How The Customer Fits In With Big Data
All companies striving to implement the latest cutting-edge techniques are familiar with big data, and have at least looked into the concept at a practical level.
More often than not it is used to analyse data about customers: their preferences, consumerism trends and behaviour predictions, but doesn’t directly interact with the customers or benefit them. Instead, it is used only for insight.
While this use is very efficient, it is relatively one sided. Because of this Dashboard has a firm opinion that the use of big data should be expanded into customer facing models. An example of such practise can be found in real estate; after the data has been collected and analysed, companies use it to create better packages for customers and be prepared for their demands. The customer facing aspect is included in the loan syndication services, where the collected, processed information can be shared with the customer.
A similar approach can and should be used in other fields, where there is a strong relationship with the customer. This can be tricky in oil and gas or mass technology, but companies from the IT, software and various retail sectors can add a level of rapport with their consumer by meeting their needs through bringing the insight directly to them. This can be particularly useful in customer service, for example, where the service isn’t only customised to fit the individual needs, but the customer will receive information on what other users found solved their problem or how they used a certain tool. This data visualisation is a way to show customers how they can benefit from big data and simultaneously create a higher level of trust into the research the provider does.
Sharing the findings from big data is very low-cost, but can have a massive impact on the customer. As transparency is gaining significance and weight in today’s business code of conduct, being open is key to reliable relationships with business partners as well as customers. This is why Dashboard is an advocate for sharing big data findings with customers.