Can large language models replace human participants in some future market research?

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Do market researchers nonetheless have to conduct unique analysis utilizing human contributors of their work? Not at all times, in response to a brand new research. The research discovered that due to the growing sophistication of enormous language fashions (LLMs), human contributors might be substituted with LLMs and nonetheless generate comparable outputs as these generated from human surveys.

The research is published in Advertising and marketing Science. The article, “Determining the Validity of Large Language Models for Automated Perceptual Analysis,” is authored by Peiyao Li and Zsolt Katona, each of the University of California, Berkeley; Noah Castelo of the University of Alberta and Miklos Sarvary of Columbia University.

In keeping with the analysis, settlement charges between human- and LLM-generated knowledge units reached 75%–85%.

“LLMs can be used to generate text when given a prompt on certain generative Artificial Intelligence (AI) platforms,” says Li. “Our analysis targeted on perceptual evaluation and the usage of automated for sure product classes.”

To conduct their analysis, the research authors used LLMs to faucet knowledge that’s broadly out there on the web. They developed a and workflow that enables market researchers to rely solely on an LLM to conduct market analysis. Consequently, they demonstrated that LLM-powered market analysis can produce significant outcomes and even replicate human outcomes.

“It is important to note that with LLMs, while market researchers may not require interviews with human research subjects, the ultimate data does originate from human beings, using available data,” says Katona. “LLMs have been engineered to accurately replicate human responses based on machine learning of actual human perceptions, attitudes, and preferences.”

Castelo added, “The core LLM takes a prompt as an input and generates a continuation of text as output. With proper prompting, the LLM can then generate comparisons and assessments of various brands or products in a given category and produce results that are, at the moment, 75%–85% in agreement with research featuring .”

The researchers imagine that for some product and model classes, their new methodology of absolutely or partially automating market analysis will improve the effectivity of market analysis by dashing up the method and doubtlessly decreasing price. On the identical time, they warning that absolutely automated market analysis with out human enter will not be correct for all product classes.

“While we are very excited about the possibilities we’ve seen through our research, we recognize that this is just the beginning and going forward, LLM-based market research will be able to answer more nuanced questions as the market research field begins to tap and develop its potential,” says Sarvary.

Extra data:
Peiyao Li et al, Frontiers: Figuring out the Validity of Giant Language Fashions for Automated Perceptual Evaluation, Advertising and marketing Science (2024). DOI: 10.1287/mksc.2023.0454

Can giant language fashions exchange human contributors in some future market analysis? (2024, April 9)
retrieved 9 April 2024

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