Even before customers enter an auto showroom, they have probably interacted online. (And their backend systems have already captured his profile online!) And once they are in the store, a virtual-reality station can help them visualise their dream car. All this data collated and analysed, across thousands of stores, can then be used to forecast consumer behaviour.
For example, one manufacturer noticed that the sales of a particular model of luxury two-wheelers had a high correlation with the digital signals they were tracking — such as the number of unique hits on the web page of this model, or the volume of social media chatter. By capturing this information, the company was able to integrate it into its business processes and to plan its production better, by increasing the volume of that particular model during specific periods. By using data, they were ready and able to act, rather than having to react in the guise of having to be “agile”. The principle at work is: “How can we best capture the signals, and capture them faster than others, that makes us know what the consumer really wants?”