Data and analytics may not seem like a natural fit in the vibrant world of food and hospitality.
Spoiler alert: They are.
From kitchen operations to the customer dining experience, every aspect of a restaurant can be optimised through the intelligent use of data.
How? Let’s find out. In this article, we take a closer look at the ecosystem of restaurant data analytics and unravel how data can be a game-changer in the hospitality sector.
The critical role of data and analytics in restaurant success
The journey of a dish from kitchen to table is laden with data points. From customer preferences to productivity levels, there’s a treasure trove of valuable data waiting to be unpacked.
Here are some of the types of data collected by restaurants:
- Customer data, like food preferences, feedback, and dining history.
- Sales data, such as popular menu items, daily sales, peak dining times, and seasonal trends.
- Operational data, like inventory levels, resource allocation, supplier performance, labour productivity, and staff costs.
- Financial data, such as the cost of goods sold (COGS), overheads, pricing strategies, and profit margins.
Understanding and leveraging this data can dramatically enhance decision-making processes, boost customer satisfaction, and improve your operational efficiency. When all of these benefits come together, you’re in a strong position to improve your entire restaurant operation and increase your profitability.
The positive impact of restaurant data analysis and how it can improve your business
When you understand how to analyse your restaurant data, you can use it to revolutionise your restaurant operations. Let’s look at some of the benefits of data analysis in more detail:
- Optimise inventory management to reduce waste. Tracking ingredients can highlight inefficiencies in your inventory management, such as over-ordering on certain food items. When you spot these inefficiencies, you can optimise your inventory levels to stock ingredients you’ll actually use. This reduces food waste and keeps costs in check.
- Enhance the customer experience through personalised offerings. When you understand what customers want from you, you can personalise the customer experience. This can improve their overall experience with your restaurant and encourage them to buy more when dining with you. It’s a win-win! For example, you can offer discounts on their favourite items to encourage them to spend more, but you’re also improving their dining experience by discounting their favourite item.
🔥Business spotlight 🔥Take a look at Pret a Manger’s loyalty scheme as an example of how data can enhance personalisation to boost profits. Users of their personalised subscription service, Club Pret, have a 30% higher average transaction value than those without a subscription!
- Boost employee morale and engagement. Fostering a data-driven culture within the restaurant team is vital. Training staff to understand and utilise data insights can lead to more engaged employees and improved operational efficiency.
- Optimise staff scheduling based on predicted customer flow. Restaurant data can provide valuable insights into scheduling, ensuring you have enough staff on the oyster to cover busy periods but also preventing overstaffing during quiet times. Nory, for example, can analyse historical data to predict future demand. We can then create optimal schedules to meet customer demand, but prevent overspending on wages.
- Improve marketing strategies with targeted campaigns. When you collect data about your customers, you can create effective and targeted marketing campaigns to boost retention and encourage new customers through the door. You understand more about their behaviour, their preferences, and their demographics — all of which can inform a successful marketing campaign.
Strategies for effective data collection and management
There are various ways to collect and analyse restaurant data, so much so that it can feel pretty overwhelming if you’re new to it. Here are some effective data collection strategies to help you get started on the right foot.
Implement the right technology stack: The backbone of data analysis
The right technology stack is crucial for harnessing the power of data analytics. Why? Because it ensures that you have access to the right data.
And if you can’t analyse the right data, you limit your potential to succeed.
So start by thinking about the data you want to analyse and the results you want. This will help you figure out what type of technology you need.
If you’re not sure where to start, here are some examples of restaurant software to consider in your tech stack:
- Point of sale (POS) systems.
- Customer relationship management (CRM) platforms.
You should also consider integration capabilities in your tech stack. You need software to talk to each other to get an accurate picture of performance, so make sure that your tech can seamlessly integrate.
For example, Nory and Vita Moja integrate to provide restaurant owners with a combined POS and operations management platform. As a result, users can streamline operations and make informed decisions about how to improve their business.
Understand and analyse restaurant data successfully: From collection to insight
Transforming raw data into actionable insights can be pretty overwhelming, but it’s necessary to reap the benefits of restaurant data.
The process typically involves several stages:
- Data cleaning, which involves reviewing and checking all the data for mistakes. For example, typos, missing information, inconsistencies, duplicate information, and so on.
- Data analysis is the most important step, as it involves understanding what the data is telling you. You find patterns, identify trends, and draw conclusions that you can use to make strategic decisions.
- Data visualisation is the process of presenting data in a clear and manageable way. For example, creating charts or graphs that highlight key information in a simple format.
Sound complicated?
Don’t worry. The good news is that centralised data analysis tools can help with this entire process.
Implementing a centralised data management system streamlines the collection process. ensuring data accuracy and accessibility. It also helps you analyse the data, identifying trends and comparable data points that can help you improve your operations.
Platforms like Tableau, Google Analytics, and restaurant-specific solutions like Nory are some examples to consider.
Real-world example of analytics transforming restaurant operations and profitability
Take a look at Clean Kitchen for an example of a real restaurant analytics case study. With Nory’s restaurant management system, Clean Kitchen was able to:
- Track restaurant performance each day (even breaking it down hour-by-hour) to make quick and informed decisions that maximise efficiency. align processes, standardise recipes, and ensure customers get the best food possible.
- Increase visibility and traceability over stock to decrease COGS by 4% and increase gross profits (GP) by 4%.
- Optimise scheduling by forecasting demand to reduce labour costs by 3%.
“We’ve reduced labour costs by 3% since using Nory, mostly from understanding how to calculate NI and pension contributions as part of their budget.” – Adam Jefferies, Head of Operations.
Want to find out more about using Nory’s restaurant data to boost your profits? Book a chat with us to get the ball rolling!
FAQs about restaurant data analysis
How can data analytics help in menu design?
By analysing sales and customer feedback data, restaurants can identify popular dishes, seasonal trends, and areas for improvement, enabling a data-driven approach to menu design.
What role does customer data play in restaurant analytics?
Customer data provides insights into preferences, dining behaviour, and satisfaction levels. These insights can inform targeted marketing strategies, help create personalised service offerings, and show restaurant leaders how to meet customer needs to improve their overall dining experience.
Can analytics improve staff scheduling?
Yes! By analysing historical sales and foot traffic data, restaurants can predict busy periods and schedule staff more efficiently to meet customer demand.
How do analytics impact inventory management?
Analytics enable precise tracking of inventory levels, consumption patterns, and supplier performance, leading to optimised stock levels and reduced waste.
What are the first steps for a restaurant to become data-driven?
Begin by identifying key data points relevant to business objectives, invest in the necessary technology stack for data collection and analysis, and ensure you (and your team) know how to understand and analyse the data effectively.
Why is data analysis crucial for restaurants?
Data analysis is essential for understanding what drives sales and how to enhance the dining experience. Without these insights, restaurant leaders are taking a stab in the dark and hoping for the best.
Simply put, data-driven decisions lead to the best results.
What insights can restaurant analytics provide?
Customer preferences, peak dining times, menu performance, and staff efficiency are a few examples. Analytics can also identify trends in customer feedback, enabling proactive management of the customer experience.
These insights help restaurants tailor their offerings, improve service times, and manage inventory more effectively.
How do analytics companies for restaurants facilitate improvement?
Analytics companies specialise in processing complex data to provide actionable insights. They equip restaurants with tools for real-time monitoring of sales, inventory, and customer engagement. As a result, they can identify opportunities for cost reduction, revenue growth, and operational optimisation.
Can data analytics directly enhance customer satisfaction?
Absolutely. By responding effectively to customer data, restaurants can create a more engaging and satisfying dining experience. Data analytics also helps restaurants personalise the dining experience by creating targeted marketing activity, customised menu recommendations, and improved service quality.
What’s the initial step for a restaurant aiming to utilise analytics?
The first step is to assess current data collection and management practices. Evaluate your existing technology stack, identify data gaps, and determine key performance indicators (KPIs) for the business. Then, choose technology that can provide the necessary tools and expertise to harness the power of data analytics, setting a foundation for data-driven decision-making.
