TikTok’s search functionality has room for improvement. The search algorithm often produces irrelevant results and fails to surface content users are actually looking for. There are a few key reasons why TikTok search struggles compared to other platforms.
Immature Search Algorithm
As a relatively new platform, TikTok is still early in developing and refining its search algorithm. Platforms like Google and YouTube have had over a decade to collect data and understand exactly what users want from search. TikTok’s algorithm has far less historical data to work with.
YouTube spent years training its algorithm by having human raters evaluate millions of searches. This allowed it to learn which results were considered high quality for different queries. TikTok hasn’t gone through this extensive process yet.
In addition, TikTok’s algorithm is inherently more complex. It tries to understand searches in multiple languages and connect billions of short, sound-heavy videos. This makes it harder to discern what users want compared to traditional text searches.
Emphasis on Personalization
TikTok heavily personalizes search results based on a user’s previous engagement, likes, follows, location and other factors. This can produce more relevant results for individuals but makes search less effective overall.
For example, if you search for “dance trends”, TikTok will show you dance videos similar to what you normally watch instead of the most popular dance trends. This can be frustrating when you want to discover new content.
YouTube and Google search do incorporate personalization as well but place more emphasis on universal relevance. TikTok search often seems to ignore what is trending or commonly searched.
Limitations of Short-Form Video
It is inherently more difficult for an algorithm to evaluate short-form videos compared to text, images or longer videos. Most TikTok videos are under 60 seconds, which limits how much context and detail they can provide.
Google can easily scan websites and webpages to understand relevancy for text queries. Short TikTok videos offer less tangible information for algorithms to analyze and categorize.
In addition, text and longer videos allow searches to match exact phrases and keywords. With short videos that are mostly visual, it is harder for TikTok’s algorithm to identify which clips match a search.
Heavy Reliance on Captions and Sounds
Since TikTok videos themselves provide limited context, the platform’s search depends heavily on captions, titles and sounds added to clips.
But captions are often optimized for engagement rather than accurately describing content. Sounds are reused across many different trends and topics. This makes it harder for TikTok’s algorithm to sort videos in a way that makes sense.
Google can scan the actual content on websites to understand relevancy. TikTok is forced to make conclusions based on limited supplemental information.
Lack of Moderation and Quality Control
Experts criticize TikTok for relying too much on artificial intelligence to moderate content instead of human reviewers. As a result, low-quality, misleading and irrelevant videos can gain traction.
These types of videos then confuse TikTok’s search algorithm, making it harder for AI to discern what content is actually valuable for search queries. Critics argue TikTok needs more human oversight to maintain search integrity.
YouTube and other platforms use both human moderators and AI to ensure search results meet a quality threshold. TikTok’s looser oversight pollutes its algorithm with junk data.
Challenges Indexing Massive Library
As one of the largest and fastest-growing video platforms, TikTok is still struggling to effectively index its massive library for searchability. With billions of videos and petabytes of data, incomplete or inaccurate indexing severely damages search relevance.
YouTube and Google search have far more mature processes and infrastructure for crawling, processing and cataloguing content at scale. TikTok is racing to index past and current videos but still has gaps.
This is a solvable scaling challenge but it requires huge engineering efforts to fix. Until indexing and infrastructure improve, results for both old and new content will be inconsistent.
Scope Limitations
Compared to Google, TikTok search has narrower scope and less diversity of content to draw upon. Google can pull from billions of webpages, images, videos, books and other sources to find relevant results.
In contrast, TikTok only has user-generated short videos to work with in search. Even with billions of videos, the constrained format and single content type makes it harder to connect searches with relevant clips.
In addition, newer videos tend to carry more weight, making it harder to surface older, potentially relevant content. Expanding beyond just short videos could help improve TikTok search in the long-run.
Brand Safety Incentives
As TikTok has come under fire for hosting objectionable content, the company has strong incentives to play it safe with search results. But this can hamper relevance.
Restricting certain hashtags and politically or culturally charged content may help TikTok avoid controversy but also blocks users from finding videos. Overzealous filtering leads to bland, irrelevant search results.
Google and YouTube face less pressure to filter everything potentially divisive or sensitive. TikTok’s approach skews search away from controversy at the expense of satisfying users.
Limited Search Operators
TikTok offers few advanced search operators compared to Google and YouTube. There are no tools for date filtering, usage rights filtering, exact phrase searching, Boolean operators like AND/OR, etc.
This limits users’ ability to fine tune searches and forces TikTok’s algorithm to guess what aspects are most important. More robust search syntax and filters would improve search relevance.
Power users on other platforms rely heavily on advanced operators to find precisely what they want. TikTok offers little control, forcing everyone into simplistic broad searches.
The Road Ahead
Improving search relevance is clearly a priority for TikTok. But building a robust search algorithm presents unique challenges compared to other platforms.
TikTok will need to expand its content scope, improve moderation, refine ranking factors and open up advanced search operators. Striking the right balance between personalization and universality will also be critical.
It took years for Google and YouTube to develop powerful search algorithms – TikTok is still in the early innings. But improving search quality will be crucial for keeping users happy and engaged over the long-term.
