Insights - The Technology behind the Evolution of Shopping.
The Technology behind the Evolution of Shopping.
Understanding what makes life simpler, easier and better for users (be it persons or businesses) is the prerequisite to create compelling and engaging user experiences for them. Starting from the user's daily life and journey offers a natural way to identify user tasks whose execution can be improved. The inherent clarity of this approach makes it easier to choose the most appropriate technology to create improvements to user experience. As an example, we look at how shopping experience evolved and how technology has enabled this evolution.
Up to 2005, purchasing in-store was the primary means of acquiring goods. With the introduction of fixed broadband, shopping became more convenient as technology enabled shoppers to research and purchase online while siting in front of a computer. Mobile broadband removed the attachment to the computer, leveraging the mobility of devices connected to mobile networks. Subsequently, social networks improved shopping confidence and speed by introducing facilities such as community ratings and one-click purchase. Since fairly recently, it is even possible for connected devices e.g. fridges to perform purchases after asking for and receiving the user's permission.
Moving forward, there are many possible paths for the shopping experience that may or may not materialise despite the fact that enabling technology might be readily available. Our picture shows one such possible path (in gray color).
- Big Data and Analytics could be used to enable connected devices (intelligent fridges) perform purchases based on rules defined by the user. In rule-based replenishment, the technology matches user preferences to information computed from historical patterns to implement rules like "always buy vegetables from local producers (rule), based on our usual seasonal consumption (big data, analytics), even if the price is 10% higher than the market average (rule, big data, analytics)".
- Artificial intelligence could be employed to enable use cases that are more interconnected with our life. For example, despite existing rules, an intelligent fridge could "independently" order more drinks, when a party is arranged on the user's connected device / calendar (predictive replenishment).
Whether the future shopping experience we describe will materialise, will most likely depend on the ability for users to "program" such rules simply and intuitively, rather than the availability of technology. This brings us to this article's key learning:
For an experience to be adopted by users it needs to make life simpler, easier, better. Technology is just an enabler.
CREDITS & REFERENCES
- Wikipedia: Artificial intelligence