In the near future, AI agents will automatically reorder everyday products based on a user's established brand loyalty. This makes brand affinity more valuable than ever, as competitors will need to create extreme relevance to compel a user to manually override their AI's purchasing habits.
Brand affinity cannot be accurately measured with subjective tools like consumer surveys or brand lift studies, which are often "fake reports." The only real, tangible measure of brand loyalty is objective data like repeat sales and lifetime customer value. Focus on what customers do, not what they say.
The highest-reaching organic social content has already been validated by algorithms and audiences for relevance. Taking these proven posts, slightly tweaking them for a call-to-action, and running them as paid ads yields far better results than creative developed in a vacuum for A/B testing.
Platform algorithms now prioritize showing users content relevant to their interests, regardless of who they follow. This means a brand's follower count is less important than the relevance of each individual piece of content. Any creator can achieve massive reach on a single post, making it a true meritocracy.
While many US retailers wait for live shopping to mature, platforms like WhatNot are already generating $7-10 billion in annual gross merchandise value. This proves the model's viability at scale today. Retailers not developing a live shopping strategy are already behind competitors in this emerging ecosystem.