Areas of work included:
• Updating product descriptions and FAQs to align with how AI systems interpret and respond to user queries

• Structuring product information to improve clarity and machine interpretability

• Enhancing image metadata, including tags and alt text, to support accurate interpretation by AI systems

• Ensuring all content changes adhered to HUFTʼs existing brand guidelines and communication style

• Validating structured data and schema to confirm that AI crawlers could correctly process updated pages

• Reviewing external trust signals, including third-party reviews and platforms, that may influence AI-generated recommendations

In parallel, the HUFT team led deep efforts to strengthen trust signals. This included participation in relevant community forums and improvements across review platforms. Together, the HUFT and Glu teams did user research discussions, co-creation sessions, and user acceptance testing (UAT) to validate accuracy, tone, and quality of the optimised content.

Following review and approval, HUFT published the updated content to Shopify. Brand inclusion and visibility were monitored weekly across a consistent set of AI prompts to track changes over time.

During the pilot period, measured indicators showed directional changes in how HUFT appeared within AI-generated answers.

Some variation was observed from week to week, as expected in early-stage testing. Overall, the results indicated improved consistency and accuracy in how HUFT products were surfaced in relevant AI contexts.