ANNUAL REPORT » DIGITAL TRANSFORMATION » CODE AND THEORY

Problem

With a 4,700% jump in referrals from AI chatbots to retail sites this year, brands can no longer rely on traditional search. JBL recognized that if their content wasn’t structured to feed these new AI algorithms, they risked becoming invisible to a massive wave of AI-first shoppers. They needed a way to translate their brand authority into the world of LLMs and social feeds, where automated discovery now dictates what consumers buy.

Solution

JBL partnered with Code and Theory to build a brand-new strategy centered on AI Search Optimization. They developed platform-specific best practices from scratch to make JBL’s content “machine-readable” and highly recommendable by AI. This included deploying LLM-optimized social content across YouTube Shorts and digital gift guides. By grounding JBL’s content strategy in AI-driven insights, they ensured that when an algorithm or chatbot looked for the best audio gear to recommend, JBL was the clear choice. 

Outcome

The shift to an AI-first social strategy delivered a massive surge in audience connection. By optimizing for how algorithms actually surface content, JBL saw their engagement metrics skyrocket. They received 200x higher engagement compared to JBL’s previous 30-day average, 2.61% engagement rate on YouTube Shorts (up from a 0.013% average), 42,500 organic views with all AI-optimized videos hitting JBL’s “Top 10” list, and 5.8% average engagement lift, proving that AI-driven insights lead to real-world interest.