More and more retailers are embracing the power of Big Data. It’s an investment that promises high returns in the form of increased customer loyalty, boosted sales, greater efficiency, and long-term rewards to the bottom line. In a recent survey conducted by the Intelligence Unit of The Economist, retail industry executives reported experiencing numerous, significant benefits from implementing Big Data analytics in their operations. Interesting highlights from the findings are noted below:
- Marketing is still a main focus and a high priority for data analysis spending
- Big data analysis is helping to drive brand loyalty and expand sales—but respondents think it can do more
- Data delivers in coordinating omnichannel commerce, bringing sales gains and greater profits to multi-channel customer tracking and management
- Strategy is set to become the most important area of focus for big data in retail, supported by relevant investment in data analysis
- Investment in data analysis has overwhelmingly seen a positive economic return
However, there’s an interesting flip side to this growing trend: uncertainty and apprehension about the sheer volume of retail data. According to the survey report, half of the executives admitted to having problems managing and making sense of the trove of data available to them. In many cases, these problems have led to doubt over how much their retail operations could truly benefit in the end from data analytics. Feeling overwhelmed under a surge of Big Data can easily quash enthusiasm for its power and ultimately hinder its adoption in the retail space.
But it doesn’t have to be this way. Armed with the right tools, you can easily make sense of the high volume of retail analytics data. The key lies in having sophisticated software to do the heavy lifting. Not only should that software be comprehensive and powerful enough to gather and process the large quantity of analytics data, but it should also be versatile, easy to use, and clear in how it presents the information gleaned from that data. And even better, it should exist as a single solution that works cohesively with all the data sources involved.
In other words, taming and interpreting the trove of data from your retail operation demands an analytics solution that can handle quantity and complexity with simplicity. And that requires software that’s robust in each of four steps of the analytical process: collection, analysis, visualization, and insights.
Collection. Before an analytics solution can present you with valuable information, it should collect the maximal amount of diverse data. It need to be versatile enough to integrate with the physical and digital data sources already inside and around your store(s), seamlessly adapting to your existing infrastructure of cameras, sensors, wireless hardware, workforce management and POS systems to name a few. Doing so not only ensures that you’re making the most of all the data available from your retail operation, but also makes installation, activation and access to the store data access quick and easy.
Analysis. Once it accumulates all the data available to it, a truly robust solution should analyze and organize it into a single place, either in the cloud or on your premises. A sophisticated analytics engine will be able to slice and dice large volumes of retail data, identifying trends and patterns and raising red flags to events and details about your operation that may otherwise have gone unnoticed. It harmonizes the data and overlays various store trends and patterns to offer deeper, more comprehensive insights into shopper behaviors and store performance.
Visualization. But beyond collection and analysis, the real key to robust and powerful analytics software is how concisely, flexibly, and easily it presents the information about your operation. It should depict data in a variety of useful formats, enabling you to discover and implement changes to improve the customer experience and your commercial performance. It should feature a robust set of analysis tools and reports to allow you to visualize the data, identify its trends, and compare them across any time period. To make this process even easier, a retail analytics solution should allow you to access all this information using a variety of intuitive interfaces, whether from a desktop computer or a mobile device. What’s more is if it sends you real-time alerts in the form of pop-ups or emails to your inbox.
Insights. Lastly, a truly useful analytics solution should provide you with valuable insights into your retail operations and shopper behaviors that’s as vast as the amount of data it collects. Furnished with a precise, fact-based understanding of how shoppers behave and the impact on store performance, you can optimize your store layouts, fixtures, staffing, and even product offerings.
In the end, an in-store analytics solution should work with you and for you, relieving the burden of having to sift through the volume and complexity of your retail data. Sophisticated software coupled with a versatile and intuitive system of visualizing the information gathered is how the power of Big Data will fulfill its promise to you as a retailer.
To learn how you can use the power of Big Data to transform your retail operation, visit the RetailNext product page.