload large or confidential video assets to the cloud.
Media Editing: Assemble clips, stitch scenes, and generate new content from indexed assets using the built-in media editor, enabling rapid production of testable ad variants.
Metadata Extraction: Automatically tag people, objects, scenes, locations, brands, and emotions to reveal the creative elements driving audience interaction.
Multichannel AI Pipeline: Analyze audio, visual, and textual layers in parallel and combine them into a shared timeline for full-context creative diagnostics.
Search and Discovery: Improve discoverability across archives by enabling search by keyword, person, topic, project, or visual attributes.
Speech Services: Use advanced transcription and translation models to ensure accuracy and improve the performance of multilingual ad campaigns.
Web-Based Tools: Evaluate content via the web portal, embed the widget into your own dashboard, or call the REST API to integrate results directly into creative automation tools.

Together, these capabilities produce a rich intelligence layer over your ad library, helping teams test hypotheses, validate assumptions, and continuously refine creative assets with data rather than guesswork.
Ready to Transform Your Ad Performance?
Teams typically begin by uploading a batch of historical ads, indexing them, and mapping the extracted metadata against performance results from platforms like Google Ads, Meta Ads Manager, YouTube, or programmatic exchanges. From there, marketers can pinpoint the creative attributes that correlate with improvements in scroll-through rates, attention metrics, view-through rates, or conversions. Once these insights are established, new creatives can be produced in the built-in editor, tested in-market, and refined in rapid cycles.
Next, organizations often integrate Video Indexer via its REST API or embed the web widget in their internal dashboards to automate ongoing analysis. With Arc-enabled deployments, teams with strict data residency requirements can process assets locally without compromising low-latency workflows or confidentiality.
Start optimizing your ad creative with AI-powered insights that reveal exactly what drives attention, engagement, and conversion.
Start Analyzing Videos with Azure Video Indexer