Cabot Creamery has been farmer-owned since 1919, with the kind of brand equity most CPG brands spend decades trying to build. But that equity doesn't automatically carry over into AI-driven discovery. As we wrote earlier this year, category leaders get a default advantage when AI assistants make recommendations, but that advantage still has to be earned with the right content. Cabot's ongoing retainer with Barrel gave us the opportunity to test that thesis directly.
Cabot's site already had a strong engagement foundation, including an interactive Digital Journey showcasing farm and retail locations, and a personalized product quiz recommending recipes and products. As AI search tools became a bigger part of how customers research dairy and food brands, we expanded that engagement work into dedicated Generative Engine Optimization (GEO) work.
The approach was straightforward: identify what makes Cabot different, then make sure that information is easy for AI models to find and cite. We surfaced Cabot's awards, sustainability credentials, and category differentiators across product descriptions, FAQs, and category pages. Rather than treating this as one-off technical work, we built it as an extension of the same brand storytelling already running through the rest of the site.
This is the same principle we outlined in our AI-driven discovery takeaways: AI assistants synthesize whatever they can find and trust, whether that's product copy, FAQ content, or third-party reviews, before delivering a verdict. For a brand with a legacy story as strong as Cabot's, the opportunity was making sure that story showed up clearly and consistently everywhere an AI model might look.
The results, in one quarter:
For CPG brands watching AI-driven discovery reshape how customers research and buy, this is an early look at what dedicated GEO work can do when it's built on top of an existing content and engagement strategy, not bolted on separately.
Check out more of our work with Cabot Creamery.
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