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Modern-day restaurant management demands navigating increasingly higher market competitiveness to achieve revenue maximisation and implement profitable strategies.
Fortunately, the power of advanced business intelligence in this digital era has created opportunities for many forward-thinking restaurant chains to exploit data analytics.
It helps them to enhance their internal processes, complement marketing communications, reduce customer wait times, and therefore, boost their bottom line.
New technologies are emerging that restaurant owners can exploit to record and extract meaningful data to improve operational efficiency and patrons’ dining experience.
For example, POS machines, kiosks, order and pay apps, QR codes, and even tableside tablets.
Besides their typical order and payment facilities, these tools offer an avenue for mining data from customer order history. This data can be applied to improve traffic flow and wait times.
Additionally, POS systems also provide actionable data points that can be used to track the frequency of customers, types of reservations, popular meal choices, etc. This data then helps the business owners to curate better menus and inform pricing.
It is important for restaurant owners to choose platforms and tools that do not just collect data but can be integrated with each other. Data interpretation across different platforms helps in generating an accurate, holistic analysis required to create a positive business impact.
Say, a restaurant needs to manage its labour costs. It may require an integrated analysis of the sales data, rostering data, table turnover data, seasonal fluctuation data, etc to generate the results.
These analytics are vital in today’s world for restaurants to gain competitive advantages in the industry.
Restaurant data analytics is the process of collating and analysing restaurant-related data and metrics to convert them into meaningful insights. This further aids in improving restaurant profitability, policies, and marketing campaigns.
Restaurant data analytics as a discipline also encompasses restaurant reporting, which involves comparing metrics of customer frequency, staffing, and profits between defined periods.
Generally speaking, restaurant data points or metrics should tell a story of how your restaurant runs.
Overall, the fundamental premise of restaurant analytics is to perform a deep analysis of restaurant metrics to better understand ‘why’ a business is performing in a particular way, and “what can I do to make it better?”
Restaurant business intelligence and data analytics platforms primarily help to track sales and metrics across all platforms. They aid business owners in understanding how their restaurant is performing across delivery, dine-in, online and reviews.
Here’s what you get when using analytic dashboards:
Restaurant analytics can help you frame a persona to better understand your customers and respond to their nuanced needs. For example, the food they like, the sports they watch, or even their specific food-related behavioural patterns.
Generally, analytics provide an avenue to identify current trends and segment customers into profiles/groups. These trends can be derived and exploited from historical data to build lasting relationships with guests.
Restaurant analytics can be exploited for predictive forecasting of future trends and revenue based on historical data comparisons with existing figures.
With the ability to accurately predict sales into the future, you can easily devise strategies and incentives like offering meal coupons, discounts, and even partnerships. It helps in creating precise staffing timetables as well as optimising labour costs. Additionally, this prediction ability can also help in budgeting and scheduling these events and incentives.
Analytics can help you determine how to best reward loyal customers, or even when to reward them.
For instance, if a specific group of customers always post about your restaurant and leave rave reviews on social media, you can send them rewards through social media.
That way, they can even boast more about receiving rewards within their social circles.
Restaurant data analytics can help when determining items to keep on the menu, or which dishes to re-introduce. Or better yet, meals to consider for couponing, promotions, and discounts.
For instance, if a particular item no longer gets re-orders yet it was previously popular, you can analyse restaurant analytics to dissect why.
Maybe the quality of raw material has dropped, or it’s just off-season. Either way, you can exploit customer feedback with your insights to achieve the perfect balance of items across disparate menu categories.
Momos platform generates accurate item sales data reports to make this process super simple for restaurants to manage across different outlets and sales channels!
Restaurant data analytics can help reveal crucial insights about restaurant guests to enhance their experience.
For example, insights into order preferences, demographics, and reservation habits can help restaurant owners to better personalise the guest experiences.
This could include offering guests a complimentary dessert on anniversaries or birthdays. Or even paying attention to cuisine preferences when sending out personalised offers to guests.
Restaurant analytics can be employed to boost operational efficiency across elements like:
When done right, analysis of all these data points can help you optimise for repeat business or simply cut costs where necessary to streamline a restaurant’s service delivery.
Labour cost management can be an overarching challenge in restaurant management.
However, analytics solutions can help with cost optimization. For example, it can help to identify slower shifts to keep costs low as fewer employees will be required during that period.
State-of-the-art predictive analytics tools can be directly connected to a restaurant’s ordering system to improve order accuracy.
For example, to predict food items that will most likely be requested during particular hours of the day to help guide procurement efforts and supplier management to meet customers’ demands.
Food wastage is a massive challenge in the restaurant industry. That's why, when planning a menu, it is important to know what quantities of ingredients are required to best prepare a meal.
Predictive analytics can help restaurants to analyse past and present inventory levels to recognise patterns and order the required quantity, as needed, to control food costs and ensure efficient use.
Restaurant analytics can help you to maintain an optimal number of kitchen and waitstaff throughout the week.
Actionable insights can also help with strategic scheduling based on busy days when sales are the highest or even during holiday seasons.
For instance, a restaurant owner can analyse historical data during the Christmas period and employ it to schedule the right mix of part-time, and full-time labour on a range of schedules.
Empty tables, unfortunately, represent lost revenue for a restaurant. Fortunately, analytic tools can help to overcome this challenge via assessment and exploitation of various critical data points.
For instance, a restaurant can analyse no-show rates, and in turn, impose reservation deposits to avoid such incidents. Or rather, they can also choose to run special offers and discounts to fill the tables.
Technological advancement has enabled restaurants to analyse historical data like price, customer frequency, and demographics to shape marketing strategies, execute customer segmentation, and guide menu management.
However, big data can be exploited for far more creative and advanced purposes than the abovementioned, for instance:
The article summarises how modern restaurants can exploit data analytics to assess a variety of business strategies to improve operational efficiency and customer experience.
For example, Domino’s Pizza has been continually improving its sales performance.
The brand enables one-to-one buying experiences across various 85,000 structured and unstructured data touchpoints derived from its POS systems, supply chain centres, text messages, social media, and Amazon Echo data.
Take another example of Tropical Smoothie Cafe which runs outlets in several cities in the United States, serving healthy smoothies and food. They used restaurant data analytics to check on the performance of their new product (vegetable smoothie).
Once they realised that it gained popularity on their menu, they utilised the analytics to see the hours when customers preferred to go for a veg smoothie vs a fruit smoothie. The results helped them to create happy hours and other marketing campaigns for customers, thereby increasing sales.
Overall, restaurant analytics can help many food establishments to leverage insights on customer data in real-time to reduce costs and improve marketing ROI.
This is perhaps one of the most convenient and accurate options to make more informed business and marketing decisions to improve profitability.
Need to effectively grow and manage your restaurant business with easy-to-use tools, real-time alerts, and simple dashboards? Reach us at Momos.
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