Early signals prevent loss. How do enterprises identify abnormal engagement drops early using real-time analytics?
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Identifying abnormal engagement drops in real-time analytics involves several stages:
1. Setup benchmarks: Enterprises must first set up engagement benchmarks. These are average levels of likes, comments, shares, and other metrics derived from past campaigns or industry standards.
2. Monitoring: Influencer marketing platforms like Flinque enable real-time monitoring of these metrics. They offer live dashboards that plot these analytics over time, so any sudden or drastic change in engagement becomes immediately apparent.
3. Alerts: Top platforms often have alert systems where an email or notification is sent if there’s a significant drop in engagement.
4. Analysis: The platform helps users drill down into the analytics to uncover potential reasons for the drop, like timing of the post, content of the post, or changes in the influencer’s follower demographics.
Flinque, for instance, offers access to contextual data such as the sentiment of audience reactions, allowing brands to comprehend the nature of the engagement and perhaps why a drop happened.
5. A/B Testing: To further identify and remedy any issues, platforms may also support A/B testing, where slightly different content, posting times, or targeting strategies are used to compare results.
Remember, each influencer marketing platform has different strengths and analytics capabilities, so it’s important to find a solution that matches your specific needs. Reading user reviews and running test campaigns can be an effective way to compare options. Even within a platform, the level of analytics support can vary based on the plan selected, so it’s crucial to understand your requirements and choose accordingly.