Applications of Artificial Intelligence in the FMCG industry

Janifha Evangeline | Thursday, 17 February 2022, 06:23 IST

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While Artificial Intelligence - a burgeoning branch of computer science that is concerned with automating tasks that would require human intervention, the simulation of human intelligence in machines enables in eliminating the requirement for humans to perform monotonous tasks, thereby letting them focus on the more relevant tasks. AI also facilitates future analysis as well as predictions that would have otherwise been arduous or inaccurate when done by humans.

“The FMCG (Fast Moving Consumer Goods) industry is a diverse and a very competitive market. Companies are continually looking to improve efficiency and reduce manufacturing costs. Technology is one of the acting forces in reducing production costs, becoming a necessary business enabler. FMCG industries aim to leverage new technologies to track the expansion of products, manufacturing locations, shipment warehouses and to analyze customer preferences and experiences,” says B Ganesh Shenoy, CFO, MTR Foods Pvt Ltd.

Applications

Sales Forecasting: businesses get ideas about the sales that are going to occur in the coming days by predicting customer purchases since the production can be planned well in advance. Furthermore, accurate sales forecasts facilitate in taking informed business decisions & predict short-term as well as long-term performance. And in case of any negative predictions, preventive measures can be taken.

Customer behavior analysis: The observation of various factors such as customer buying patterns, preferred locations, preferred choices, tastes and trends in the market, least liked products, purchasing habits, etc. will enable in making the needed modifications to not only get new customers but also keep the existing ones satisfied, without losing them to competitors.

Consumer’s Sentiment Analysis & Decision-making: with the help of the customer’s sentiment analysis & decision-making solution, the customers’ emotions can be taken from the internet for finding out how customers feel about a particular product, brand, or service. This insight can be gained and utilized in a way that helps businesses to respond effectively to their clients, which would help in improving customer experience as well as engagement.

Demand Sensing & Raw Material Consumption prediction: by leveraging and implementing deep learning frameworks, users cannot only predict the new and upcoming demand but also predict what raw materials will be needed in a certain period of time in order to prevent shortage/wastage of supplies. Artificial Intelligence can interpret a large amount of data that is relevant and can also render relevant insights and this will facilitate inventory planning.

Automated Targeted Marketing: rather than marketing to every nook & corner, why not market to customers who may actually purchase your product? Therefore, it is important to making the marketing system highly intelligent with Artificial Intelligence.

Logistics Management: AI lets retailers as well as customers place orders easily and directly from the enterprise and then track their packages. This helps in removing the requirement for a middle man. It also lets raw materials orders be placed with the vendors automatically when scarcity is being sensed, which helps in avoiding the need for keeping a tab on every raw material which would need replenishing. Predicting demand, rerouting in-transit goods as well as modifying orders through implementing AI will help in lowering transportation costs.

Recommendation Systems: understanding the buying patterns of customers as well as preferences to suggesting similar items which will help in cross-selling & up-selling, which may also be based on what the clients purchase from competitors and the correct items will be provided utilizing different types of filtering.

Churn Prediction: one of the ways to find if the customer would be discontinuing their subscription with brands is through the data and feedback they receive from the customers. Churn prediction, therefore, helps the industry to gain a superior understanding of the anticipated revenue. Moreover, the ability to forecast the potential churn rate of any particular customer helps in targeting that individual more wisely.

Conclusion

“Several FMCG industries are utilizing technological services as they are acquainted with the fact that consumers are evolving with technology and they need to keep pace with them. Certain FMCG companies have resorted to innovative packaging solutions to minimize the operational cost and to create a direct impact on consumer perception of products. Innovations in automated production, logistics, and capacity management are amplifying cost-cutting mechanisms. FMCG industries have realized that technology plays an important and game-changing role that can stimulate revenue growth,” states B Ganesh Shenoy.

What is crucial for the success of FMCG enterprises in the present digital economy is personalized experience coupled with customer engagement. Furthermore, Nimble and optimized operations along with insights included at every decision point are more important at the back end. Therefore, all of these can only be accomplished with the implementation of digital technologies such as Artificial Intelligence.

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