Understanding a consumer’s needs and preferences can often be a challenging task. Many have hoped that artificial intelligence and machine learning (AI/ML) algorithms will make it easier for market researchers to identify critical information to better target customer groups. The release of ChatGPT, a new chatbot system created by OpenAI that leverages natural language processing (NLP), is a tool that could help researchers cut through all the noise in traditional market research methods.
ChatGPT could help researchers quickly and easily automate the collection of customer feedback. They could use the platform themselves to scour the World Wide Web or, alternatively, use the technology’s chat interface to ask users targeted questions to gain insights into customer needs, preferences, and experiences.
The platform is designed to work with users in a conversational manner, so much so that customers may even think they are chatting with another person. As they interact with the chat, they can ask follow-up questions if they don’t understand something – or challenge preconceptions or errors they may see in the questions.
Proponents of AI say ChatGPT offers the potential to mine richer data and, consequently, more actionable insights – and that’s just one reason why the technology has gotten so much hype since its release last year. It is important to remember, however, there are some downsides to its use.
ChatGPT is only as good as the data it’s trained on, so if your team doesn’t have a strong handle on the product or service you are researching, you may miss critical information that could differentiate your marketing efforts. A second issue is that research studies have shown that ChatGPT can inadvertently add incorrect and/or biased content to its results. If you aren’t well versed in your subject matter, you may find ChatGPT providing information that will actually derail your efforts.
There’s no doubt that ChatGPT, and other AI/ML tools, will change the way we conduct market research in the future. But it’s important to understand what they can do – and what they can’t – to use them effectively to get to the kind of data that can further your research efforts.