Big Data Analytics: Driving the Restaurant Industry towards Profitable Growth

Big Data Analytics: Driving the Restaurant Industry towards ProďŹ table Growth -Hidden Brains Enterprise Web & Mobile App Development Company

What is Big Data?

According to Techtarget, “Big data analytics is the process of examining large and varied data sets i.e. big data – to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions.”

Big Data in the Restaurant Industry Restaurants are witnessing epic behavior changes in millennials and centennials who are replacing baby boomers. Changing demographics are helping create new experiences for customers. Restaurants, grocery store owners and food retailers are heavily focused on repeat customers. The key to achieving long-term traffic growth and market share is getting actionable insights and data-driven information about customer preference that will help prepare for the future.

Big data can be described by the following characteristics

Volume : Quantity of generated and stored data Variety : Type and nature of the data Velocity : Speed at which the data is generated and processed Variability : Inconsistency of the data to handle and manage it Veracity : Difference in quality of captured data can affect accurate analysis Big Data Sources : Restaurant owners need both structured and unstructured data to create actionable insights that give a complete view of customers.

Big Data Analytics in Restaurants

Restaurants can drive performance by applying insights from advanced analytics in the following ways: On-time Delivery With several big data analysis tools and techniques, food delivery can be optimized to deliver a seamless experience to customers. Big data analytics can gather data from several sources such as traďŹƒc, weather, temperature and route to provide a fair estimate of time taken to deliver goods. Big data analysis can predict the impact of all above factors on food quality. Thus data analysis allows effective planning of your resources to avoid transporting stale products and deliver perishable food items in good quality.

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Menu Enhancement Menu reengineering and optimization can help maximize proďŹ ts and customer satisfaction.

Restaurants can use data to build customer proďŹ le that include favorite drinks and food. Your POS system should be able to help you identify which menu items are most popular. From online surveys and feedback forms, you can identify whether menu items need to be improvised or completely revamped.

Effective Customer Segmentation Restaurants can segment customers based on several factors to personalize promotions to increase proďŹ tability, and better customer engagement. Factors such as demographics, age, income brackets, ages, marital status, preferences, food allergies, as well as dining out preferences can help you know your audience better.

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Custom Dining Experience Analytics tools can help track guest preferences based on whether they enjoy red wine, specialty drinks, or exclusive Italian treat. This vital information can help you provide customized dining experience for individual guests. With guest proďŹ les, restaurant owners can suggest menu choices; help regular customers celebrate birthdays or special occasions, ultimately increasing proďŹ ts.

Streamline Operations With effective data analytics, root-cause analysis and predictive analytics, restaurants can predict future revenue. Restaurants can prescribe actionable recommendations to change business operations and optimize proďŹ tability.

Big Data: Part of Integrated Solution

LEVERAGE SOCIAL MEDIA Collaboration between restaurants and manufacturers or distributors, through shared digital events or joint social media pushes.

RETHINK CUSTOMER EXPERIENCE Design & integrate services to bridge the gap between order placement and serving customer. Develop analytics capabilities to understand customer preferences and preferred channels.

BE LOCALLY RELEVANT Optimize marketing programs, loyalty programs and rewards for local areas. Consider the unique customer, category and environmental factors related to the area.

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