Getting Started with Restaurant Analytics in 2024

Restaurants have a lot of data, but many don't know how to use it for growth. This guide on restaurant analytics can get you started.
May 21, 2024

Guess what? Four out of five restaurants are swimming in a sea of data. Yet only one has the solid strategy, tools, and processes to analyze this data and foresee trends. So, while others are wading, one is riding the data wave like a pro! If your restaurant is in the “figuring-it-out” camp, it's time to get serious about your data.

Every day, restaurants gather data from various sources: POS, reservation systems, inventory management, employee software, customer feedback, and the supply chain. This data is ubiquitous yet not utilized for various reasons (more on this later).

What follows in this guide are the basics of restaurant analytics, what might be stopping you from utilizing your data, and a few strategies to help you move from just appreciating your data to embracing it for growth.

How data analytics contributes to restaurant growth

Restaurants that use analytics have seen a 5-10% revenue boost, a 15% dip in operating costs, and up to 20% improved EBITDA. These numbers are intriguing, but there are more reasons (most of which directly contribute to these numbers) why your restaurant should invest in analytics.

Optimize operations

Optimizing restaurant operations translates into making everyday tasks smoother, cutting costs, and doing things more efficiently. This includes taking orders, preparing food, managing supplies, coordinating staff, and serving customers more easily. The aim is to run things more smoothly, save time and resources, and give both the staff and customers a better experience.

Data from your POS, CRM, inventory, marketing, and other tools can help you understand your customer preferences, peak hours, popular menu items, and go-to marketing strategies. You can fine-tune things based on insights from these tools. 

For instance, inventory management tools can help you identify which recipes produce the most waste. You can map the recipe's waste to the money it makes and decide if those ingredients could be used better in another recipe or if you should use less of them. 

Right resource utilization 

Optimizing operations is a broader strategy that aims to improve the overall functioning of a business. But when we talk about resource utilization, we're specifically looking at using resources in the best way possible to meet specific business goals. So, optimizing operations is like improving everything, and resource utilization is about using specific things wisely. 

Talking about restaurants, using resources wisely could mean making good use of ingredients, staff, time, and money to increase profits. It's about using these resources in the best way possible to meet customer needs, reduce waste, and improve how the restaurant works.

For instance, you might notice that fresh herbs often go unused, resulting in waste. To address this, you can analyze customer preferences and launch a daily special menu that uses these herbs. This not only prevents waste but also attracts customers seeking unique dishes.

Menu engineering

Data helps restaurants optimize menus with customers' favorite dishes. You can see what dishes are popular and how much money each makes. This also helps simplify the menu by removing unpopular dishes and adding new ones based on emerging food trends and customer feedback. 

This way, restaurants can decide on the right prices, portion sizes, and promotions to make customers happy and boost sales.

Reporting for audits and inspections

Restaurant analytics makes reporting for audits and inspections a breeze by keeping track of operational data. 

During audit inspections, the team can quickly prove they abide by the regulatory laws by sharing accurate data about the restaurant's inventory, sales records, employee schedules, and adherence to food safety standards.

Gain competitive advantage

Optimizing operations, utilizing resources optimally, optimizing the menu, and reporting for audits result in a competitive edge. This well-rounded strategy builds a solid foundation for sustained success by helping the restaurant adapt to market fluctuations, implement cost-effective measures, and deliver value to stakeholders. Eventually, these process improvements make the restaurant adaptable and responsive to industry changes.

You now realize that the possibilities are endless once you start using analytics in your restaurant. Yet, the road to getting analytics working across all teams and creating a culture focused on data can be tricky. The challenges you face depend on how big your restaurant is and how complex your data team is – you might encounter a few or all of these hurdles.

Challenges restaurants face in implementing data analytics

Lack of awareness

Many restaurant owners might not fully understand how using data can improve their business. This lack of awareness means they miss out on opportunities to improve their operations, enhance customer experiences, and ultimately make more money.

Absence of a cohesive data strategy

Without a clear plan for collecting and using data, it becomes tricky to get helpful insights or see how the restaurant is doing. Not having a data strategy makes it hard for restaurant owners to make the most out of the available data.

Integration challenges

When data is scattered across many different places, like online and offline sources, it can lead to confusion and gaps in data. This makes it tough to get accurate insights and make smart decisions.

Resource constraints

Sometimes, there just isn't enough money or people to invest in tools or hire experts to handle data. This limitation can hold back the restaurant from using data to grow and run more smoothly. 

Tech barriers

Using old or incompatible systems can make combining all the data and gaining insights difficult. These technology barriers can prevent the restaurant from getting the most out of its data.

Training gaps

If the staff doesn't know how to use the available data properly, it's like having a tool that no one knows how to use. This lack of training means missed opportunities in utiliizing data to your advantage.

Scalability concerns

As a restaurant gets bigger, there might be problems with the systems not keeping up. Without solutions that can handle growth, the restaurant may struggle to adapt its data systems, which can affect how well it runs. 

To tackle these obstacles, restaurants should develop a cohesive data strategy, trust in data use, and be willing to invest in basic technology and training. This way, they can use their data to grow and operate more efficiently.

How restaurants can get started with data analytics

Based on insights from handling restaurant data, here are some pro tips from our in-house data engineers for your team to kickstart their restaurant analytics journey:

Understand what you want to achieve with data

Start by identifying specific goals you want to achieve with data analytics. This could include improving customer satisfaction, optimizing inventory, refining menu offerings, or increasing profitability. Clearly defining these goals provides direction and focus for your analytics efforts.

Tips to get started

  • Gather key stakeholders to discuss and define the primary goals to achieve with analytics. 
  • Consider current challenges, areas for improvement, and long-term business objectives.
  • Document these goals clearly to ensure alignment and understanding among team members.

Educate your team on data

Ensure that everyone in your team understands the basics of data and its importance in achieving the restaurant's goals. Provide training and resources to build data literacy among staff members. Help them understand how data can be used in their roles to contribute towards achieving organizational objectives.

Tips to get started

  • Organize training sessions or workshops to introduce staff to the fundamentals of data analytics. 
  • Cover topics such as data collection, analysis techniques, and interpretation of results.
  • Encourage participation and provide hands-on exercises to reinforce learning.
  • Preach the practical applications of data analytics in improving their daily operations and decision-making.

Build your data team & infrastructure

The key to creating a data-focused culture in your restaurant is the foundation you build with your data team and infrastructure. You have two options: either take on the task of hiring people, creating processes, and getting tools on your own (which might take months), or let 5X take care of it for you (we can kickstart the process within weeks). Here's a closer look at both approaches.

Setting up data infrastructure by yourself

Building a typical data team & infrastructure involves three steps:

Building the team

Defining roles: Clearly decide the roles you need and what each person on the team will do, like who works on data, who analyzes it, and who leads the team. Figuring out who does what might take some thought and time. This goes hand in hand with understanding the business needs and your goals for analytics.

Recruitment: Find and choose people who know about data and can work well with others. Look for a good mix of technical skills and teamwork. Finding the right data people with experience in the QSR or related industry can be tricky. But keep in mind that industry-specific experience is not mandatory. Evaluate their skills against your requirements to find the best match.

Tools selection

Assessing requirements: Tool selection begins with understanding your organization's needs and data processing requirements like volume, analysis types, and scalability requirements. The chosen tools should work together to create a seamless experience for people across teams. This can be complex as it requires a deep understanding of current and future data needs. 

Evaluating options: Evaluating options includes researching and comparing tools for data collection, storage, analysis, and visualization. Considerations include cost, ease of use, and compatibility with existing systems. The data space is highly fragmented, and finding the best fit can be challenging and time-consuming. 

Tool implementation: Building proof of concepts for selected tools is usually a big resource drain, taking 2-3 months and a ton of data team effort. Diverse data sources, use of legacy systems, resource constraints, skill gaps, budget limits, time sensitivity, security concerns, customization needs, and resistance to change add to the complexity.

Creating processes

Data collection and integration: Defining data collection and integration processes involves specifying how data is gathered, processed, and integrated into the organization's databases. The variety and volume of data sources can make the process complex. 

Training programs: Developing training programs involves creating structured learning paths to enhance the team's skills in using selected tools and technologies. Tailoring training programs to individual team members' skill levels and keeping them updated creates complexity. 

Quality assurance: Establishing quality assurance measures ensures the accuracy and reliability of data through regular checks and validations. 

Or, use a fully managed data platform

The data ecosystem is highly fragmented, and buying and implementing the right tools can be overwhelming, especially for newer teams and startups. 

Selecting and implementing the tools can last for over two months. It involves narrowing the choices from a range of tools in every category (ingestion, warehouse, BI, and more), creating POCs, handling contracts, looking for integrations with existing systems, and managing billing. 

Talk about hiring the data team: there simply aren’t enough trained and experienced data professionals willing to join a not-very well-known business with fewer project options. According to a 2021 Gartner report, even scouting a junior-level data science professional, let alone a data scientist, is challenging.

So obviously, doing this on your own can be expensive and time-consuming. Moreover, there's a risk of things not working out well and wasting resources. But not with 5X by your side.

5X is an end-to-end data solution provider, helping restaurants unlock value from data. We provide the people, processes, & tools to give you a 360° view of your restaurant, track trends, and make informed business decisions around acquisition, retention, growth, & operations. 

Why choose 5X?

  • Complex data, simplified: Streamline your data – sales, delivery, inventory, staffing – with 5X's centralized hub, making it easily accessible.
  • Expert guidance every step of the way: Don’t have a data team yet? No worries. 5X offers a team of experts to help you create dashboards and understand your data. 
  • Easy-to-use insights: 5X provides interactive dashboards and reports, making it simple to understand your business, customers, and areas for improvement.
  • Make your team data-centric: 5X doesn't just provide tools; we help build a data-driven culture in your team. Everyone, from staff to management, gets the know-how to use data effectively.
  • Stay ahead with predictions: The restaurant & QSR space progresses fast. 5X uses smart tech (AI and ML) to predict trends, helping you stay ahead of the competition.

Don’t just take our word for it. Listen to one of our many customer experiences.

5X has transformed the way we work. The automated data collection & reporting saves us 300 hours+/month. And the insights help us identify & double down on activities that boost store revenue.

Kevin Santiago

President, Cupbop

We’ve helped restaurants like yours streamline their data operations & save costs.
Sign up for the 5X Startup Program today, and let us handle your analytics end-to-end.

Join now

Monitor customer feedback

Analyze online reviews, feedback forms, and social media comments to gain insights into customer satisfaction, service quality, and dining experiences. Monitoring customer feedback allows you to identify areas for improvement in the menu, staff training, and services.

Tips to get started

  • Set up processes to collect and track customer feedback from various sources, such as review websites and apps, communities, social media platforms, and feedback forms. 
  • Use online reputation management tools or manual monitoring techniques to stay updated on customer reviews and comments. 
  • Categorize feedback based on common themes or topics, such as food quality, service speed, or ambiance. Study the feedback regularly to identify trends, patterns, and areas for improvement. 
  • Implement changes or improvements based on customer feedback to enhance the overall dining experience.

Track inventory closely

Use inventory management tools to monitor, and manage inventory levels, track ingredient usage, identify trends, and prevent issues such as overstocking or stockouts. This ensures proper supply chain management, reduces waste, and contributes to cost savings.

Tips to get started

  • Set up an inventory management system that integrates with your data analytics tools.
  • Record and track the usage of ingredients, taking note of quantities and expiration dates.
  • Utilize analytics to generate reports on inventory levels, identify slow-moving items, and optimize ordering quantities. Regularly review these reports to adjust ordering strategies, minimize waste, and maintain fresh inventory.

Promote transparency in data reporting

Foster a culture of transparency in data reporting. Ensure all team members understand how their contributions affect the restaurant's overall success. Clearly communicate data insights, performance metrics, and their relevance to organizational goals.

Tips to get started
  • Adopt a regular reporting system that shares key performance indicators and data insights with all team members. 
  • Conduct training sessions to help staff interpret and understand the data presented.
  • Emphasize the connection between individual performance and the restaurant's overall success to motivate and align team members with organizational goals.

Measure and communicate

Define key performance indicators (KPIs) for all aspects of the restaurant. Regularly measure and communicate these metrics to the entire team to foster a culture of continuous improvement and alignment with organizational goals.

Tips to get started
  • Identify and document KPIs relevant to customer satisfaction, operational efficiency, and financial performance. 
  • Implement a reporting system that regularly shares these metrics with all team members. 
  • Conduct regular meetings or workshops to discuss performance trends, celebrate successes, and identify areas for improvement based on data insights. Monthly or weekly all-hands meetings could be an excellent opportunity for this.

Do’s, don’ts, & KPIs for restaurant teams



Track KPIs

Identify and monitor KPIs such as total sales, average transaction value, and peak hours. This provides insights into customer behavior and helps in optimizing sales strategies.

Segment customers

Analyze customer data to identify trends and preferences. This helps build personalized marketing strategies and promotions to boost sales.

Use predictive analytics

Leverage predictive analytics to forecast future sales. This allows for proactive decision-making so that you are well-prepared for demand fluctuations.


Neglect seasonal trends

Ignoring seasonal variations can lead to inaccurate predictions. Consider seasonal factors to adjust your strategies accordingly.

Overcomplicate reports

Keep sales reports clear and concise. Avoid unnecessary complexity to ensure easy understanding for all stakeholders.

Disregard employee performance

Include employee performance metrics in your analysis. This will help you identify top-performing staff and areas where additional training may be needed.


  • Total Revenue
  • Average Transaction Value (ATV)
  • Customer Retention Rate
  • Menu Item Performance
  • Table Turnover Rate
  • Cost of goods sold (COGS)



Implement real-time inventory tracking

Monitor inventory levels using real-time tracking. This prevents stockouts, reduces waste, and ensures a seamless customer experience.

Set reorder points

Define reorder points based on historical data and demand patterns. This prevents overstocking or running out of key items.

Analyze supplier performance

Evaluate your suppliers' performance. Analyzing delivery times, product quality, and pricing can help you make better purchase decisions.


Delay updates

Regularly update your inventory data to avoid discrepancies. Delays in updating can lead to errors in forecasting and ordering.

Overlook shelf life

Consider the shelf life of perishable items in your inventory analysis. Avoid wastage by managing stock based on expiration dates.

Ignore demand variability

Be mindful of demand fluctuations. Analyze historical data to understand peak periods and adjust inventory levels accordingly.


  • Inventory Turnover Ratio
  • Stock-Out Rate
  • Carrying Costs
  • Order Accuracy
  • Deadstock Percentage



Track campaign performance

Monitor the performance of marketing campaigns. Analyze data on customer response, conversion rates, and return on investment.

Segment customer feedback

Analyze customer feedback and reviews. Categorize feedback to understand customer sentiment and tailor marketing strategies accordingly.

Use social media analytics

Leverage social media analytics to understand the impact of your marketing efforts. Identify popular platforms and content to refine your social media strategy.


Neglect data privacy

Ensure that customer data used in marketing analytics complies with privacy regulations. Protecting customer privacy is pivotal for trust.

Disregard channel effectiveness

Analyze the impact of different marketing channels. Avoid investing in channels that do not yield positive results.

Overlook competitor analysis

Include competitor analysis in your marketing strategy. Understanding competitor trends helps in differentiating your offerings.


  • Return on Investment (ROI)
  • Customer Acquisition Cost (CAC)
  • Campaign Conversion Rate
  • Customer Lifetime Value
  • Social Media Engagement

Kitchen team


Efficiency metrics

Use analytics to measure kitchen efficiency. Track prep times and order fulfillment rates to identify areas for improvement.

Ingredient usage analysis

Analyze ingredient consumption patterns. Optimize inventory and reduce waste by mapping ingredient ordering with actual usage.

Performance tracking

Implement analytics to track individual and overall kitchen team performance. Provide targeted training based on data insights to enhance skills and efficiency.


Ignore recipe popularity

Analyze which dishes are popular and require more attention. Neglecting this data can lead to inconsistencies in the quality and availability of popular dishes.

Overlook equipment downtime

Monitor analytics for kitchen equipment downtime. Ignoring equipment issues can disrupt operations and impact food quality.

Disregard staff workload

Analyze staff workload during peak hours. Disregarding this can lead to burnout and decreased efficiency.


  • Order Fulfillment Time
  • Food Wastage Percentage
  • Ticket Accuracy
  • Kitchen Staff Utilization
  • Health & Safety Compliance

Front-of-house team


Table turnover analysis

Utilize analytics to optimize table turnover rates. Enhance the front-of-house team's ability to accommodate more guests during peak hours.

Reservation management

Implement analytics for efficient reservation management. Ensure the team is adequately staffed and prepared for peak reservation times.

Customer satisfaction metrics

Use analytics to measure customer satisfaction. Identify trends in customer feedback to improve service and address issues promptly.


Neglect wait time analysis

Analyze data on customer wait times. Neglecting this aspect can lead to frustrated customers and negative reviews.

Overlook staff rotation

Monitor analytics for staff rotation and breaks. Overlooking this can impact service quality during extended shifts.

Disregard reservation trends

Analyze reservation data for trends. Disregarding this can lead to overbooking or understaffing during peak hours.


  • Customer Satisfaction Score (CSAT)
  • Average Service Time
  • Average Waiting Time
  • Upselling and Cross-Selling Success
  • Reservation Management

Unlock your restaurant growth today

Data-driven decision-making starts with building a solid data infrastructure and ensuring widespread data literacy. Yet, the true magic happens when everyone across the organization looks at data as an enabling factor, leveraging it across different departments. Depending on how big your restaurant and data team are, you might find it hard to start using analytics, but following the above-listed best practices can help you get started. 

Restaurant data & insights are scattered across apps.
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