
Mar
Brand Health Tracking with LLM Equity (Part 2)
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World
Is AI Surfacing Your Brand?
In the first blog of our three-part series, we touched on how AI is reshaping the shopping process from the searching for products up to completing the purchase in the customer’s behalf, and what Large Language Models (LLM) equity means for brand health. To illustrate, when a consumer asks an AI agent like ChatGPT for recommendations on clothing brands, does your clothing line show up? And if it does, how what image is being surfaced for your brand?
By tracking brand health, brands are able to learn not only whether their marketing strategies and creative directions are converting into market share, but also determine performance drivers per platform and digital metric, understand which themes or aspects of their brand resonate with consumers, and assess their “piece” of the LLM pie- or how often LLMs surface or recommend their brand.
Image: Julio Lopez
How Is AI Surfacing Your Brand?
There are several dimensions to brand health which includes the strength of your brand to be picked up and recommended by algorithms, the main themes and imagery associated with your brand by consumers and AI, how often consumers and AI share your content or recommend your brand, how likely your consumers would convert into advocates for your brand, and the perceived value of your brand in terms of pricing, quality and worthiness across different media. These can be boiled down into three main dimensions: brand awareness, brand associations, and brand loyalty. From these three main dimensions, a company can form and anchor their LLM equity strategies for visibility, communication, differentiation or positioning, engagement, attracting potential customers, optimizing marketing spend, as well as pivoting or responding to the competition or other emerging challenges.
The effectivity of brand strategies can be measured in three metrics: alignment, engagement, and intent. Alignment refers to how clearly and consistently your brand messaging, themes and values are being represented and communicated to and by your consumers, engagement is concerned with how customers are interacting with your brand in different media and platforms, while intent looks at how your brand moves audiences to search and look up your products and services. All three consider the strength of your brand messaging and values as reflected through consumer-earned content and digital footprints.
With these sets of brand health dimension and key metrics forming the backbone of brand marketing strategies, brands are not only able to catch attention but also earn consumer trust; not just reach audiences but also influence customer decisions; become not only “first to mind” to consumers but also strongly and coherently presented by LLM platforms as we gradually move into an AI-driven shopping landscape.
Image: Atlantic Ambience
Featured Image: TungArt7
Top Image: Anna Shvets

Mar
Brand Health Tracking with LLM Equity (Part 1)
jerry9789 0 comments artificial intelligence, Brand Surveys and Testing, Brandview World
AI Is Disrupting The Shopper’s Experience
There’s a paradigm shift in the shopping process and AI is the driving force behind this change. Shoppers are no longer just searching online or scrolling through websites; they’ve now taken advantage of AI platforms to discover, compare, and even buy products in their behalf.
According to generative engine optimization (GEO) firm The Rank Collective, their analysis of cross-platform AI visibility data revealed that 64% of consumers are now using AI tools to discover and learn about new products, with frequent online shoppers increasing that share to 66%. ChatGPT serves as a starting point for 34% of these high-intent users.
Another study based on two multi-market surveys of 5,000 consumers aged 18-67 comprised of US, UK, Canadian and Australian residents reported that 41% of consumers trust Gen AI search results more than paid search results. That same study- the 2025 Consumer Adoption of AI Report- also found that only 15% trust AI less than search ads.
Additionally, Adyen’s Retail Report shared that 51% of shoppers are open to AI making purchases in their behalf. It also noted that the number of US shoppers using AI assistants rose from 12% to 35%. With these encouraging figures, 88% of retailers are considering adopting AI to handle the entire shopping process in the shopper’s behalf, with 56% of them prioritizing this technology for 2026.
Image: Google DeepMind
LLM Equity and Brand Building
AI has opened up a new world of fast and frictionless shopping experience. While still in its early stages of adoption, companies have begun exploring this new space to understand what challenges it would need to address in order to compete and thrive.
Perhaps a good starting point is understanding Large Language Models (LLM) equity. LLM equity generally refers to ensuring that AI models are fair, unbiased, and accessible across diverse populations, preventing the reinforcement of existing disparities. It requires addressing algorithmic bias in training data specifically with race, gender, and socioeconomic status, especially in the field of healthcare. It’s also concerned with expanding access and at the same time, performing in non-English languages and low-resource settings.
For brand building, LLM equity is more concerned with whether your brand shows up in Gen AI search results and how it’s being represented. What theme or themes are being represented by your brand? Are those themes coherently represented in your social media? Is your current brand representation connecting and engaging with your audience? Is that connection strong enough to not only move consumers to purchase your product but also engage with your content? Is your brand content strong enough to capture the interest and be remembered by prospective consumers?
In other words, understanding LLM equity in brand building is understanding and tracking your brand health.











