The data revolution is here. With a never-ending focus on improving customer and patron experience, more restaurants are turning to large, quantitative data sets to help ‘steer the ship.’ In one particularly noteworthy example, McDonald’s recently purchased data and tech firm Dynamic Yield to tap into the well of big data. McDonald’s will use the technology and capabilities supplied by Dynamic Yield to create personalized experiences for their customers. For example, the drive-thru menus will more prominently display coffee on colder days and McFlurries in the summertime. This type of data-driven innovation is the core of a new movement within the Food and Bev industry at-large.
Today, customers are ready to spend more money on food than ever before. In return, these consumers expect much more out of their restaurant and bar experiences. Data is here to make that happen. Moving forward, big data will continue to have a huge impact on our industry -- in can provide us with up-to-date and actionable insights into the spending habits of our customers.
It’s important to note that data isn’t a cure-all or a silver bullet to instantly improve your restaurant’s revenue. But, data can present robust and previously unavailable insights that can prompt valuable business decisions.
Through data, we can identify sales metrics like ‘revenue per server’. This can help restaurants to adapt and make crucial staffing decisions that can directly impact restaurant profitability. ‘Revenue per server’ can help identify any fluctuations in a server’s overall sales, and this will allow you to make adjustments to optimize your operation. It can tell you where you would benefit from additional manpower, and where you can afford to be shorter-staffed.
Data can also analyze what items you sell in abundance, and how that can or should affect your ordering cadence. From this, you can optimize your menu by dropping items that do not perform regularly, and introducing items that are more likely to sell.
Apart from detailed menu evaluation, particularly savvy restaurants and bars are using big data to look at customer profiling, operations improvement, sales forecasting, customer trends, and more. In a business with razor-thin profit margins, any type of insight to improve your credit score should be taken advantage of.
Labor is no small part of the picture when it comes to restaurant finances. And generally speaking, the longer you’re open, the more you’re going to be spending on labor costs. With that in mind, it’s beyond crucial to keep an eye on your labor costs. Data can help identify slower seasons and busier times, allowing you to be staffed appropriately.
These data-driven insights will also help to streamline your overall scheduling process. Specifically, restaurant owners are now able to analyze historical data for traditionally busy times of the year. This allows owners and managers to staff the right combination of temporary, part-time, and full-time labor.
All of this will ensure that labor costs are kept under control, leaving more room for profit at the end of your year.
When speaking of data, the benefits can be seen across the entire ecosystem of a restaurant. This, of course, includes customer experience. Analyzing sets of data can reveal critical information and insight into the spending habits of bar/restaurant guests. Data can reveal order preferences and order history, allowing for restaurants to fine-tune their programs to better suit the ever-changing needs of their customers. When sending out promotional material, restaurants and bars can tailor those items to the preferences of their recipients.
Looking at these big data sets also gives you the chance to identify trends and place customers into groups based on personal preference. This type of customer-focused profiling will allow restaurants to build long-lasting, mutually-beneficial relationships with customers. Overall, the more value you can provide to customers, the more likely it is that they become long-term, returning patrons.
Many restaurants make use of historical information to predict upcoming trends and sales peaks. In an industry that seems to be constantly floating between trends, this is an invaluable strategy to have that effects both customer-facing and operational aspects of a bar or restaurant.
This type of work is generally called ‘predictive analysis’, and can be used for several different applications.
First, restaurant owners can use predictive analysis to eliminate or significantly reduce food waste. When seasons change, waste often surges due to the customer’s increased or decreased demands for certain food or drink items. By looking at previous years’ data, restaurant owners can anticipate how to adjust their ordering cadence, and thus prevent excessive waste. Modern predictive analytics systems can also directly fuel your inventory management strategy year-round, creating an accurate cadence for nightly and weekly product orders. When it comes to ordering, big data means that owners and managers no longer have to rely on guesswork and intuition.
Beyond waste, owners and managers can use predictive analysis to forecast future trends. By comparing the historical data with current sales figures, you can accurately predict the ebbs and flows of your service. As well, data firms also offer comprehensive sets of industry figures which can be used to predict upcoming trends and hot-selling ingredients.
Annual restaurant and bar sales hover around $800 billion today. With such a seemingly-thriving business, it’s easy to wonder why data is relevant. If it ain’t broke, don’t fix it, right? Well, data enables marketers and restaurant owners to get a real-time, fact-driven snapshot of their customer base. By getting this valuable insight into your customers, big data makes it easy to optimize marketing strategy and adjust as you grow.
With data, restaurants can leverage information about customer behavior, weekly routines, and so much more. As patrons spend more, they expect more, and data gives restaurant owners actionable insights to create value for their customers.
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