The grocery retail industry might be one of the most famous industries in Lebanon. Due to its ability to deal with economic uncertainties on the national level. This sector in Lebanon is in a relatively good shape in comparison with other industries that severely suffered from the economic crisis. However, the Lebanese grocery retail industry might still have a lot to learn when it comes to AI, and data science. This article discusses 5 points on how AI and data science could impact grocery stores.
Forecasting sales and improving supply chain management
Forecasting sales is essential for all grocery stores. Indeed, knowing how much each item is expected to sell over a period of time, can help the grocery store plan on how much supplies it needs and what is the accurate pricing strategy to use. However, the most important aspect of the sales forecast remains the fact that the business will be able to avoid shortages or excess supply by simply optimizing the quantity of inventory ordered. This is extremely important for products with an expiry date, or highly perishable products such as fruits and vegetables.
Optimize number of staff for shelves replenishment
Having too many staff is an issue for any business. However, in the case of a grocery retail store, having not enough staff to replenish shelves, will make the business experience shortages on many items as the shelves will be empty for a period of time and potential customers for this product will be counted as lost sales. Therefore, data science can be used to monitor the shelves and the availability of each product on the shelves. And then collect data on how frequently the shelves are empty in order to determine a suitable number of employees for shelves replenishment.
Improve sales by getting to know the customer
An important contribution of AI is clustering of customers into different segments. This is very important to determine the best marketing strategy to use, best pricing strategy to use, and shelves allocation strategy.
Assess the performance of each cashier staff
Similarly, based on some data collection, the business management can compute the average time a customer spends waiting in line before checking out at the cashier. This helps assess the level of customer satisfaction, but most importantly it helps determine the best performing cashiers.
Boost loyalty programs
Data science can be used to identify top customers, and what
they regularly buy. This can be used to adjust the loyalty program by
customizing it to customers. This means that each customer will get the
suitable gifts (Free products) based on what he or she buys the most
frequently.
Please note that the ideas mentioned above are just a few
examples on what data science can potentially provide to grocery stores. Many
more achievements might be made possible by using data science.
No-Responsibility Disclaimer: This blog provides general information related to Data Science and its applications in Businesses. The content provided in this blog and any linked material is NOT an advice, and NOT a recommendation. And the author is NOT liable for any problem or unexpected results that might result from the information provided in this blog post. Similarly, the author is NOT responsible for any wrong information mentioned in this blog post.
