Google Discover Optimization

Why It Matters

Google Discover can deliver significant unpredictable traffic spikes to content that resonates with audience interests, particularly for news, entertainment, and lifestyle topics. Unlike search traffic which requires active user intent, Discover reaches users proactively. High-quality content with strong E-E-A-T signals and engaging visual assets is most likely to surface in Discover feeds.

How It Works

Discover uses machine learning to model user interests from search history, app usage, and engagement signals, then matches content to those interest models. Content eligibility requires indexation in Google Search, high-quality images (1200px+ minimum), adherence to Google's content policies, and strong quality signals. Content freshness and topical relevance to active user interests drive Discover selection.

Use Cases

• News publishers optimizing article images and headlines for Discover card display
• Lifestyle content brands creating visually rich content targeting Discover audience interests
• Educational publishers creating timely content tied to trending topics for Discover discovery
• B2C brands creating story-driven content that aligns with consumer interest signals
• YouTubers cross-publishing article companion content to capture Discover traffic alongside YouTube reach

Best Practices

• Use high-quality images of at least 1200px width-Discover cards are image-led and image quality determines CTR
• Write headlines that are descriptive and interest-piquing without resorting to clickbait
• Publish consistently on topics you want to be associated with in Discover's interest categorization
• Implement Article schema with image properties to ensure Google correctly identifies your best image
• Monitor Google Search Console's Discover performance report to identify topics driving Discover traffic
• Publish timely content tied to trending topics while the topic is actively surfacing in feeds