Predictive Analytics in Retail Industry
Looking at the growth of today’s industries, retail is the one that’s producing more data than ever. Be it the number of customers and their details, inventory, supply chain or employees, there is always a pool of data that can translate into useful information. Therefore, it is becoming more important to convert this data as the industry is growing at a rate of 3% per year.
But how will the companies find relevant information based on the data? What algorithms should be used? Or what parameters should be considered? All of these questions have the same answer- Predictive analytics. In an industry that solely relies on the need and requirement of the customers, predictive analytics is the key to success. It can help in building a strong revenue and customer base. With the help of predictive analytics, retailers can enhance their operations and smoothen their supply chain. Hence, giving them an edge over the competitors.
Some of the key applications of predictive analytics in retail are:
- Resonating with Customers: The prime focus of any retailer is to retain its customers. Even a single day’s data can generate helpful insights. But retailers need to understand the buying history, shopping preferences etc. to reveal potential opportunities to engage customers. By using predictive analytics, retailers can foresee the needs of the customers and provide them a personalized shopping experience.
- Inventory Management: How helpful it will be if retailers could foresee the requirements of customers?! Predictive analytics makes it possible. Retailers who deploy predictive analytics can assess the demand of the market and plan their inventories accordingly. It ensures that the stock that you are buying doesn’t convert into sunk This reduces the inventory expenditures to a huge extent.
- Marketing Campaigns: It is easy to analyze the lifestyle and buying behavior of customers based on their data. By leveraging this data with predictive analytics, retailers can plan their promotion around it. The more relevant the campaign is, the more interested the customers are. This helps in improving the ROI and enhances the buying experience for customers.
- Pricing Decisions: Setting price for a product is nothing less than rocket science. A small mistake can result in losing market share and customers. Predictive analytics can analyze the inventory and quotes of competitors and determine what the prices should be. The right prices can boost up the sales and increase profits. Companies are continuously considering analytics to ensure better results in competition.
- Catchment Analysis: One of the key aspects of retail sales is the location of the retail store. Where should be the shop opened? What should be its proximity to its competitors? All of these questions are answered by predictive analytics. Retailers can make decisions based on demographics, lifestyle, and competition.
It has now become important for the retailers to incorporate analytics into their infrastructure if they want to stay in the competition. Companies that innovate with changing times and harness the power of analytics can optimize their efforts and garner better results with the proactive strategies emerging from real-time insights.
Most of the analytics tools that are present in the industry take a lot of time to analyze data. By that time, the needs of the customers might change. At Kaara, we have developed products that leverage our skills to minimalize the time-to-market for our customers. Our developers have built data pools which makes it easier to map databases, hence reducing the time frame for marketing. Visit Kaara today to know more!