Trust was traditionally associated with an emotion or a feeling, but individuals and businesses are increasingly putting their trust in technology. This has in part been facilitated by internet banking, mobile applications and even the technology features in driverless cars and even trains.
A trend that has been exacerbated by the business and consumer shift to keyboard shopping and validation as opposed to grabbing a physical trolley and heading to a retail outlet.
“Brands are facing an enormous shift in the way they present themselves to the world. As influencers start to lose their impetus and customers becoming more discerning around quality, businesses must turn to data to help them better package and deliver their offerings,” says Clinton Scott, managing director at TechSoft International.
“The data gathered from a variety of credible sources can be invaluable for planning, understanding customer behaviour, and even tackling challenges from supply chain disruption effects to identifying the financial impact of the current crisis.”
Collecting customer data in real-time provides businesses with the ability to be proactive in anticipating their needs which is in line with the increasing expectation of instant gratification.
Customers are more likely to share their grievances online with the expectation of an instant response from suppliers and service providers than to praise them.
Considering the vast volumes of data in the world, traditional methods of data analysis just won’t cut it anymore, and companies will struggle to achieve the desired results.
“It is all about being able to help your customer anticipate their next move on their behalf. It sounds like science fiction, but if you leverage the right datasets and know which ones you need to interoperate with your sales engine, you get closer to the customer’s buying truth. Admittedly, a lot of customers are still pursuing a path towards data unification, data analysis must be integral to the business strategy,” adds Scott.
But there are still challenges as data for data sake is just data and many businesses still need to manage, analyse, and rationalise huge siloes of data and marry these to communication channels that make datasets accessible regardless of their location.
Smart businesses rely on platforms that support their end-to-end analytics lifecycle while providing enterprise security and governance.
“With a data tool, you can analyse, continuously query, and act on the data derived from an IoT environment as well as streaming data sets from different sources, at lightning-fast speeds. Speed to information is critically important for brands,” Scott continued.
“This is especially for those that can take real-time operations and analytics to the next level, through the delivery of pertinent information to intelligent applications. Deploy these quickly and hook them into action-based models that refine and influence decision-making and models, all without extra overhead.”
“In the absence of a data science team, a data science platform easily operated and driven by citizen data scientists, will help your teams and users to deliver on their work, create insights in the same platform, and then share their knowledge. When a brand needs to expand past sales and into securing customer loyalty, the need to move beyond your own data becomes crucial,” added Scott.
“By expanding beyond their own data, organisations that seek and secure new information and external datasets can create converged analytics which unlocks hidden value for the company and its customers. Predictive analytics is an invaluable tool that is set to enable you to seize not only the moment but also anticipate the next— even before your customer does. Opening the way for loyalty and not just sales,” concluded Scott.