The food industry is a major sector of the U.S. economy, with an estimated worth of more than $1.5 trillion. The stakes in this industry are incredibly high: Customers expect the food they want when they want it, and that food also needs to be fresh, clean, and high-quality.
An increasing number of businesses in the food industry are solving challenges, improving their operations, and driving customer satisfaction with the help of data analytics, data science, machine learning, and artificial intelligence.
What is Data Analytics?
Data analytics is the ability to leverage an organization’s data to help them gain deeper insights and enhanced decision-making capabilities. It helps organizations be more agile and proactive, ultimately gaining a competitive edge in the market.
6 Uses of Data Analytics & Science in the Food Industry
Some of the best ways to use big data analytics to create impact and realize benefits in the food industry are:
- Predicting shelf life
- Improved customer satisfaction
- Optimized product portfolio
- Reducing waste
- Optimized operations
- Improved marketing personalization
Predicting shelf life
A key aspect of operations in the food industry is accounting for the shelf lives of products.
Data science and data analytics can enable you to pinpoint the shelf life of the ingredients you are using or the food products you are selling, such as bakery products, wine, and dairy products, to ensure maximum levels of accuracy.
Leveraging data analytics in this way ensures your organization only carries and uses fresh ingredients and products, knows exactly when to restock inventory, and has the right amount of stock for your customers’ needs without overbuying, and ultimately wasting, food.
Improved customer satisfaction
Big data can be used to significantly improve the experience and satisfaction of your customers when they dine with or shop with your brand. By analyzing data on customer interactions, sentiments, and feedback, organizations in the food industry can identify opportunities to make improvements.
Natural language processing (NLP) can be used to analyze feedback from sources including social media, complaint forms, comment sections, and customer reviews.
This allows you to pinpoint areas to improve, such as bringing back certain seasonal menu items or adjusting your menu to cater to certain dietary restrictions.
Establishing effective feedback mechanisms and garnering insights from the data enables your organization to continually evolve and optimize your user experience.
Optimized product portfolio
Using NLP to analyze customer feedback from a variety of sources can help you pinpoint the products that are most and least popular among your customers.
You can also analyze extensive historical data to identify which of the food products you sell are most commonly and least commonly ordered or purchased.
This enables your organization to refine and optimize your product portfolio by only offering the food and beverage products your consumers truly want and eliminating the products with low sales and popularity. This, in turn, increases your business’s revenue.
Reducing waste
In the United States, an estimated 30 – 40% of the food supply is wasted. This equates to 54.2 million tons of food waste on an annual basis, a value of $408 billion dollars.
The food service industry accounts for a significant amount of this waste. Waste is an unavoidable aspect of dealing with perishable goods; however, that is not to say that the amount of waste your organization is generating cannot be reduced.
Data analytics can help you identify inefficiencies in your manufacturing or production processes that are causing a significant amount of waste. Tracking your products’ shelf lives and maintaining a database of the information, as we identified above, also helps your organization to reduce waste.
Optimized operations
Applying machine learning (ML) algorithms and predictive analytics enables you to leverage external data – including weather patterns and its impact on both agriculture and transportation – as well as internal sales data to forecast trends and make informed predictions.
This type of trend forecasting enables you to foresee any potential issues with your supply chain and react swiftly.
These insights help organizations in the food industry to strategically plan and make better decisions to continue providing customers with the food products they desire and expect, even during drastic situations like extreme weather impacting shipping.
A historical analysis of this data can also allow you to pinpoint seasonal trends in both your supply chain and consumer buying behavior and adapt your operations and offerings accordingly.
Improved marketing personalization
Today, 73% of customers expect the companies they interact with to understand their unique needs, desires, and expectations.
By collecting and analyzing massive amounts of data, you can gain valuable insights into your customers’ behaviors, preferences, and buying or dining patterns. As a result, you can target your marketing campaigns effectively to deliver the kind of personalized messaging recommendations, and discounts that your customers expect.
For instance, you may learn from your data analysis that your target customer is in their 30s, lives in the city, and is a parent. You may also learn that, due to their busy parenting schedule, the target consumer is more likely to order takeout or food delivery for their family than to dine in a restaurant.
To reach these individuals, you could launch a targeted social media campaign that highlights your business’s quick, convenient, and affordable food delivery that’s perfect for a weeknight dinner with the family.
Identifying your customers’ habits, traits, and preferences is an excellent way to meet your customers where they’re at and launch a successful, personalized marketing campaign.
Leveraging the Full Value of Your Data in the Food Industry
Big data is an incredibly powerful tool for organizations in the food industry looking to optimize their operations, deliver the personalization and products customers expect, and reduce waste.
At AIM Consulting, we leverage proven analytics methodologies, best practices, and tools to define the right analytics solutions for your restaurant or food manufacturing organization’s needs, solving complex business challenges and driving future growth.
Looking to Harness Data to Optimize Food Industry Operations?
When it comes to harnessing data to drive insights and strengthen performance, the possibilities are endless.
Join the many businesses in the food industry that are exploring new ways to leverage big data to improve operations and better serve customers.
