With massive transformations in global markets, AI and machine learning have become important assets for companies since they have the power to transform the way companies in the food and beverage industry deliver customer experiences. These technologies offer huge opportunities to companies to revolutionize critical aspects of their business processes. In the food and beverage industry, producers, retailers, and restaurants are rapidly changing their business strategies to incorporate innovative technologies to meet consumer demands, stay ahead of the competition, and provide an enhanced experience. Through the implementation of AI and machine learning technologies, retailers in the food and beverage industry can transform business processes and directly enhance the customer journey. In this article, we have summed up some of the interesting benefits of AI and machine learning that retailers in the food and beverage industry can leverage to improve customer engagement as well as ROI.
Big data analytics has dynamically changed the way businesses are conducted. It largely eliminates decisions based on gut-feeling and intuition by providing extensive data for driving result-oriented decision making. The food and beverage industry is no exception to this revolution due to the vast applications of big data. Big data analytics can transform the food and beverage industry right from the origin of production to the final delivery to consumers.
Food consumption habits have evolved over the years with people preferring takeaways and home delivery over preparing their meals. Big data analytics can highly optimize the food delivery process by gathering data from various sources including weather, road traffic, temperature, and route. By analyzing data across all points, businesses can estimate the correct delivery time for the food along with optimizing routes to get it quicker to the consumer.
The use of analytics in F&B industry seems to have no bounds. Organizations can check not only the impact of market trends on global food demand but also analyze the effect of temperature on food quality. For instance, by using predictive analytics, companies in the food and beverage industry can figure out optimal inventory levels at specific locations by taking market trends and future demands into consideration.
Consumer Behavior Analysis
Retailers can use sophisticated big data analytics tools to monitor the purchase history of the consumers along with items currently in their cart to predict the next item a consumer is likely to purchase. Based on such insights, players in the food and beverage industry can create effective combos to improve their marketing efficiency.
Today, the customers are very sensitive with their food preferences and are more than happy to share positive feedbacks or vent out their disappointments with brands in the social media. Brands and food chains can figure out customer preferences and their emotions towards the brand by using complex big data tools such as natural language processing, social media listening, and other data analysis tools. This way, food chains and retailers can take quick action to resolve customer dissatisfaction and prevent the damage by controlling the spread of negative word.
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Over the past few years, players operating in the food and beverage industry have started increasing their focus on innovation to move towards a more consumer-centric environment owing to the rising health awareness among the populace. Additionally, organizations across the food and beverage industry have started moving towards advanced digital assets to offer better-personalized products and a superior customer relationship experience. Consequently, to stay on par with the developments in the food and beverage industry space, key stakeholders are utilizing digital analytics solutions. Moreover, with the help of robust digital analytics solutions, players operating in the food and beverage industry can determine and forecast the needs, preferences, and expectations of the target customers; thereby, increasing the market growth potential and improving ROI.
With years of expertise in offering a plethora of digital analytics solutions, Quantzig helps clients use data to make better-informed business decisions. Additionally, clients can also leverage the use of digital analytics to manage their marketing efforts, digital supply chain, and IP rights.
A global food and beverage industry client with offices spread across geographies was facing predicaments in measuring their marketing performance and gaining insights into the areas of improvements. Additionally, the client also wanted to gauge information on the sales team’s activities to gain a deeper understanding of the past performance and current performances. Furthermore, the food and beverage client wanted to improve their transparency and digital presence in the industry space.
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Digital Analytics Solution Benefits
This robust digital analytics solution helped the food and beverage industry client transform their existing media delivery platforms to provide more personalized products to the audiences. Additionally, the client was able to complement the data, efficiently optimize marketing, and manage the sales force; thereby, estimating the payback between online and offline channels. Furthermore, the client was able to track and measure online campaigns at a granular level.
Digital Analytics Solution Predictive Insights:
- Determine the impact of media on sales and distribution
- Track and monitor sales performance and improve the decision-making process
- Refine marketing campaigns promptly and track performance-related metrics
- Increase brand awareness of the food and beverage industry client
- Increase the ROI by 50%
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The interconnectedness of various devices and sensors is opening up a huge potential in the food safety market. These networks of sensors can collect data from factories, vehicles, home, hospitals, shops and supply chains across the world. Consequently, businesses are getting aboard on the trend of using IoT and big data to improve operational efficiency and food safety. They are now able to get access and notification to real-time data relating to storage conditions, temperature, and hygiene of food products.
IoT and big data are helping players in the food safety market to enhance traceability from farm to fork through a series of interconnected devices and centralized networks. Here are some evidence of IoT and big data revolutionizing the food safety market landscape:
Companies have evolved from using barcodes and RFID manually to incorporating it within the IoT. This interconnectivity facilitates the food traceability from their point of origin to subsequent follow-up destinations across each level of supply chain till the grocery store. Companies are using advanced sensors to track and identify food dust particles, temperature, humidity, and contamination across the distribution channel. This enables them to determine where the contamination took place and take actions to mitigate the situation.
Food Safety Efficiency
IoT is considered a breakthrough in the food safety market with its ability to closely monitor food safety data points such as temperature and humidity. These sensors can automatically send out alerts to a central network notifying the user to take action. The technological advancement has progressed to such levels that with the help of big data it is possible to analyze the genome of bacteria within the food and detect anomalies in food samples with harmful bacteria.
Food Safety Through Multiple Data Sources
Big data takes the food safety game to the next level by gathering data across other verticals apart from just temperature and humidity. For instance, regulatory inspection programs are taking advantage of publicly available information such as food inspection reports, 311 service data, community and crime information, and weather data to run predictive models to identify restaurants that are likely to breach food safety regulations.
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Running a grocery store can be challenging. There are numerous products to manage, many of which spoil quickly, often resulting in a significant amount of waste. With the profit margin for grocery retailers typically ranging between 1% and 2%, careful planning and strong marketing are essential. There are many ways big data can help facilitate this, and strategic use of food and beverage analytics solutions can make a significant difference to profitability.
Uses of Big Data in the Food and Beverage Industry
Though often criticized for its nutritional value, fast food is here to stay. The increasing prevalence of fast food restaurants is offering a greater number of people with affordable and varied meal options, as well as treats, beverages, baked goods, and more. The fast-paced nature of service and sizeable menus of these restaurants require them to run smoothly and efficiently in order to keep customers happy and profits rolling in, a task that can seem difficult to anyone who has been in a crowded fast food restaurant trying to get a chicken nugget meal at 2 AM. Luckily, big data and food and beverage data analysis is here to save the day. Using data analytics, every French fry, late-night chicken nugget, and ice cream sundae sold generates data for fast food chains to analyze and act on, improving quality across the board. Here are a few ways that the fast food industry can use data and analytics to change their business practices and make business decisions:
- Test new products: Fast food chains can use data analytics to evaluate the financial impact and popularity of new products—including food items and in-restaurant technologies—before they implement them. Using food and beverage analytics to look at how customers interact with drive-through menus, for example, can give chains insights as to how they will react to certain technologies and changes. They can also utilize publicly-available data for further knowledge of customer preferences and habits. Additionally, chains can conduct surveys that will allow customers to give them direct feedback about how they would respond to a new product or in-store attraction or service.
- Improve operations: As more and more fast food restaurants begin to offer delivery, they can use analytics to increase the speed and quality of service. They can also derive insights from the data collected from delivery orders, and get a better picture of where their customers live and what they are willing to spend money on having delivered. Analytics and big data can also improve in-store operations—for example, chains could analyze data on wait times to improve service and decrease the amount of time customers spend standing in line to order and receive their food, or could use findings from food and beverage data analysis and food and beverage industry predictive analytics to alter staffing schedules in accordance with the busiest days and times an individual restaurant experiences.
- Cater more effectively to customers: Analysis of data about what food products customers prefer can help fast food chains to optimize their menus and increase sales. The use of food and beverage analysis for fast food menus lets chains know what the most popular or most frequently purchased menu items are, as well as which largely unpopular items they can cut to save costs without much outcry from customers. It can also tell them what changes they can make to their menu to expand their customer base—data about the prevalence of food allergies, for example, can help chains decide what ingredients to alter or omit so that a larger number of people can safely access their products.
Though data and food can seem like they’re entirely incompatible—at lunch time most of us are focused on carbs instead of numbers, after all—they get along a lot easier than it may appear. Data analytics can be used to help improve eating habits, dietary health, and the food options that consumers have available to them, and are becoming an essential tool for food and beverage companies to understand what their customers want and need. Here are five key ways that food and beverage companies can use analytics and data to make positive changes to their products and practices:
Analytics in Food and Beverage Industry
1. Streamline profit and revenue management: The use of food and beverage analytics solutions can help companies to understand where the majority of their profits come from, what their pricing strategies should reflect, and how their businesses can perform better. It can also help them to compare their pricing practices to other companies within the same industry, giving them a good idea of where they stand and how they can change to become more competitive.
2. Improve marketing: Food and beverage companies can use data and analytics about what products people are buying from their stores or brands to more effectively market to them. For example, a company that saw that its blueberry muffins were experiencing extreme popularity could entice customers to buy more of them, and more of other products, through deals, coupons, and personalized offers. This also makes email and digital marketing more effective, allowing companies to target customers who have a history of purchasing a particular product. For example, a beverage company could target customers who frequently purchase coffee to advertise a new variety of cappuccino.