It’s high time for both traditional brick-and-mortar stores and e-commerce outfits to modernize and fine-tune the way they do business. With every new wave of technology also comes new challenges to fulfilling customer needs. The case is particularly relevant to the retail industry, in which retailers must manage their product line, stay on top of their customer base, and foster ambitions to grow and expand.
This is where the data side of it comes in. Machine technology has made it such that even months’ worth of important data can be available to retailers in an instant; patterns are easier to read, and actions that are important for the business (such as adjusting price points) are based on solid, accurate findings.
Thus, more retailers have begun to invest in upping their business intelligence in order to work smarter with the information that they accumulate about their customers, products and services, and their business at large. The key technology behind this is real-time data analytics. Being able to record, manage, and respond to high volumes of information via a system of real-time data analytics for retail will facilitate complex business decisions, make for efficient monitoring, detect fluctuations in customer behavior and customers’ spending habits—ultimately, analyze, on a wide scale, what will make the customer experience even better.
Read on to find out more about how real-time data analytics fosters business intelligence and paves the way for even better retail business.
Dynamic Responses to Customers’ Wants and Needs
The first thing that real-time data analytics capitalizes on is the customers themselves. Real-time technologies have the power to analyze interesting customer behaviors—for example, what the most popular searches are for a particular product and within a particular customer demographic; how the demand for a product rose when it was launched to the public and newly endorsed by a celebrity; or how much more customers purchased from a certain line of products based on weather and seasonality.
In this matter, it is important to note above all that customer behavior often fluctuates, and that a business can be affected at any given time because of these fluctuations. What real-time analytics can provide is resilience to these trends, via immediate preparation to address them and determining pre-emptive movements to give customers what they need, quickly and efficiently.
Another key area that real-time data analytics can improve is overall efficiency in management. Having access to reliable and up-to-date information about the retail business lessens any delays in decision-making for greater improvement. Once the information is readily available, it is immediately actionable.
An efficient data management system also enables greater efficiency from its human counterparts. Take the example of sales staff being able to process sales reports at a much faster rate, and at a more regular time period, as the data becomes more streamlined. The system will complement human efficiency and raise a standard for human performance in retail tasks.
Creating new, personalized shopping experiences
Lastly, real-time data analytics has enabled new profits to rise from increased spending on services, and customer loyalty—via personalized shopping experience. There is a higher chance of customers returning to retail establishments if they can acquire something that they feel is tailor-made for them and if they are given something more than generic treatment.
This comes into play through things such as targeted promotion campaigns, product curation, and the offering of in-house services such as product customization or tapering. A customer will feel as if he or she was reached out to as an individual, and will come away with an entire shopping experience that feels as is if it is uniquely “theirs.” An intelligent platform will help indicate what custom services are possible for your company to execute and how best to do so.
Ultimately, both customers and retailers are part of a dynamic and data-driven world. Rather than deal with problems such as information overload, or a scant system to generate and manage information when it is needed the most, it is possible to employ a system such as real-time data analytics to optimize business intelligence, fight stiff competition, and ensure the business’s longevity in the retail market.