Restaurant Data analytics is the process of analyzing every datapoint related to your business and converting them into meaningful insights, which can help improve everything from menus and staff straining to restaurant policies and marketing campaigns.
Big Data and Restaurants Big data basically refers to the large volumes of data that is constantly being generated by the software solutions a restaurant has in place. For many, this begins with how a customer places an order and pays for their food.
Larger restaurants may even have 8 or more technology vendors on their payroll, which highlights the need to invest in a reliable analytics solution. Restaurants that operate on this scale, think McDonalds scale, may be looking at big solutions to understand and make use of the huge amount of data they generate. In contrast, small and independent restaurants shouldn't need to stress over big data, as they’re unlikely to have multiple software vendors on board. In short, they most likely don't generate enough data. For them, it’s better to concentrate on finding usefulness in the data their POS is currently producing. With that said, restaurants of all sizes are generating more data than ever before, which makes data analytics an exciting space to explore.
Likewise, analysis of the data from your CRM can be used to identify why certain items sell well, who ordered what and how much of it, and other front-of-house insights. This can be used to improve your menu, as, if you evaluate what entrees are being ordered in what amounts, you can introduce more of such items on the menu.
Predictive analytics make use of historical data to predict future trends and outcomes. While a handy approach for any business, when used for restaurants, this tactic can play an essential role in improving your revenue. Essentially, restaurant owners can use predictive analytics to:
Improve order accuracy: Modern predictive analytics solutions can directly connect to your restaurant ordering system to increase order accuracy. Most of them can predict what food items will be requested during specific hours of the day. This also helps you stock up on supplies to fulfill customers’ demands.
Forecast trends: Restaurant predictive analytics can also be used to forecast future trends and revenue. By comparing historical data with your current numbers, you’ll be able to predict where your restaurant will be in the next couple of years. Consequently, you can devise strategies and take steps to help your business achieve its goals.
Minimize food waste: When planning the menu, it is imperative that a restaurant owner knows what quantities of ingredients are needed to prepare a meal best. By using predictive analytics, you’ll be able to drill down into past and present inventory levels. This helps you to reduce food wastes by ordering the required quantity as and when needed and control your food cost efficiently.