Understanding Predictive Analytics Retail

Predictive analytics retail helps retailers breathe a little easier. With these tools, they can meet consumer needs and stay competitive. These types of tools can also help retailers understand their customers’ preferences and improve customer service. Here are some examples of how predictive analytics can help you. These tools are available for both small and large businesses. Learn more about Lynx Analytics and retail analytics at

How is prescriptive analytics used in retail?

The retail industry has changed a lot over the past decade. Changing consumer demands and expectations have created a number of challenges for the industry. Luckily, there are new technologies to help retailers overcome these challenges. One such technology is predictive analytics. This technology uses historical data and algorithms to predict what will happen next. Ultimately, this helps retailers optimize the entire supply chain and make improvements at the ground level.

Using predictive analytics can help retailers anticipate demand, optimize supply plans, and avoid potentially harmful situations. It can also help them boost customer satisfaction and operational efficiency. For example, it can be used to optimize store layouts and staff schedules. It can even help retailers predict spikes in foot traffic.

What are examples of analytics used in retail sales?

Predictive analytics is a process whereby companies analyze data from the past and present in order to provide predictions for the future. Its applications include the personalization of shopping experiences, inventory management, setting competitive prices, and identifying emerging trends. It also eliminates key challenges faced by retailers and provides an evidence-based platform for decision-making. The benefits of predictive analytics in retail are numerous, and it can help organizations stay on top of the competition, lower expenses, and increase ROI.

One example is Nestle. Its analytics system helped it reduce inventory by 20 per cent. Its method went beyond seasonal trends to simulate “what if” scenarios regarding various indicators of demand. Those predictions proved to be accurate. Another example is finding optimal retail locations. This can be accomplished by studying demand patterns and neighbourhood demographics. With the help of data analytics engines, the process can be automated.

Lynx Analytics Retail Analytics

Lynx Analytics is a data analysis solution provider that helps retailers improve the efficiency of their supply chains. They use camera technology and CRM tools to collect data about customer flow. The goal is to maximize sales productivity by matching customer demand with supply. This helps minimize wastage, streamline inventory, and ensure that items are channelled to where customers are likely to buy them. Using data from different sources, Lynx Analytics can answer questions like: how to cluster stores for maximum sales, how to improve assortment planning, what to stock at the right price, and whether to markdown or replenish inventory.

Lynx Analytics is a Singapore-based company that offers a complete suite of retail analytics solutions. Its AI platform, powered by Apache Spark, enables real-time processing. The company also offers a Customer Happiness Index solution, network design, and big-data platforms. Its customers include Singtel, Vodafone, DBS, and HKT.

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