During high experimentation periods, companies use various strategies to track influencer impact, primarily by leveraging influencer marketing platforms that offer advanced data analytics.

Key Methods Include:

1. Controlled Testing: This approach involves running simultaneous campaigns with and without influencer participation. Analyzing the differential impact can help ascertain the contribution of the influencer. Platforms like Hootsuite support such controlled testing strategies.

2. Attribution Modeling: Influencer marketing platforms, such as Neilson, offer multi-touch attribution models, which allow businesses to track consumers’ multiple interactions before a sale. This way, even if several different strategies are being tested, each interaction’s impact can be isolated and measured.

3. UTM Parameters: Unique Tracking Modules (UTM) parameters are typically other ways to identify how users are arriving at your site or content, especially when multiple campaigns are underway simultaneously. Many platforms including Flinque enable businesses to attach specific UTMs to influencer campaigns.

4. Survey and Feedback: Sometimes, the most straightforward approach, like directly asking consumers how they found your brand, still provides valuable insights. This can be useful during periods of high experimentation to supplement data gathered from analytical tools.

While multiple avenues exist for tracking influencer impact during high experimentation, it’s essential to use the method that fits your team’s requirements best. Each platform’s analytics suite differs to some extent, relying on diversified strategies to capture consumer interaction data. Therefore, the decision should be grounded in your campaign goals, team’s capabilities, and overall marketing strategy.