big data in retail and eCommerce syntelli solutions inc
An increasing number of enterprises, especially retail and e-commerce businesses are tapping into the potential of big data to win big using predictive analytics. Predictive analytics is the process of extracting information from big data to predict trends and behavioral patterns. It includes a variety of statistical techniques from machine learning, predictive modeling, and data mining, which analyze current and historical facts to make predictions about future and unknown events. Predictive analytics can be applied to any type of unknown entity to predict likely trends, such as identifying suspects after a crime or to detecting credit card fraud as it occurs.

The core of predictive analytics relies on capturing relationships between explanatory variables and predicted variables from past occurrences and using them to predict the future outcome. However, the accuracy and usability of results depends on the level of data analysis and quality of assumptions. Businesses are increasingly using predictive analytics to gather all information, gain tangible new insights and determine the next best actions for their businesses to stay ahead of the competition. Data scientists are hired by companies to not only acquire data from multiple sources to accurately trained the models, but also identify business outcomes using predictive analytics.

Businesses use predictive analytics in the following ways:

Personalization – Businesses use predictive analytics to provide their sales associates with information about customers’ past purchases along with the buying habits which thereby allows them to make product recommendations to customers. Using analytics businesses can also foresee customers’ next purchase actions and can make product recommendations based on their behavior and preferences.

Inventory optimization – Manufacturers and retailers are finding it difficult to effectively manage their inventory, as the globalization of businesses has made supply chain much more complex. Thus, inventory optimization has become the need of the hour, to get rid of the ambiguity on distributing the right inventory, in the right quantity to the right locations at the right time. Predictive analytics powered by cutting-edge technologies helps companies identify trends and patterns in inventory use. It anticipates the optimal inventory level that help organizations in minimizing overstocking costs and also ensures that out-of-stock situation never occurs.

Pricing – Businesses use predictive analytics to set optimal prices after taking all possible factors into account, which would be difficult to achieve without data science and machine learning. Apart from considering competitors’ pricing strategies, a predictive pricing model also takes into account real time sales data and weather information to optimize product’s price for a particular time. Predictive analytics solutions also allows businesses to determine the best time to drop product prices in order to enjoy maximum profits.

Predictive Search – Businesses use predictive analytics to provide a user-friendly shopping experience to customers based on their history, behavior, and preferences. Customers need to type just a few letters and their desired search results are listed, as it can predict what a customer is looking for.

As businesses strive towards maximum customer satisfaction and loyalty, predictive analytics serves as an important tool to aid the process.

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