Technology and data innovation can open a number of doors to retailers looking to maximize revenue and customer satisfaction. However, even though Big Data is now an established fact of business, the majority of firms are still not leveraging the wealth of information available to them to anywhere near its full potential.
While many retailers have implemented connected devices as a means to improve their customers’ experiences, the majority have not got the accompanying analytics tools in place needed to actually use the data captured. They have a substantial amount of data but no idea how to use it, leaving a disconnect between what they are offering and what the people actually want.
The most successful retailers are those who have integrated customer analytics, data innovation, and the internet of things (IoT), and are using the insights to align their product offerings with customer demand.
When retailers realise the potential of the data stored in their connected devices and IoT infrastructures and turn it into intelligent product recommendations, offers, pricing, and personalized ideas - all of which can dramatically improve the customer experience - they will be rewarded with long-term loyalty, an increasingly rare commodity in retail.
The first thing to note is that consumers are aware of the amount of data being collected by firms, and they expect to see a return on this. They understand that it is a trade-off, and that the vast amount of personal details they are handing over online are being used for a range of purposes for retailers' own benefits, but they expect to be paid back with a seamless retail experience. This is far more achievable when IoT, analytics and data innovation are integrated as there is greater scope for customer segmentation, meaning people can be treated as individuals and their needs better understood.
It is also important to understand that marketing is not the only area of retail that Big Data can be applied to. It can be used across all areas of the company, from optimizing price structures to inventory management. For example, by analyzing customer habits to predict demand, you can far better control inventory levels and limit costs of storage and unnecessary transport.
Gathering as much information as possible across the firm is vital, but it is also important to be selective about which insights are deemed actionable. Some are not practical to apply to day to day practice, returning trivial amounts compared to the cost of implementing them.
While customer analytics is now affordable, there is still need to invest as quickly as possible in order to gain a competitive edge, or at the very least keep up with other firms who are integrating their analytics and IoT.