Computational Consumer Insights: Using AI and Machine Learning to Understand Consumer Preferences


Summary

The globalization and digitalization of the world have given consumers more information and choices than ever before. At the same time, it has become easier for businesses to collect consumer data from online surveys and other sources. Thus, Consumer Insights has become a key pillar of business strategy. The objective of consumer data analysis is to find valuable business insights. We view Consumer Insights as an information game where the goal is to uncover as much relevant information as possible about consumers, with the least costs and efforts. We believe that human-driven technology is the key to enhancing human capabilities in data insights, by leveraging computational and algorithmic power. We use Artificial Intelligence (AI) and Machine Learning to create the next-generation tools for Consumer Insights. AI and Machine Learning must be used in conjunction with Human insights to create value and we call this Human-Driven Artificial Intelligence (HD-AI). HD-AI can also be used to optimize survey design and data collection. Asking the right questions increases the quality of consumer data, which in turns improves business insights. Our technology can also automatically process free-text data from open-ended survey questions.

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