Speculation around the future of retail often tends to drift into visions of drones flying through the skies and delivering packages within minutes of a consumer clicking a few buttons on a site. In this projection, the bricks and mortar retail stores are old fashioned, out of date and a relic of the past. Yet the reality of today’s retail environment is a far cry from that distant future. Today’s innovative retailers are harnessing information technology, and using Big Data and analytics in innovative and unusual ways, with a goal of enhancing the shopping experience, as well as gathering and processing valuable data that will help retailer’s better position themselves to meet the consumer’s needs.
What kind of insights are being gathered via big data in retail industry?
Many. For example, predicting which products are going to be most popular over the coming weeks and making sure that there is enough stock to meet the demand. Analyzing which branches of a retail chain are busier than others, what products they should be stocking, and who their customers are. Who the customers are in a particular store, what they usually buy and what else can they be offered to augment their shopping experience. All of this detailed and important information is being gathered via the intelligent use of Big Data as a Service (BDaaS).
In the retail environment, there are multiple points from which data is gathered. Customer transactions, loyalty programs, shopper behavior, store layouts, not to mention social media sentiment, macroeconomic data and much more. These all need to be factored into retail data analysis. Broadly speaking, retail analysis is divided along five streams: Store Analysis, Sales Analysis, Spend Analysis, Performance Analysis, and Customer Analysis. Each stream has a different focus but when they are taken together they allow a complete retail analysis to deliver a deep understanding of customer behavior to increase loyalty, increase conversion rate and average basket value due to efficient and targeted marketing campaigns, and reduce overall costs in the process. Great retail analysis can and should deliver a win-win situation for customers and store owners.
How can big data in retail be leveraged?
CloudMoyo is a Big Data Analytics firm with a wealth of experience in the retail environment. One of its flagship clients is the American technology giant Microsoft, and the two companies have recently worked closely on the performance of its chain of retail stores. The challenge that the tech giant was facing was to effectively monitor and measure the performance of each of the stores in their network, as well as analyzing the performance of their agreements with the respective landlords.
CloudMoyo faced a number of challenges in setting this up. Most of the data was scattered and difficult to analyze, there was no central collaboration system across the stores, and no system to visualize or analyze the data. As a result, it was almost impossible to predict trends and revenue from any of the stores. Through its experience and sophisticated cloud based data-monitoring solutions, CloudMoyo was able to create a centralized repository for documents, enable easy collaboration, develop state-of-the-art user interface systems with dashboards and install an easy system of tracking budgets, issues, risks and challenges via a simple email notification system. The solution enabled predicting store revenues, lease optimization, weather and demographic analysis of footfall etc.
While the solutions may seem technical, what they translate into is an opportunity to provide better solutions for head office and branch owners, as well as an improved experience for consumers, which will make them keep coming back for more. This is critical. CloudMoyo CEO Manish Kedia explains how “retailers need to be able to identify each customer, their behaviour, preferences, what makes them tick, and apply these insights across their preferred interaction and commerce channels. That is why being able to collect, analyse and leverage customer data is becoming increasingly important.”
The challenge in today’s market is not to gather more data, but to properly handle the data which one already has. If retailers are going to be successful in today’s market, they’ll need to know how to tie the right, relevant data together to meet business needs and drive desired consumer behavior. In-store analytics can help traditional retail operations understand consumer needs, improve employee efficiency, drive sales growth, and better appeal to customers. In the battle for consumer dollars, it’s one more way that traditional retailers can use technology to survive.
The benefits of working with a dedicated data analysis firm such as CloudMoyo are numerous. Retailers can outsource the tricky business of analysis and focus on what they do best, they can test out their insights and “hunches” about a business against real data, and they can put all the data they have been gathering to work, and make informed decisions.
If you feel your company would benefit from a 5- Day Azure Assessment workshop where CloudMoyo looks at your data structure and provides feedback and a roadmap for the way forward, then please get in touch with us.