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From NASA's engineering to virtual shopping worlds: how digital twins are changing retail research

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 develop procedures that helped bring the crew safely back to Earth.

Today, thanks to advances in computing power, artificial intelligence and immersive technologies, digital twins can be used to replicate entire environments, such as shops, to study human behavior. By integrating behavioral data with advanced 3D visualization, virtual representations can be built that closely mirror real-world conditions.

Changing the Retail Decision-Making

Consumer behavior is increasingly dynamic and unpredictable. While shoppers face tightening budgets, they are also confronted with an ever-increasing number of choices, as innovation across categories intensifies. Under these conditions, seemingly minor factors such as packaging design, shelf placement, pricing cues or competitive adjacency can significantly alter purchase decisions.

As far as traditional research is concerned, many established methods rely heavily on declarative data: what consumers say they would do when confronted with real choices in a realistic context, rather than what they would actually do. This gap has created a need for a new research tool that reflects the real decision-making environment and captures behavior, rather than intention.

Digital Twins as Virtual Retail Laboratories

repliQ is built precisely on the digital twin idea. The tool creates a highly realistic virtual retail environment that consumers can 'walk' around inside and see shelves complete with products, prices, layouts, etc. This environment is flexible and can be modified, allowing researchers to test alternative configurations under controlled conditions. During web study real consumers/respondents are invited into the "digital twin" and can interact with it naturally, browsing and making purchase decisions as they would in real life. Their actions generate behavioral data that reflects their decision patterns, rather than abstract preferences or post-rationalized declarations.

repliQ enables multiple scenario testing, where alternative strategies, such as pricing, packaging and shelf layouts, are benchmarked against a baseline to quantify their impact. This is translated into core metrics which capture changes in units, volume and value, not only for the brand, but across the entire category. Moreover, repliQ shows how different scenarios influence penetration, loyalty and sources of volume, thereby effectively decoding whether growth comes from winning new shoppers or shifting existing demand. Finally, by analyzing basket impact, repliQ uncovers the retail environment's impact on consumer spending, choices and trade-up or trade-down behaviors.

As a result, repliQ delivers insights that are accurate and predictive. It allows organizations to move from intuition-driven or declarative decision-making toward evidence-based optimization, by testing strategies in realistic conditions before committing resources in the real world.

Technology Foundation: AWS-Powered Scalability

repliQ is built entirely on AWS infrastructure, ensuring scalability, reliability and enterprise-level performance. The platform leverages key services such as Amazon EC2 and Amazon S3 for compute and data storage; AWS Lambda and AWS Amplify for serverless execution and rapid deployment; and Amazon SageMaker to support advanced analytics and AI/ML workloads. This cloud-native architecture enables large-scale simulations, rapid scenario testing, and efficient processing of complex behavioral datasets, while maintaining flexibility as research needs evolve.

Conclusion: Uncovering Human Truth Through Machine Power

By combining the scientific rigor of behavioral research with the scalability of digital twin technology, Mad Research enables organizations to test, learn, and optimize decisions in environments that truly reflect how people shop. In a world of growing complexity and uncertainty, repliQ exemplifies how machine power can be used to uncover human truth, before real-world decisions are made.