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The origins of the term “digital twin”can be traced back to NASA’s space program of the 1960s, when engineers created highly accurate ground-based replicas of spacecraft and their systems. These counterparts enabled teams to monitor performance, simulate various scenarios, anticipate failures and test solutions, all without putting astronauts at risk. The most famous example of this is the Apollo 13 mission, during which NASA used a replica of the damaged spacecraft to develo

Qualitative research allows us to go beyond raw numbers, revealing the motivations and emotions underlying consumer decisions. However, access to this level of insight comes at a cost: compared to quantitative approaches, organizing in-depth interviews is both more time and more resource intensive. Moreover, as it requires the simultaneous availability of both the researcher and the respondent, a single moderator can only conduct a limited number of interviews per day, even w

In a retail environment defined by visual clutter and split-second decisions, trade marketing can no longer rely on intuition or post hoc learning. Most wobblers, stoppers, displays, shelf cards and other POS materials are produced and deployed without any pre-testing. When evaluation does occur it is often slow, expensive and limited to small eye tracking studies. PROSPECT, an AI powered cognitive visual analytics platform, changes this. By forecasting the real impact of in

Packaging is one of the most crucial brand assets and a critical in-store touchpoint to win over the shopper, so it is no surprise that packaging regularly goes through extremely detailed consumer-perspective evaluations. Classic research approaches, however, are slow, expensive and resource-heavy processes. Eye-tracking studies and consumer panels require specialized equipment, controlled environments and significant budgets. While these approaches do provide valuable insigh

In an era defined by rapid innovation and information overload, market research is undergoing a profound transformation. Traditional methods rely heavily on manual coding and subjective interpretation of open-ended responses; however, these are no longer sufficient for organizations that need to make data-driven decisions at the speed of modern markets. Mad Research’s Vision—automated concept analysis pipeline—represents a major step forward within a suite of automated market