Influence marketing’s problems can be solved with a machine-learning solution
People subjectively picking influencers who will best represent their brand is risky, argues Social Soup’s Sharyn Smith. Instead, the world of influence marketing should turn to machine learning.
Social media influencers have become a common tool in a marketeer’s toolbox to reach current and potential customers, building awareness, third-party credibility and purchases.
But the rapid growth of this channel (in little over 10 years) has brought with it significant debate on its effectiveness and ethics. And those criticisms warrant the introduction of machine learning.
Criticisms levelled at the industry and individual influencers have included: a lack of transparency of the effectiveness of influencers, unfilled promises made by those representing influencers, and a lack of knowledge among in-house marketing teams on how to use influencers for their brand effectively.
Fantastic read! Was this article written using machine learning?