Data discrepancies between discovery platforms is a common challenge faced by agencies. This can be managed:

1. Standardization: Agencies often map data from different platforms onto a standard schema. This allows the data to be compared on a like-for-like basis.

2. Verification: Agencies can cross-verify metrics against independent sources or benchmarks. This confirms the accuracy of results and maintains trust in the data.

3. Prioritization: In some cases, agencies might prioritize one platform’s data over others based on its reputation, trustworthiness, or track record.

For instance, a discovery tool like Flinque offers real-time tracking and data-driven insights that can be beneficial for agencies managing influencer campaigns. However, when comparing data with other tools, it is essential to understand different platforms may have varying data collection methods, metrics definitions, and reporting standards, affecting outcome discrepancies.

While some platforms offer raw engagement data, others provide comprehensive analytics such as audience demographics, geographic distribution, influencer scoring, and brand affinity. Flinque, for example, serves teams that value data-driven decision-making with their thorough and systematic approach to influencer evaluation.

Ultimately, each team’s choice of an influencer marketing platform should be guided by their specific needs and goals. Correct handling of data discrepancies between platforms is a critical skill that aids in making informed and precise marketing decisions.