The restaurant industry is one of the most competitive industries on the planet. We already mentioned in a previous post on big data examples in real life how the catering industry could benefit from restaurants analytics, so we will today go deeper in the topic.
According to Modern Restaurant Management and the National Restaurant Association, 60,000 new restaurant locations open each year. However, 50,000 restaurant locations close their doors each year! Additionally, according to studies done by The Perry Group and The Restaurant Brokers, 90% of restaurants that are independently owned close within one year of opening. 70% of restaurants who manage to stay open for a year close their doors within the next 3 to 5 years. So, it’s no exaggeration to say that the vast majority of restaurants don’t succeed. If you’re reading this post, you’re probably wondering how you can prevent your restaurant from joining the masses of “almost made it”. There’s no easy answer that we can offer. However, we can point to our strength here at datapine: data science.
Managing their information with a data analysis software, restaurants can sharpen their competitive edge, increase revenue, and increase profit margins – all by looking at the data. Data allows you to get an objective, nitty-gritty view of the daily functions of your restaurant. Do we have you hooked so far?
But I Know My Business So Well…
At this point, you might be thinking, “Well, data is all well and good, but I’ve worked in the restaurant industry for a long time. I trust my gut – and I don’t think data is going to be more knowledgeable than me”. Let’s investigate that further.
Let’s assume that you’ve been in the restaurant industry for decades. Maybe you’ve worked your way all the way up from a dishwasher to the owner or manager position. Or maybe your family has had a restaurant for as long as you can remember and you’ve been involved since you were young. Either way, you’ve developed a finely tuned sense of “what works” in your restaurant and geographical location and what doesn’t. You’ve tried specials, tried promotions, and switched the menu around.
You feel just you’ve done just about everything. After all of these experiments, you know what your customers like, dislike, and what they might be interested in the future. Nobody is disputing that. Data can’t run a restaurant for you, and data can’t replace in-the-trenches experience. Data also can’t replace your creativity, your style, and your passion for your business.
Here’s the thing: data isn’t meant to “replace” anything. Instead, restaurant analytics are an addition to your already capable business intelligence. And let’s be honest for a moment: it’s possible that some of your intuitions aren’t perfect. Let’s say you feel that you know:
- What types of dishes your customers like best
- Which servers are bringing in the biggest orders consistently
- What new promotions are likely to sell
You know these things based on past experience, and so you developed beliefs for each of these areas. The problem is our modern world is changing at an accelerating rate. Your beliefs and intuitions can quickly become inaccurate.
Data can serve as a way to “check yourself” and get to the bottom of what truly makes your business tick. As data science guru Peter Chen wrote in an article, “analytics can’t come up with ideas, but it can help you improve on good ones, avoid trying bad ones, and uncover flaws that can be fixed”.
A Case Study In Cooking Up Profits
Let’s illustrate some of these principles at work in a case study. Dickey’s Barbeque Pit is a U.S. based, family run restaurant chain with over 500 locations. One day, CEO Roland Dickey pitched an idea to his wife (and CIO) Laura: “Barbecues and Big Data – let’s make this work!”. More than just big data, the couple wanted real-time, actionable insights.
After getting their restaurant analytics system into place, they started to collect “priceless” information, such as:
Demographic data. Thanks to analytics, Dickey’s now knows that their average lunch guest is a 43 year old man who drives an SUV to work. They even know that this customer’s average commute time is 30 minutes. As a result, Dickey’s is now specifically targeting Ford owners who live 15 to 30 minutes away from a Dickey’s location in their advertising.
Behavioral data. Dickey’s learned that women with kids often go to a location on a Wednesday, and enjoy a long lunch late in the afternoon. Because of this data, Dickey’s now advertises “Craft Wednesdays” on Pintrest as a draw in for mothers and their children.
Shared customer interests. Dickey’s found that their customers love fantasy football and dogs. As a result, they started to advertise on fantasy football sites and dog lover sites, as well as T.V. channels like Animal Planet. They even use dogs in their catering photos as a brand move.
Finally, as a result of the real-time nature of their restaurant analytics platform, Dickey’s managers and franchise owners can do nifty tactical moves related to daily sales trends. Combining your knowledge with various sales KPIs, you can optimize your operations. For example, you can do local sales for items that are building up in inventory, or do local sales if there was less business in a certain location than expected. By this point, we hope we’ve convinced you to give restaurant data analytics a try.
So now, let’s go over some ways in which you can use these restaurant analytics once you have them.
4 Ways Restaurants Analytics Can Help Your Business
1) Increasing order sizes with drinks
If you’re designing a new drink menu, you can look at your restaurant analytics to see what drinks people tend to order with certain items on your menu.
Then, you can increase these sales by suggesting these already popular wine or drink pairings with meals both on the menu, and through your wait staff.
2) Getting more repeat business with menu analytics
You can use restaurant analytics to identify which items on your menu are studs, and which ones are duds. This works best in conjunction with a customer loyalty program so that you can track individual customers’ patterns over time.
For example, let’s say you run the data for a few months of purchases. You’ll be able to divide your menu items into 4 categories:
1. Your all time greats. These items are ordered a lot, and people tend to reorder them
Definitely don’t mess with these – if anything, consider doing more advertising mentioning these dishes or feature them in some other way. Additionally, if you’re looking to add new items to your menu, your “all time greats” should be the first place you look for inspiration. If all your “greats” are steak dishes, it’s possible that new vegetarian dish won’t pan out so well.
2. Your “one hit wonders.” These items are ordered a lot, but people don’t tend to reorder them.
You’ll want to investigate these further. Are people not re-ordering because the dish is bad? Or did they just want to try a “different” dish to see what it would be like? If it’s for the first reason, you can re-work the dish to be better or get rid of it altogether. However, if people just wanted to try a “different dish” – this is also a useful thing to know. Apparently, this item is tantalizing! Examine the item’s name and menu description for clues that you can apply to the rest of your menu.
3. Your “hidden gems.” People don’t tend to order these dishes that much, but once someone tries it once, they’re hooked.
This is a great case for analytics because you can run promotions and discounts to get people to try these dishes. Once they try them, your work is done. This category could also possibly benefit from better menu names and descriptions to make them more appealing to people who haven’t tried them before.
Additionally, these are great dishes for your wait staff to highlight, giving them a chance to show off their knowledge. After all, many people love the idea of a “hidden gem” that is delicious but not well known.
4. Your laggards. These dishes aren’t ordered often. When they are ordered, people don’t order them again.
You should either rework these dishes or get them off your menu because they’re giving your restaurant a bad name. It’s much better to have a “tight” delicious menu with fewer selections than it is to have a sprawling menu with some so-so items on it.
As a final note here, you should train your staff to give recommendations from the “All Time Greats” and “Hidden Gems” category whenever a customer asks for a recommendation. These dishes have the best chance of making a good impression (and getting repeat business).
3) You can (objectively) see who your star performers are
Let’s say you rely on your manager’s opinion when it comes to hiring and firing staff members. This probably works fine – but your manager might have their own biases that color and distort their perceptions of what wait staff is performing at a high level.
If you have restaurant data analytics related to employees’ average order size, for example, you can have a much clearer idea of who’s “bringing home the bacon”.
4) You can see (and anticipate) trends
Once you’ve been using your restaurant analytics for a while, you’ll be able to know things like:
- What your busiest times of day are
- What your busiest days are
- What holiday business is like
And this is when data visualization tools join the party to give you a helpful hand in order to arrange your various indicators and measures into compelling business dashboards. Thanks to these insights, you can plan your staffing needs better and make sure you’re not over or undermanned for any given shifts. In order to make the most out of this data, you will need to visualize it to comprehend it better.
Restaurant analytics are a valuable tool in the restaurateurs’ arsenal. They give you an added edge that helps you to understand your customers and your business even better than you already do. In today’s cutthroat restaurant industry, you need every advantage you can get. Start out now with a 14-day free trial and gain insights from your restaurant data analytics!