Overview
Interest insights help reveal the topics, themes, and content categories that resonate most strongly with users in each audience cluster.
These insights are based on audience behavior and profile analysis rather than self-reported preferences, helping provide a more objective view of audience affinities and engagement patterns. Interest analysis is one of the core components of TikTok Insights reports and plays a central role in audience segmentation and audience understanding.
How Interests Are Determined
Interests are inferred by analyzing TikTok post content and profile biography information This allows Audiense to identify the topics and categories most strongly associated with audience behavior and self-expression. Because the analysis is based on actual audience activity and profile-level signals, interest insights provide a strong indicator of genuine audience affinity.
Understanding the Interest Taxonomy
TikTok Insights organizes interests using a two-level taxonomy structure.
The taxonomy includes:
- 25 parent categories
- 498 specific interests
For example, a broader category such as Sports may contain more specific interests such as Soccer, while Music may contain interests such as K-Pop. This structure allows organizations to analyze interests at both broad and highly granular levels. Users may belong to multiple interests and categories simultaneously.
Understanding TML (Times More Likely)
TML stands for Times More Likely. TML measures how much more or less likely a cluster is to engage with a topic compared to a comparison baseline audience.
For example:
- 1.0x indicates alignment with the baseline audience
- 2.0x indicates the cluster is twice as likely to engage with the topic
- 0.5x indicates below-average affinity
By default, the comparison baseline is set to Global - General, although other comparison groups may also be supported. TML helps organizations identify which interests are most distinctive for a cluster rather than simply the most common.
Interest Visualization Options
TikTok Insights currently supports two primary interest visualization modes. These visualizations help users explore audience affinities from both high-level and detailed perspectives.
Treemap View:
The treemap view displays interest categories as a grid of colored rectangles. The size of each rectangle reflects the penetration score for that category within the cluster. Larger rectangles represent categories associated with a larger percentage of the audience.
At the category level, colors act as fixed category identifiers. When drilling into a category, color intensity reflects TML affinity relative to the comparison baseline. Treemap visualizations are useful for quickly identifying dominant audience interests and major affinity areas across a cluster.
Bar Chart View:
The bar chart view displays interests as ranked rows alongside additional metrics.
This view includes:
- Penetration percentage
- TML affinity score
- Number of subcategories
The bar chart view also supports grouping interests by category or displaying all interests in a flat ranked list. This view is useful for more detailed interest comparisons and affinity analysis workflows.
Filtering and Sorting Interests
TikTok Insights supports filtering and sorting within interest visualizations. Users can filter interests using keyword searches and sort results using dimensions such as:
- Percentage
- TML
- Subcategory count
Sorting by penetration helps identify the most common audience interests, while sorting by TML helps surface the most distinctive affinities for the clusters.