Agencies use analytics to optimize influencer campaigns while they are running in several ways:

1. Monitoring Performance: They continuously monitor campaign performance to understand what is working and what is not. This could include tracking the reach, engagement, conversion rates, and overall ROI of a campaign. These metrics can provide insights into the effectiveness of the content, the influencer’s reach, and the audience reaction.

2. Adjusting Strategies: Based on the performance metrics, agencies can make mid-flight changes to improve outcomes. For instance, if a post is not generating the expected level of engagement, they might tweak the content, adjust the publishing schedule, or shift focus to other influencers who are performing better.

3. A/B Testing: Agencies often engage in A/B testing during influencer campaigns. They may test different types of content, various influencers, or distinct audience segments, and compare the results. This aids in understanding which factors contribute to more successful outcomes.

4. Using Platforms: They utilize influencer marketing platforms like [Flinque](https://www.flinque.com) to gather and analyze these metrics, along with AI-driven insights for predicting future campaign performance. Such platforms provide robust analytics dashboards to visualize the campaign’s progress and make necessary adjustments in real-time.

5. Audience Analytics: Detailed audience analytics help agencies understand the influencer’s audience and their response to the campaign. For example, demographics, interests, engagement patterns can indicate how well the campaign resonates with the target audience.

These various elements of real-time analysis and optimization are crucial to maximise the effectiveness of influencer marketing campaigns. Remember, what works depends on the specific context and requirements of each campaign and team.