The changing lifestyle of our daily lives is associated with many aspects. Many in the business sector, particularly in retail, had to overcome numerous obstacles such as the global economic slowdown, changes in the social environment and consumer behavior, or an epidemic such as COVID-19. Many enterprises face an existential threat affecting their business revenue and profit. However, using only human labor to run a business, whether collecting, managing, or analyzing large amounts of data, results in many errors or high chances of inaccuracy, which can lead to an enormous loss of income. Retail businesses therefore need to consider solutions to product management problems and poor marketing strategies in order to increase sales as well as improve financial management. This way, retail businesses are forced to leverage intelligent technologies such as AI and data to enhance their business agility in order to strengthen their business opportunities over competitors.
Currently, many retail business leaders stay ahead of their competition by utilizing the benefits of AI and data to help transform different functions of their business, including Marketing Management - the use of Machine Learning with Data Analytics to analyze customers’ shopping behavior and interests to further plan for promotions that suit each group of customers for certain product categories. The marketing process includes Customer Segmentation, to sell products and offer the right promotions to meet different customer groups. After that, the Promotion Effectiveness will be measured to help evaluate the efficiency of marketing to meet the needs of each customer group as well as develop new ideas for the upcoming promotions. Customer Lifetime Value, on the other hand, is a method of estimating a customer's profitability and the business's potential for long-term growth in order to retain existing customers and build a new customer base by using past spending values of customers to identify patterns and trends in changing spending values. method of detecting if customers are likely to leave the product as well as finding new and effective strategies to attract them is called Churn Prediction. Lastly, AI and data can optimize Product Recommendation to help customers choose the products they like and the products they look for, increasing the chance of purchase and creating a better personalized shopping experience for them.
Store Management - using the analysis of each product's history data together with current product trends as well as other external factors for the operators to perform better product management. The method includes Demand Forecasting, to increase the accuracy in making future estimations to prepare appropriate products in stock, in relation to customer demand over a specific period. Assortment Optimization, to help select a set of products to offer to a specific group of customers according to their preferences to maximize the revenue. Lastly, AI and data can help with Store Replenishment, which has become the essential aspect of inventory management. The system will help calculate and recommend the appropriate order quantity to ensure that the right number of products are being reordered to meet customer demand in order to reduce the opportunity loss from products that are out of stock and overstocked at the same time.
Geospatial Prediction - the use of data science that contains location data and other external data such as data from local surveys, navigation systems, sensors, as well as economic, social and population data in the area to develop Location-Based Marketing, which allows operators to target consumers at a granular level with online or offline messaging based on their physical location. It can also help find what we call New Store Opening AI, to know the suitable locations to open stores or new branches so that the operators are able to reach the potential customers to generate sustainable sales and profits in the long run.
It is clearly seen that the outstanding roles and capabilities of AI and data have driven and optimized the management in various aspects of the retail business to be more efficient and reliable. It obviously helps reduce unnecessary human labor and significantly increases the accuracy of data analysis with measurable results. Having AI and data to transform business is not just an option anymore; it is revolutionizing the way to make your retail business survive in the fast-changing world full of competition today.
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