Customer segmentation is much more than merely “categorizing” customers along traditional baseline filters: demographics, geographics, psychographics, and prior purchase history. While those data points are useful as far as they go, they simply don’t go deep enough.
Director Emily Bielak was invited to the Bullhorns and Bullseyes Podcast to discuss the topic of customer segmentation and why it’s more than sorting by demographics or even psychographics.
The integration of artificial intelligence into market research processes has been embraced by some as a game-changer, promising to streamline data collection, enhance analysis, and drive informed decision-making. However, as with any technological advancement, the advent of AI brings both opportunities and challenges, prompting researchers to navigate the terrain with caution and curiosity alike.
One of our recent innovations in our ongoing pursuit to optimize and perfect Emotion Intelligence research is the use of images in a “qual-then-quant” process to gain deeper and more authentic insights into how emotions and sentiment are driving purchase decisions (or not).
It is critical, when analyzing and working to optimize customer experiences, that three primary tenets of sound CX design be woven deeply into the fabric of the analysis, even when using artificial intelligence or other technology to do some of the information gathering and processing.
Without top-down analytics as part of the market research equation, one runs the risk of placing faith in two sources of data that have proven at times to be unreliable and substandard pictures of reality.
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