Customer Sentiment Analytics

Sentiment analysis is analyzing the customer’s inclination, emotions, and feelings towards a product, its brand, and personal reviews regarding that. In Sentiment, analysis data is gathered from different social media platforms. This data is interpreted, analyzed, and visualized to get insights out of it. This may help industries to know “What Customer Wants?” This helps …

Supply Chain Transparency

In the present market, comprehending an existing supply chain with all its participants becomes crucial for carrying out smooth operations. By enhancing visibility brands can boost their relations with their customers and focus on building trust and connections while also delivering higher-quality goods and establishing authority. By Helping drive the surge of such transparency Big …

Quality Control

Data analytics can also be used to ensure your products meet certain quality control standards. If you’re manufacturing food products, the packaging and ingredients directly affect product quality. By analyzing and monitoring all the components along your supply chain, scanning the quality of incoming materials, you can use this data to identify different ways to …

Food Shelf Life

Data science and analytics help in predicting the shelf life of the food products like bakery products, wine, etc by using predictive analysis. This may help them to save food products before it gets wasted. Through effective big data governance organization techniques, one can sort through data that relates to the ingredients you carry on …

Deliveries

By using data analytics to collect information and data governance to ensure the information is organized and easily accessible, you can better understand how your business is performing in the food delivery sector. By implementing data analytic systems and processes, you can easily monitor and track orders to accurately provide estimated delivery times to customers. …

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