MFour adds Google Gemini conversations to consumer data platform

Expanding the AI data map

MFour Data Research, Inc. has officially added Google Gemini to its collection of AI conversation data. This move expands the company's reach into how people interact with different large language models (LLMs) during their daily lives. By including Gemini, the platform now tracks 2.35 million unique AI conversations every 30 days.

The addition of Gemini brings the total number of consumer-generated messages in the dataset to 10.1 million. These messages come from users interacting with both ChatGPT and Google's AI. This data provides a broader view of the current AI landscape, showing that consumers are diversifying the tools they use for information.

As MarTech Cube reported, the goal of this expansion is to provide brands with a more complete picture of the modern consumer journey. Because Gemini is a major competitor to ChatGPT, having data from both allows for a more comprehensive analysis of how different AI personalities influence user behavior.

Connecting prompts to purchases

What makes this dataset unique is that MFour does not just look at the text of the conversation in isolation. The company links each AI interaction to what the same consumer does next in the physical and digital worlds. This includes tracking online activity, app usage, and even GPS-verified store visits.

By connecting these dots, the platform can show the path from a specific AI prompt to a final checkout. For example, a brand can see if a user asked Gemini for a product recommendation and then subsequently visited a local store to buy it. This level of journey intelligence helps bridge the gap between digital research and physical commerce.

The data is captured at the account level, which means it covers conversations happening in the Gemini app on mobile devices as well as on desktop browsers. This ensures that the data reflects how people use AI across different environments and hardware types throughout their day.

Tools for deep research

Brands and agencies can access this information in two primary ways. They can choose to license the raw dataset directly to perform their own internal analysis. Alternatively, they can use DANI™, which is MFour’s AI-powered analyst, to generate specific reports based on the data.

DANI is designed to handle the heavy lifting of data processing by running autonomously for hours. It can sift through billions of signals to find specific insights and recommend next steps for a business. This allows researchers to go from a simple question to a finished report using only a single prompt.

Furthermore, DANI can connect the 'why' behind the behavior by surveying the same consumers who provided the data. This creates a single workflow where a company can see what a person did, what they asked an AI, and then receive a survey response explaining their underlying motivations.

Ethical data collection

The data for this platform comes from MFour’s first-party panel, which consists of members who explicitly opt in to share their information. These participants agree to share their behavioral data across the entire path to purchase, from the initial research phase to the final transaction. This opt-in model is central to how the company gathers its insights.

MFour emphasizes that they follow ethical, fair-trade practices regarding this data collection. Panelists are compensated for two distinct actions: sharing their behavioral data and participating in surveys. This ensures that the consumers providing the data are aware of its value and are rewarded for their contribution.

By maintaining a first-party panel, the company can ensure a higher level of data integrity compared to third-party sources. It allows for a more consistent flow of information, including demographics and web browsing history, which are tied directly to the AI conversations and purchase behaviors.

The shift in brand visibility

The inclusion of Gemini data addresses a growing concern for marketers who feel they are losing sight of how consumers make decisions. As AI becomes a primary tool for research, brands need to see those conversations to understand where they win or lose consideration. Without this visibility, a significant portion of the buying decision remains hidden from traditional marketing tools.

Chris St. Hilaire, CEO of MFour Data Research, noted that adding Gemini expands visibility beyond just ChatGPT. He explained that it reveals how consumers interact with AI and what they do next online or in-store. This suggests that the way people seek advice is fundamentally changing the way products are discovered.

Looking ahead, the integration of more AI platforms into consumer data sets will likely become the standard. As more people turn to AI for personalized shopping guides and comparisons, the ability to track those specific interactions will become essential for any brand trying to understand modern consumer behavior.