Introduction#
Views and upvotes create a popularity loop—content that’s already popular gets more visibility, while new content struggles. Platforms that want to surface genuinely valuable content need to look at subtler signals.
Diving Deep into User Behavior#
Instead of only focusing on explicit feedback, observe how users genuinely interact with the content:
Time Spent and Scroll Depth: If a user stays longer and scrolls more, it indicates genuine interest.
Content Revisits: Frequent returns to the content emphasize its continued value to users.
Exit Rates: A rapid exit can signal a content-value mismatch.
Quality from the Content’s Own Merits#
Not all good content gets immediate upvotes or comments, but its intrinsic qualities can hint at its potential:
Uniqueness: Novel perspectives or topics can draw genuine interest.
Structural Integrity: Proper formatting, grammar, and clarity often equate to quality.
Author’s Past: Without considering views or likes, an author’s past engagements can hint at the potential value of their new content.
Peeling Layers from Interactions#
Feedback is more than just an upvote:
Early Comment Sentiment: Positive initial comments, even if few, can signal quality.
Semantic Analysis: Content filling gaps or matching emerging platform trends might be given prominence.
Tapping into Current Digital Pulse: Search Engine Keywords and Trending Topics#
The broader digital ecosystem offers cues on what’s resonating currently:
Keyword Integration: Content aligning with trending search engine terms indicates current relevance.
Content Responsiveness: Rapid content production in line with trending topics shows timeliness.
Predictive Analysis: Predict which topics might trend next and prioritize fresh content that matches.
Cross-platform Trends: What’s buzzing on Twitter or Reddit might be relevant for your users too.
User Queries and External Referrals: If users are searching for a topic on your platform or if a piece draws traffic from search engines, it’s a hint of its current relevance.
Striking a Balance with A/B Testing and Network Effects#
Test and Learn: Expose new content to subsets of users to compare its engagement against established content.
Networked Insights: Observe how content spreads, both internally and externally. Shares, mentions, and embeds provide insights into content value beyond just views or likes.
Concluding Thoughts#
Good content ranking combines multiple signals: user behavior (scroll depth, revisits), content quality (uniqueness, structure), trending topics, and A/B testing. No single metric tells the full story.