1. In-store Revenue
Food and beverage industry analytics can be used to drive revenue of physical stores. Based on history, notifications can let users know when items they purchased are running out and need to be stocked up.
Additionally, when in the store, the GPS function will enable pop-up messages relevant to their previous purchase. For instance, a customer, when standing in a cereal aisle, can receive a text for the cereal they previously purchased last month at the same store.
2. Food Deliveries
Food and beverage data analytics help companies deliver on-time. This is done using data collected on road traffic, weather, and directions. These upon evaluation are used to create a precise estimate of the order’s times. Data analytics helps deliver perishable food items while fresh and eliminates transport of stale products.
Must Read: Food Trend Predictions 2022
3. Insight-based Marketing
Food and beverage data analytics show that personalized marketing is the best way to harness new opportunities. With actionable insights and consumer feedback businesses can better understand market dynamics, evolving customer needs, and the best strategies to meet them.
Offering combo deals, value-added options is a great way to attract and retain customers.
4. Understanding Customer Expectations
Customers have access to several platforms where they are exposed to a wide variety of ideas, images, and campaigns. Their feelings toward a certain dish or new campaign is often evident on social media. The information and knowledge accumulated through this offers a nuanced insight into customers’ reactions and emotions toward specific products.
Access to food and beverage data analytics is highly sought after. It is a critical factor in product development and is often deployed by food giants.
5. End-to-End Visibility
With direct influence on human health, the food and beverage industry needs end-to-end transparency in their supply chain. Food contamination is a significant obstacle. Additionally, product life span decreases during logistics.
Transparency is maintained by predicting storage conditions, environmental demographics, contamination, weather, shelf-life, etc. These predictive models are based on food and beverage data analytics. Additionally, they assist in inventory management by alerting owners whenever there is a shortage.
Also Read: Food Trend Predictions 2021
How Can Big Data Analytics Improve the F&B Industry’s Bottom-line?
Data analytics in the food and beverage industry helps brands and restaurants recognize recurring patterns and forecast ongoing trends. During the initial days of the lockdown, for instance, restaurant sales were at an all-time low.
Eating and dining habits of consumers changed significantly during this time. Data analytics estimates consumption trends and mitigates potential risk in over or under stocking. Data analytics for inventory management plays a significant role in reducing loss and improves the bottom-line.
Personalize the Experience
Integrating a table management system with a POS software offers visibility onto several data points. Restaurants can tailor the guest experience based on previous experiences that offer a comprehensive food insight into their preferences.
Access to this information allows the staff to understand customer preferences and make suggestions based on past behavior.
Additionally, this degree of personalization allows restaurants to send out targeted messaging based on spending habits or preferred items. For instance, if a customer regularly orders Pad Thai, the restaurant could send them targeted marketing messages about their next Pad Thai night. This goes a long way in building loyalty and customer retention.
Whether restaurants or physical stores, consumers expect uniform quality and taste. The flavor of the dish is contingent on the proportion of ingredients used and quality of fresh produce.
Changes in quality is analyzed through data analytics which further estimates the impact on food taste and quality. These insights are crucial for identifying problem areas and developing ways to counter them.
Enhance the Menu
Food and beverage data analytics help ascertain how well various items on the menu perform. Customer preferences and the bills generated will help determine the items that have been most preferred or least ordered.
This helps review overall sales and why a particular dish isn’t getting many orders. Based on insights gained from data analytics, the root cause can be understood. This will help in choosing new items to add to the menu or eliminate dishes that are not doing well.
Similarly, this will also help understand why certain bestsellers are your bestsellers, who ordered what and how much, and other front-of-house insights. This will play a central role in deciding the type of items to be highlighted in the marketing campaign.
Data analytics in the food and beverage industry covers every aspect and works to ensure brands tick all the right boxes. Analyzing consumer behavior, leveraging predictive analytics to historic shopping data helps brands meet evolving customer expectations and needs.
This helps brands reduce the average waiting time, manage inventory stock, and keep abreast of developing food trends.