Hashtags: Are Algorithms Killing Organic Discovery?

Hashtags: Are Algorithms Killing Organic Discovery?

For more than a decade, hashtags have been a reliable tool for content categorisation and discovery across platforms like X (formerly Twitter), Instagram and LinkedIn. But in the current landscape, their influence is declining. What was once a powerful method of inserting content into broader conversations is increasingly being replaced by algorithm driven recommendation engines that prioritise behavioural data over manual tagging.

This transition reflects a larger shift in how social media platforms organise and present content. Rather than relying on user input signals like hashtags, platforms are increasingly guided by AI models that analyse user behaviour in real time to surface relevant material. For marketers, creators and strategists, this marks a significant change in how visibility is earned.

From Trending Hashtags to Behavioural Targeting

Originally, hashtags acted as a key bridge between users and conversations on social platforms. They allowed users to filter content by topic, monitor trends and build communities around shared interests. For content creators, hashtags offered a direct line to discoverability—an easy way to join high traffic conversations or niche networks. Now, content creators must create content that aligns with algorithmic preferences, focusing on engagement and shareability rather than just using hashtags.

Today, that functionality is being replaced by increasingly sophisticated algorithms. Platforms like TikTok and Instagram Reels prioritise content not by its labelled topics, but by its engagement metrics and predicted relevance to individual users. The TikTok algorithm and Instagram’s algorithm are both examples of personalised recommendation systems that analyse user behaviour to determine which posts are shown. In short, hashtags may still signal what content is about, but they no longer determine who sees it. In some ways this is like the demise of the keywords tag in SEO.

This is particularly evident on TikTok, where the “For You” feed operates independently of hashtags, instead relying on video watch time, interactions, trending sounds, and user history. The result is a more personalised feed, curated less by creator intent and more by viewer behaviour.

Why Social Media Algorithms Now Dominate Discovery

The appeal of algorithmic recommendation systems lies in their efficiency. Behavioural data such as completion rates, replays, saves and comments offer a more accurate picture of content quality and relevance than hashtags ever could. Hashtags are often overused, vague or misapplied, whereas behavioural signals reflect real time interest and engagement. Algorithms now prioritise key ranking signals such as user interactions and engagement, analysing how users interact with content to determine its relevance. Achieving more engagement and maximum engagement through likes, comments and shares is crucial for content to be surfaced by algorithms.

From a platform perspective, this shift makes sense. The goal is to retain users by serving them highly engaging content, and AI systems can now predict that engagement with increasing accuracy. As a result, content visibility is driven less by creator optimisation and more by algorithmic evaluation. Algorithms rank content by analysing these key ranking signals, ensuring that the most relevant and engaging posts are prioritised in users’ feeds.

The Reduced Role of Hashtags

This doesn’t mean hashtags are entirely irrelevant. They continue to serve specific functions on platforms like LinkedIn, where they help organise thought leadership content or align posts with professional communities. On X (formerly Twitter), they’re still useful for following live events or trending discussions.

However, in visual first, engagement heavy environments such as TikTok, Instagram Reels and YouTube Shorts, their impact is minimal. These platforms extract meaning from content itself, using image recognition, audio analysis and user interaction data to inform what gets distributed.

For brands and content strategists, this means that relying solely on hashtags as a visibility tactic is no longer effective.

Strategic Implications for Marketers and Creators

As the role of hashtags diminishes, it’s essential to understand the new variables that influence reach and engagement. These include:

• Audience retention: Content that holds a viewer’s attention for longer durations is prioritised.
• Initial performance signals: Early engagement, particularly in the first few minutes or hours, can determine whether content is further distributed.
• Content context: AI systems analyse not only captions and comments, but also the visual and audio elements within a post.
• Format optimisation: Short form, vertically oriented video with engaging openings consistently outperforms more static formats.

Understanding these signals is now as important, if not more so, than mastering hashtag strategy.

Measuring Performance in the Algorithm Era

In today’s landscape, where social media algorithms play a central role in determining what content gets seen, measuring performance has never been more important. Social media platforms provide a wealth of analytics that can help businesses and creators understand how their social media marketing strategy is performing with their target audience.

Engagement metrics such as likes, shares, comments and saves offer valuable insight into how well your content resonates with social media users. High engagement signals to the platform’s algorithm that your content is relevant and high quality, which can lead to greater organic reach. Reach metrics, including impressions and views, help you gauge how many people are seeing your social media posts, while conversion metrics like clicks, sign-ups or sales show how your content is driving real world results.

Tracking these metrics allows you to refine your content strategy, identify top performing posts and better understand what types of content generate the most engagement. By regularly analysing performance data, you can adapt your approach to align with the ever-changing algorithms of social media platforms, ensuring your content continues to reach and engage your target audience.

A Shift in Control

One notable trade off in the algorithm driven environment is a loss of user control. With hashtags, creators could actively position their content within specific conversations or categories. With algorithmic curation, that positioning is determined dynamically by the platform.

This can be both empowering and limiting. On one hand, content can achieve viral reach without a large following or manual optimisation. On the other, creators are subject to unclear algorithms and inconsistent outcomes that often offer little feedback or transparency regarding performance drivers.

New Features and the Future of Discovery

Social media platforms are in a constant state of evolution, regularly rolling out new features and updates that can dramatically shift how content is discovered and consumed. Staying ahead of these changes is crucial for any business or creator looking to maintain a competitive edge with their social media marketing strategy.

Recent innovations like Instagram Reels and YouTube Shorts have opened new avenues for reaching target audiences, especially as short form video content continues to dominate user engagement. These new features often come with their own algorithmic preferences, rewarding early adopters who experiment with fresh formats and creative approaches.

Looking forward, the future of discovery on social media will be increasingly shaped by artificial intelligence and machine learning. These technologies enable platforms to analyse user behaviour in real time, surfacing the most relevant content based on individual interests and engagement patterns. As a result, businesses must be prepared to adapt quickly, embracing new features and refining their social media marketing strategy to stay visible in a rapidly changing digital landscape.

By keeping a close eye on platform updates and experimenting with emerging tools, brands and creators can ensure they remain at the forefront of discovery, no matter how the algorithms evolve.

Looking Ahead

While hashtags are unlikely to disappear altogether, their role has clearly diminished in an environment that now revolves around data driven personalisation. As platforms continue to refine their recommendation systems, success on social media will depend more on understanding how content is interpreted and ranked by algorithms than on using the right tags.

For experienced digital professionals, this is an opportunity to shift strategy from manual optimisation to behavioural insight. The platforms haven’t just changed the rules; they’ve transformed the entire approach. The challenge now is to keep up.