Big data and analytics have helped out a number of companies and industries. The ability to gather massive amounts of information and turn that into actionable insight is invaluable to companies trying to cut costs and make more money. The food and beverage industry is a great example of how this works.
Retailers, restaurants and consumer brands have the ability to drill information down to specific products in order to gain insight. In an example outlined at SmartBrief, that includes beverages:
For example, many beverage companies connect geographical data and purchasing trends to individual stores, while others collect data on influencers and use that data to engage with them in the form of multichannel campaigns and promotions, Chakrabarti said. In addition, loyalty card companies, which collect a significant amount of shopper data anyway, are making their data available to other types of beverage businesses to help empower their decision making and share consumer insights, he said. Data has also become a powerful tool for optimizing assortments, streamlining supply chains, analyzing trends that appear on social media and planning and executing brand campaigns.
By tracking purchasing decisions from the retail level down, companies learn about what and where products are being purchased. Tracking beverages at the item level – sorting by physical purchases and online purchases – allows companies to make decisions about merchandising, assortment and supply chain. The trick is using up-to-date technology and valuable insights in order to make that data work for the company.
Take this tidbit about supply chain analytics, from At Once:
According to David Telford of Qlik, 42% of business professionals have to make data-based decisions within a day. Data analyzes generate a high return on investment in the supply chain, according to Telford. “In the past, the supply chain mainly revolved around making and supplying products. Today it is more about creating a commercial context. He also pointed to a number of so-called supply chain disruptors, such as Uber, drones and 3D printing.
Now consider the following example. A company might learn that customers in the Pacific Northwest are purchasing 15 percent more of a diet beverage than the nationwide average. Further, they may learn that the Midwest is purchasing 15 percent less of the diet beverage. This allows the company to make a handful of decisions – shipping more of the diet product to the Pacific Northwest and less to the Midwest to meet demand up front, manufacturing the diet product in facilities closer to the Pacific Northwest to cut down on shipping costs, and pushing more of the marketing budget for the diet drink to outlets in the Pacific Northwest to capitalize on an already apparent favor to the drink.
Now look at how Red Robin does things. According to SmartBrief:
…software allows its more than 400 locations to collect a variety of sales and operating data and apply that data to the beverage item level, according to Chakrabarti. The company applies data that comes from about 10 different sources, including menus, points of sale, inventory management and daily sales, to analyze the performance of menu items and make any necessary adjustments at the store-level on a weekly basis.
This is the individualization of the retail market. It’s no longer enough to lump consumers into groups. With the advent of big data analytics, and the growing technologies that gather data to be analyzed, retailers are able to consider potential buyers as individuals. Delivering an individualized experience to consumers will increase sales because it allows for the most specific marketing opportunities possible.
For starters, a company needs a cloud architecture that allows the company to collect and analyze data in real time. The company needs to identify key performance indicators that will let them analyze the data correctly to make decisions. Drawing from sales isn’t enough – social media, as an example, can offer insight into what consumers like, and dislike, about your product. Then, growing outward from the product level, analyzing the costs of shipping, manufacturing, and more can help whittle down unnecessary costs. And purchasing an advanced analytics software is a necessity in order to ensure the information you have is correct, so the conclusions you draw are sound.
Big data analytics is very much a fluid thing. It requires a consistent commitment to gathering, analyzing, and learning from data. Your company will need to constantly pivot, in real time, based on what you’re learning on a monthly, weekly, and sometimes daily basis. However, if you can succeed, it can save costs, strengthen processes, and generate more revenue than any business has ever had the ability to do before.
Knowledge is power when it comes to big data analytics. Just ask the food and beverage industry.