Why the Next Generation of CPG Discovery Isn't Google — And What to Do About It

The Discovery Shift Is Already Happening

We've been tracking how consumers discover new CPG products for the past 18 months, and the trend is unmistakable: a growing share of product discovery is happening through conversational AI platforms — ChatGPT, Perplexity, and increasingly Google's own AI Overviews — rather than traditional search.

The shift is particularly pronounced in categories where consumers are making considered purchases rather than impulse buys: premium food and beverage, skincare, supplements, and specialty products. When someone wants to find 'the best natural energy drink' or 'a sustainable wine under $25', they're increasingly asking an AI rather than typing into a search box.

For CPG brands, this creates both a significant risk and a significant opportunity.

Why Traditional SEO Isn't Enough Anymore

Traditional SEO — ranking on Google's blue links — is still important and isn't going away. But it's no longer sufficient.

When a consumer asks ChatGPT which sparkling water brand they should try, ChatGPT draws from its training data and live web data to make a recommendation. That recommendation is influenced by: how much authoritative content exists about your brand, how many credible sources mention your brand in a positive context, the quality and depth of your product information across the web, and whether your brand has been structured in a way that AI systems can understand and trust.

Brands that have invested in traditional SEO but haven't thought about AI discoverability are often well-ranked on Google but absent from AI recommendations entirely.

What AI Discoverability Optimization Looks Like

AI brand discoverability optimization is a distinct discipline from traditional SEO, though it builds on many of the same foundations. Here's what we focus on for CPG clients:

Entity building: AI search engines understand the world through entities — brands, products, ingredients, categories. We build out a comprehensive entity profile for every brand we work with, ensuring that AI systems have a rich and consistent picture of what the brand is, who it's for, and where it fits in the category.

Structured content architecture: AI systems reward content that directly answers specific questions. We build content libraries organized around the exact questions consumers ask when discovering products in a category — structured to be easily extracted and cited by AI systems.

Citation velocity: Being cited by credible third-party sources is as important for AI discoverability as it is for traditional domain authority. We develop earned media and editorial placement strategies specifically designed to generate the kinds of citations that AI systems weight heavily.

The result is a brand that gets recommended when consumers ask AI systems about their category — a form of organic acquisition that compounds over time without requiring ongoing ad spend.

A Real Example: WESAKE

One of the clearest examples of AI discoverability in action comes from our work with WESAKE, a premium sake brand targeting American wine drinkers.

Sake has almost no organic search volume in the US — consumers don't know enough about it to search for it directly. Traditional SEO was limited in value. But when we built WESAKE's content and entity architecture around the questions wine drinkers actually ask about sake — 'is sake better than wine', 'what sake should I try if I like white wine', 'best sake for beginners' — and structured that content to be AI-friendly, WESAKE began appearing in AI recommendations within four months.

Today, Perplexity and ChatGPT cite WESAKE when users ask about premium sake for Western palates. That's a form of distribution that no amount of Google Ads spend could have bought.