The highly dynamic nature of the retail industry has urged retailers to rely on various fourth generation technologies to tackle market competition successfully. For instance, artificial intelligence, big data and machine learning have enabled retailers to incorporate optimal strategies as the industry evolves digitally. Over the years, business has shifted its focus to introduce customer-centric strategies to improve market worth and customer loyalty rates. Companies have introduced policies to attract potential customers as well as satisfy and retain current ones.
Businesses have shifted their focus on predictive analytics to solve issues and achieve optimal results. Also, predictive analytics have enabled an efficient utilization of resources and the effective generation of strategies to forecast business outcomes. In addition, the analytics help in setting key performance indicators and predicting sales as well as customer practices for corporate success in the retail industry.
A concept that has recently been gaining popularity in the field of big data analytics and machine learning is Social Physics. The Social Physics concept is a revolutionary advancement in the field retail as it is continually tracking customer behavior to boost innovative business practices. In addition, the concept assists in predicting behavioral trends to generate smarter retail strategies. Social Physics collects data on human behavior from sources such as web activity, social media accounts, call center queries and in-store preferences. According to market research, firms using Social Physics are predicted to witness an increase in the return on investments by around 30 percent.
According to recent studies, Social Physics plays a crucial role in empowering employees to work together and achieve tasks with ease. In addition, the concept helps in eliminating wastage of resources and repetition of tasks. Educating employees about customer behavior and potential market trends will assist in quicker completion of sales and produce better outcomes. Social Physics also helps businesses to improve communication and thus, improving employee retention rates.
In comparison to traditional customer data collection methods, Social Physics is predicted to improve current machine learning technologies to collect and handle vast amounts of data on customer behavior. In addition, Social Physics enables retailers to solve challenges regarding predictive analytics as it promotes quick decision making and simplifies the process of incorporating data to meet current business models. Social Physics requires very little data to respond to any queries regarding customer behavior and thus, it is a valuable advancement in accurately forecasting and creating sustainable business ideas. Also, Social Physics assists in reducing business risks.
Data analytics and machine learning capabilities are crucial to attaining optimal predictive analytics. But the inclusion of Social Physics has improved the overall opportunity to enhance the analytics. Businesses can now easily understand and apply strategies to meet the consumer’s preferences as well as optimally use resources to increase business profits.
Rajiv Prasad is the chief information officer at Xpandretail, which is powered by Sávant Data System.