Category: Quantitative Research

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The Use of AI in Quantitative Research: What to Adopt, What to Avoid

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.

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Show Me, Don’t Tell Me.

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).

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eBook: Measuring and Optimizing the Customer Experience

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.

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Market Sizing Using Top-Down Insights

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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Price Modeling: Applying Science When Data is Scarce

Historically high and stubbornly persistent inflation in recent years has wreaked havoc on more than just consumers’ wallets. It has also had the effect of throwing many companies’ pricing strategies out of whack and into question.

Rather than play a hunch, the smart money is on a proven methodology for setting pricing strategy based on hard facts, figures and formulas.

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