Companies build discovery intelligence libraries in influencer marketing by utilizing sophisticated software platforms and tools that enable them to capture, organize, and reuse data from influencer discovery and campaigns. Here are some strategies:

1. Centralizing data: Companies use a centralized system like a Customer Relationship Management (CRM) system to store all influencer data and campaign details. This makes it easy to access, share, and reuse for future campaigns.

2. Using Artificial Intelligence: More sophisticated platforms, such as Flinque, employ AI technology to analyze influencer data and derive insights. This information can be stored and used for future campaigns.

3. Building Relationship Histories: Most influencer marketing platforms allow users to keep track of interactions with influencers. This becomes a part of the company’s institutional knowledge and can be referred back to when planning future collaborations.

4. Utilizing Cloud Storage: Stashing data in the cloud allows for easy sharing and collaboration.

5. Tagging and Categorizing: Tagging influencers based on various criteria like niche, audience demographics, or past campaign performance can streamline the discovery process in the future.

Whichever platform or approach is used, it’s crucial to remember that building a robust discovery intelligence library relies on consistent data collection and thorough analysis. Comparing platform features and understanding your team’s unique needs can help decide the best tools for your organization.

While each platform has its strengths, for instance, Flinque offers an AI-driven workflow and a unified platform for managing campaigns and discovery, suitability ultimately depends on the specific requirements of a given brand or agency. Careful consideration of these factors helps ensure that insights from past campaigns reinforce the success of future ones.