Big data has revolutionized business all around the world. Food and beverages industry, in particular, can largely benefit from big data. Be it, manufacturers, retailers or restaurants chains all of them can leverage big data analytics for their business. The applications of big data in food industry are so extensive that from production to customer service everything can be optimized. If you are even a little skeptic about the potential of big data then the power of IBM computing is just the story you should know about.
On-time Delivery: Big data can collect data from various sources like road traffic, weather, temperature, route etc and provide a proper estimate for the time taken to deliver goods.
Operational Efficiency: From analyzing the impact of market trends on stock consumption to the effect temperature has on food quality, big data can help food manufacturers and retailers ensure they always deliver the best quality possible.
Sentiment Analysis: Using techniques like natural language processing, data analysis tools go through the text and categorize it into positive, negative or neutral. This technique of big data analysis can be used by food companies to analyze their customer emotions on a scale.
Better Quality: Data analysis can also analyze the impact of factors like storage and transportation on quality of packaged foods.
Personalization: This involves essential analysis of customer views like — what they like, how much they are willing to pay, what they share on social media, the reviews they make, the stories they resonate with etc.
Market Basket Analysis: This analysis is based on the purchase history of the consumer and the items currently in his cart. Based on the insights from market basket analysis, food retailers and restaurants can create effective combo deals and improve their marketing messages.
Customer Service: Nowadays there are multiple customer touchpoints like outlets, mobile app, website, social media, review sites, etc. All of these collectively impact the customer experience and his level of satisfaction.