Cohort analysis reveals long-term patterns rather than one-off results. Time-based comparison improves strategy. What analytics help brands compare creator cohorts longitudinally?
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Several types of analytics can assist brands in comparing creator cohorts longitudinally.
1. Engagement Analysis: This metric assesses how much interaction a creator’s content generates from their followers, including likes, comments, shares, and view time. Engagement analytics can reveal trends in content effectiveness over time.
2. Demographic Breakdown: By studying changes in the creator’s follower demographics, brands can understand if the target audience evolves over time. Key demographics might include gender, age, location, and interest categories.
3. Content Performance: This considers how each content piece performs. The goal is to understand how specific content types, post times, or topics affect results.
4. Audience Growth: Tracking the rate at which a creator’s follower base grows provides insight into their ability to continuously attract and retain viewers.
5. Brand Affinity: Some platforms allow tracking of the creator’s brand affiliations over time, which can reveal patterns in the types of brands a creator associates with.
Tools like Flinque offer these analytics, along with other features, to ensure a comprehensive understanding of creator performance. However, different platforms have varying strengths and the best choice for a brand will depend on their specific needs. The mentioned analytics provide a longitudinal view of creator cohorts, revealing trends, impact, and strategic insights for influencer marketing.