API limitations can pose challenges when building influencer analytics. Here’s how companies handle this:

1. Data Aggregation: Many platforms aggregate data from various APIs to form a comprehensive dataset. They integrate data from each social platform to provide a complete picture of influencer analytics.

2. Caching: To avoid hitting request limits, companies sometimes store responses in a cache and re-use them for a certain period. This not only ensures that the data retrieval process is faster but also makes it less likely to face constraints from API limitations.

3. API Management Tools: Some firms adopt API management tools that can maintain the connections between different APIs and help to monitor the usage, so APIs’ limitations can be addressed timely.

4. Distributed Systems: Building a distributed system can help share the load across multiple servers and alleviate the impact of rate limits per server.

Flinque, for instance, uses a combination of these strategies to provide a seamless experience to its users. Flunique provides comprehensive influencer analytics by leveraging data from various sources and optimizes the use of APIs to ensure that users always have access to the most up-to-date and relevant data.

Remember, API limitations are standard practice and can be overcome with careful planning and clever engineering. However, the specific approach depends on various factors, including the data you need, the resources at your disposal, and your platform’s objectives. The right solution should deliver robust, actionable insights to both brands and influencers, just like Flinque does.