ChatR AI Brand Perception Tracking

People are talking to AI…
what is it saying about you?

Consumers are increasingly relying on AI tools to navigate and enhance their shopping journeys across discovery, research, product comparisons, and purchase. Vital Findings AI Brand Perception Tracking gives you insight into this emerging world of AI conversations. Innovated by tracking experts, chatR is a proprietary market research tool that measures how LLMs – individually and in aggregate – recommend and describe your brand when consumers ask for shopping advice.

Learn more about ChatR

How it works

Define Relevant Personas

Short definitions of your key marketing segments, steered by relevant attitudes, demographics, and your product focus areas

Gather Realistic Scenarios

Actual questions each persona would ask an AI assistant when shopping ie. Which shoes are best for running on pavement?

Generate Conversations

Scenarios are posed across major LLMs (ChatGPT, Gemini, Claude, Grok), capturing each model’s full response along with a structured data follow-up

Aggregate & Score

Responses are quantified: which brands are recommended, who’s first, how is each brand characterized, and what sources are AIs using to answer

What you can do with it

Understand & track your position across scenarios

Identify messaging or product gaps showing in market

Develop strategies to shift the conversation

Case Study

the opportunity

A footwear company wanted to understand their performance as a Lifestyle shoe, overall and among 18-24 year olds. VF used our proprietary AI Brand Perceptions Tracking solution – chatR – to answer their question & provide concrete recommendations.

our approach

First, we defined Core themes underpinning Lifestyle shoe decisions:

  • Everyday Comfort
  • Style & Versatility
  • Performance Cushioning
  • Trends & Cultural

Then, we generated a variety of real-world questions that consumers are asking AI about Lifestyle shoes within each theme. For example:

  • Everyday Comfort Question: Looking for comfortable sneakers I can wear all day — what do you recommend?
  • Style & Versatility Question: What sneakers do you recommend that go with pretty much everything?

16 questions were then asked across 4 popular AI models, once with no user age specified, and again with a user age of 18-24 specified (128 unique chats).

Results showed a clear gap – the client brand was leading Everyday Comfort and Performance Cushioning, but non-existent in Style & Versatility and lagging in Trends & Culture. 18-24 results showed the same – with even poorer performance in Trends & Culture.

the results

Based on the results and rationale across AI chats, concrete recommendations were made that address different aspects of the lagging performance:

  1. Seed the market with the desired info. There is a notable absence on the internet for styling the client brand, outfit or occasion versatility, and an absence from trends. AI answers from training data or by searching. The internet must contain something for AI to retrieve it.
  2. Target high impact sources. LLMs pull from specific sources – which we can see. Use this to target marketing & brand or product info to influence each of the LLMs.
  3. Strategic decision about the product. For consistently winning brands, AI noticed a pattern. The client brand’s current portfolio does not fit into that pattern. This departure is not breaking through in style or culture at a level that impacts recommendations.