The retail industry is highly competitive, with traditional retailers under pressure from E-commerce services. In this competitive environment, anything delivering an advantage to traditional retailers has to be seized quickly. Predictive analytics offers enormous benefits to retailers using such a program; they can turn Big Data into an actionable insight that further enables better understanding and interaction with customers. According to research, the usage of essential data by retailers can help them increase their profit margins. This article enlists some benefits of predictive analytics software for the retail industry.
Improved customer experience
As per experts, companies that can improve their customer journey can increase their profits and reduce their costs to a great extent. The best predictive analytics software lets a retailer gain a much clearer and more granular understanding of their customer- what they like, their attitudes, preferences, and behaviours. Storing all this data in predictive analytics models further helps retailers know what products their customers would like and can communicate with them.
Personalized and targeted marketing
Personalization has become essential for every retailer as it helps them build profits and loyalty. Most retailers are uniquely positioned to collect a range of data on each customer, including their likes, preferences, buying pattern, shopping history, and more. With predictive analytics tools, a retailer can begin personalising every aspect of the marketing and engagement strategies with targeted customers.
Reduced customer churn
It is a well-known fact that it costs far more to attract a new customer than to retain the existing ones. A retailer needs to know when a loyal customer begins to disengage with his company or brand. It is predictive modelling that can help retailers understand which customer is straying, which individual has the most potential to become a loyal customer, and when a customer is likely to purchase again from the particular brand. The best predictive analytics solution can help retailers identify customers who are likely to leave and also predict practical remedial actions.
Optimized and flexible pricing
Predictive analytics is now widely being used as a crucial part of an optimized pricing strategy where products are priced differently as per channel, location, or time of the year. The best predictive analytics tools allow retailers to develop highly accurate predictive models for studying competitors’ prices, historical pricing patterns, customer demand, and inventory levels to ensure that fair prices are charged in each situation.
Improved inventory management
Retailers are applying predictive analytics solutions to improve inventory and store management by understanding customer demand. Using such programs, a retailer can highlight areas of high demand, quickly identify sales trends, and, thus, optimize delivery so that the right inventory is transferred to the right location.
The best predictive analytics software is efficient enough to give an idea of the present and future based on past information. The access to Big Data allows these predictive analytics models to use past data and predict future events helping retailers increase their sales and revenue.