Low Fidelity
Low Fidelity
Low Fidelity
Customer Reality
Overview
A Customer Reality test is an ethnographic research experiment that helps us deeply understand how customers experience a particular challenge or process in real-world settings. At Future Foundry, we use this method when developing customer-centric solutions that need a clear understanding of daily habits, work environments, or purchasing behaviours. Rather than asking customers what they want, this experiment observes what they actually do—revealing unspoken pain points and opportunities that traditional interviews or surveys might miss.
A Customer Reality test is an ethnographic research experiment that helps us deeply understand how customers experience a particular challenge or process in real-world settings. At Future Foundry, we use this method when developing customer-centric solutions that need a clear understanding of daily habits, work environments, or purchasing behaviours. Rather than asking customers what they want, this experiment observes what they actually do—revealing unspoken pain points and opportunities that traditional interviews or surveys might miss.
A Customer Reality test is an ethnographic research experiment that helps us deeply understand how customers experience a particular challenge or process in real-world settings. At Future Foundry, we use this method when developing customer-centric solutions that need a clear understanding of daily habits, work environments, or purchasing behaviours. Rather than asking customers what they want, this experiment observes what they actually do—revealing unspoken pain points and opportunities that traditional interviews or surveys might miss.
Process
We select a small number of representative customers and observe their typical day, focusing on how they interact with products, services, or processes relevant to the experiment. Depending on the industry, this might involve shadowing them at work, following their consumer decision-making process, or analysing their digital behaviour across platforms. Insights are documented in detailed reports, journey maps, and video/audio recordings, capturing both stated frustrations and behavioural evidence of friction points. Patterns are then extracted to inform feature prioritisation, workflow improvements, or entirely new business models.
We select a small number of representative customers and observe their typical day, focusing on how they interact with products, services, or processes relevant to the experiment. Depending on the industry, this might involve shadowing them at work, following their consumer decision-making process, or analysing their digital behaviour across platforms. Insights are documented in detailed reports, journey maps, and video/audio recordings, capturing both stated frustrations and behavioural evidence of friction points. Patterns are then extracted to inform feature prioritisation, workflow improvements, or entirely new business models.
We select a small number of representative customers and observe their typical day, focusing on how they interact with products, services, or processes relevant to the experiment. Depending on the industry, this might involve shadowing them at work, following their consumer decision-making process, or analysing their digital behaviour across platforms. Insights are documented in detailed reports, journey maps, and video/audio recordings, capturing both stated frustrations and behavioural evidence of friction points. Patterns are then extracted to inform feature prioritisation, workflow improvements, or entirely new business models.
Requirements
This experiment requires deep customer access, consent for observation, and a structured method for documenting findings. The best results come when paired with quantitative validation, ensuring insights translate into scalable product improvements.
This experiment requires deep customer access, consent for observation, and a structured method for documenting findings. The best results come when paired with quantitative validation, ensuring insights translate into scalable product improvements.
This experiment requires deep customer access, consent for observation, and a structured method for documenting findings. The best results come when paired with quantitative validation, ensuring insights translate into scalable product improvements.
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