Ladle vs. tablespoon.
Saw vs. wood carving knife.
Lawn mower vs. weedwhacker.
Tools are typically created with an intended use in mind. And while you can often use a tool multiple ways, the most efficient and effective results are usually found by using the right tool for the job. A tablespoon works much better for eating soup than a ladle, although the ladle is more efficient for serving it. And a lawn mower cuts your grass much faster than a weedwhacker, but can't get those detailed edges that make a great lawn look so neat.
The same is true of AI and large language model tools. There are many AI tools available for use, with ChatGPT being one of the best-known and widely used. We often get asked the question, why can’t I just use ChatGPT for market research? Let’s explore the answer.
ChatGPT, powered by OpenAI, is an AI language model designed to engage in human-like conversation. It leverages deep learning algorithms to generate text (think blog posts, outlines, content ideation etc.) based on the input or prompts it receives, making it a versatile tool for various applications. And at this point, most of us have played around with it to see what it’s like to ‘talk to a machine.’
ChatGPT has a broad application, making it perfect when you need to ‘go wide’. It does lots of things well but it’s not designed to be specific to an individual use case. Consider ChatGPT your saw…it can cut the wood, but it can’t carve the figurine. So, if you’re trying to determine if ChatGPT is the right tool for your insights project, you should keep your goals in mind. Do you need broad information or actionable insights specific to your business?
While ChatGPT excels as a conversational agent, the data is typically old and stale. This is because the areas that ChatGPT and the models it was built on were created to address don't shift and change as quickly as MRX-specific data like brand sentiment. Concepts like the Pythagorean theorem and other mathematical rules for example have been around for millennia. The most advanced (ChatGPT Plus only) models are good for basic code implementations, code debugging, and basic data science, but none of these constitute a supplement for real-time market research.
Let’s look at some of ChatGPT’s key features and use cases to help you out.
Key Features:
ChatGPT does many things well. But it’s an off-the-shelf solution that can only offer so much customization, even with targeted prompts. And if you’re not skilled at providing ChatGPT with the appropriate prompts you may find your output unhelpful and generic, sounding more like a computer and less like your brand.
You will also find a lack of repeatability in your answers, and you will need to consider your source. With ChatGPT there are some important ways the results cannot be trusted (recency bias, self-consistency bias, overly positive scoring bias) plus hallucinations when ChatGPT cannot find relevant data to answer your questions. This is where much of the negative feedback from synthetic data testing has stemmed.
And while everyone has access to ChatGPT…you also need to be very careful with privacy. If you haven't got your settings correct, any information you input into this LLM trains its model.
Yabble's Virtual Audiences – The Wood Carving Knife
If ChatGPT is the saw, Yabble’s Virtual Audiences tool is the paring knife: versatile, capable of providing detail, and built with insights creation in mind by and for researchers. Yabble’s Virtual Audiences aren’t just simulations; they're dynamic AI-driven personas that emulate real customer interactions, providing invaluable insights into consumer behavior. These personas generate responses as if they were real individuals, making them invaluable for understanding consumer behavior and preferences at depth.
Yabble’s Virtual Audiences are powered by our proprietary augmented data model, which uses the combined knowledge of Large Language Models (LLMs), relevant and recent trend data, social data, and behavioral statistics to create a unique AI-generated audience to answer your research questions. What’s more, you can add your own data into the model to make it even more specific for your brand and audience. This unique approach via the Yabble platform provides increased relevancy, recency, depth, and accuracy of data above what a large language model alone can provide.
Yabble's Virtual Audiences tool streamlines the insights generation process, turning hours or even days of work into mere minutes. It allows for insights to be created without the traditional fieldwork stage, meaning that insight generation can almost be instantaneous. What’s more, the outputs are rich, detailed, and insightful. Think specific.
This idea of using natural language to analyze data is fundamentally changing the insight landscape. Not only does it democratize the insight generation process, but it accelerates the speed to insight and enhances the ability of data to live in an organization.
When deciding between ChatGPT and Yabble's Virtual Audiences for market research, it's essential to consider the specific needs and objectives of your project, the nature of your research, the level of interaction needed with your specific segment, and the resources available for analysis and interpretation.
ChatGPT excels in going broad and providing generic responses making it ideal for brainstorming, ideation, and creating at scale. On the other hand, Yabble's Virtual Audiences can provide more custom, reliable, and recent insights based on your unique segments, in a format that is ready for a researcher to use.
So you can use ChatGPT to dip your toes into generative AI, but make sure you know which tool you need…a saw or a carving knife. And if you understand the limitations of each tool, you can leverage the appropriate AI-driven technologies to gain deeper insights into consumer behavior and drive informed decision-making.
If you're ready to use the right tools to start making data-driven decisions backed by insights you can trust, book a demo with the Yabble team today.