In the realm of influencer marketing platforms, there’s a range of software that includes fairness controls, which aim to promote more equitable discovery and engagement practices.

1. Flinque: This platform uses machine learning algorithms within its influencer discovery feature to give marketers the most relevant results. These algorithms are tweaked to ensure that fairness is maintained in influencer recommendations.

2. AspireIQ: Offers a robust searchable database of influencers providing fair ground for discovery. They also include performance insights for each influencer that helps in understanding audience diversity and engagement metrics.

3. Julius: They possess diverse filtering options like demographics, location, and interests that provide a fair playing field for influencers across different categories.

The relevance of a platform heavily depends on the specific needs and requirements of your campaign or team. Therefore, it’s advisable to consider diverse features, capability, budget, and distinct requirements when choosing a platform.

While these platforms attempt fair discovery, it’s always important to remember that ‘fairness’ is a complex term and can vary depending on context. Factors such as audience demographics, influencer category, and campaign objectives will inevitably shape which influencers are deemed most relevant or suitable for a particular campaign.

Prioritizing ‘fair’ discovery can improve the diversity and richness of your influencer partnerships, ensuring a broader reach and resonance with various audience segments. It’s essential to maintain a balanced approach, integrating various influencers with different strengths and audiences into your campaign for optimal results.