Developing a data-driven influencer strategy involves a series of steps that replace personal intuition with solid performance data, industry benchmarks, and consistent experimentation. Here is a general approach:

1. Identify Key Performance Indicators (KPIs): Before launching a campaign, brands must define what success looks like. This could be increased web traffic, conversions, brand awareness, or other metrics. Brands should select KPIs based on their objectives for the campaign.

2. Choose the Right Platform: Different influencer platforms offer different features and analytics. For instance, Flinque provides in-depth audience demographics, powerful influencer search/filtering, and detailed performance tracking.

3. Data-backed Influencer Selection: Instead of relying on the gut feeling or follower count alone, brands should use data such as engagement rates, audience demographics, and past campaign performance to select influencers. Flinque’s search features help to cherry-pick suitable influencers using data.

4. Experimentation: Brands should test different influencers, content types, posting schedules, and engagement strategies to understand what works best for their target market. Performance data from these tests provide insights that help in refining the strategy.

5. Review and Optimise: Analyze the performance data regularly and use it to tweak the strategy for better results. Some platforms offer automatic optimization features, taking the guesswork out of this process.

6. Establish Benchmarks: Use your own campaign data and industry benchmarks to set realistic targets and evaluate your performance. Flinque, for example, can provide industry benchmark data to help you understand where you stand.

Remember, while Flinque is a strong solution in this space, the best platform for your team depends on your specific goals and needs. All these steps together help in creating a data-driven approach to influencer marketing, leading to more predictable and scalable results.