Giant.aep

The account @aep.giant has 1.1 million followers, with an average video reaching 3.6 million views. The total likes amount to 35 million, resulting in an engagement rate of 10.96%. This indicates a substantial reach and strong audience interaction, with each video achieving significant viewership and likes relative to its follower base.

The @aep.giant account demonstrates exceptionally strong engagement metrics, with an overall engagement rate of 10.96%, which exceeds the typical 5-10% benchmark for most accounts. This rate is driven by an average of 370,536 likes per video, which accounts for approximately 33.7% of their 1.1 million followers. The high like volume suggests the content is highly appealing or aligns with trending topics, though it does not fully explain the overall engagement rate, as likes alone contribute 94.3% of total engagement (likes + comments + shares). The 2,205 comments per video represent 0.59% of likes, indicating a relatively low proportion of audience interaction beyond liking. Shares are even lower, at 23,149 per video (6.25% of likes), which suggests limited audience motivation to redistribute content. The metrics highlight a clear pattern: while the account excels at driving likes, it lags in fostering deeper audience interaction. The disparity between likes and comments/shares may reflect content that prioritizes visual appeal or emotional resonance over prompting discussion or sharing. For instance, the 10.96% engagement rate is heavily influenced by the 370k likes, which alone account for 94.3% of total engagement. This suggests the content is effective at capturing attention but may lack elements that encourage dialogue or organic sharing. The low share rate (6.25% of likes) further indicates that the audience is less inclined to amplify the content beyond their own interactions. These metrics collectively indicate that @aep.giant’s content resonates strongly with viewers in terms of immediate reaction (likes), but the account may benefit from strategies to increase comment and share activity. For example, incorporating prompts for audience input, leveraging trending challenges, or creating content that invites personalization could help bridge the gap between likes and more interactive engagement. The high like-to-comment ratio also suggests the audience may prefer passive consumption over active participation, which could inform content optimization efforts.

Engagement Quality Analysis

Median-based metrics that resist fake virality and outliers.

@aep.giant's content strategy is heavily centered around football, as evidenced by the dominance of hashtags like #messi (29x), #lionelmessi (22x), #barcelona (22x), and #footballtiktok (27x). These tags suggest a focus on football-related content, likely featuring player highlights, match analysis, or sports culture. The frequent use of #fyp (38x) and #viral (38x) indicates an intentional effort to maximize visibility on TikTok’s For You page, prioritizing algorithmic discovery over niche communities. The repetition of #edit (27x) and #aftereffect (18x) further implies a thematic emphasis on video production techniques, possibly aligning with trends in sports content creation. Thematic consistency is reinforced by the overlap between football-specific hashtags and engagement-driven tags like #viral, suggesting a dual strategy: leveraging football’s broad appeal while optimizing for virality. However, the absence of primary content categories limits deeper insights into whether the focus is on player-centric content, match footage, or sports commentary. The strategic repetition of #fyp and #viral, paired with football-related tags, indicates a calculated approach to balance niche relevance with algorithmic reach, though the lack of category data prevents confirmation of content uniformity across all posts.

Video Duration Breakdown

Original Sound Usage

Percentage of videos using the creator's own audio