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10 Ways Analytics is Changing Restaurant Business

Artificial Intelligence, Blog, Data Analytics, Data Science, Machine Learning, News, Restaurants

If you’re in the restaurant business, you’ve probably already heard a lot about how restaurant analytics can help bring in more customers. But are you aware of the operational, and predictive ways in which analytics can impact other areas of your business?

    1. Sales

With advanced restaurant business analytics software, you can uncover key insights on the performance of stores and products, the productivity of resources, and sales category performance – all in real time.

    1. Operations

Use data analytics for restaurants to see how you’re doing on key operational metrics such as delivery time, cook time, wait time, store efficiencies, labor, and more. Know the performance of franchise owners by region and/or store.

    1. Menu

Advanced restaurant software can also give you insights into deeper questions such as which products sell well together, what are the top customer choices by demography, how historical sales patterns will impact transaction value, and much more.

    1. Location

Analyze the potential of a new store location, using location and guest demographics to postulate footfalls and potential sales. Compare and choose the best site for your restaurant with comprehensive data sets that translate into high demand.

    1. Mobile App

Improve engagement on your mobile app through in-depth analytical understanding. Know when, where, and how customers use your app in order to engage them with contextual messages in real time. Encourage mobile app orders based on location, current order, cart components, and the guests’ historical relationship with your brand.

    1. Customer Satisfaction

Advanced restaurant analytics software should be able to give a view of customer satisfaction by channel and store, allowing deep-dive analysis of how Net Promoters Score (NPS) impacts store performance. Using analytics, you can, therefore, identify both broad (across-store) and narrow (within a store) reasons for dissatisfaction down to each guest level.

    1. E-commerce

Analytics enables a finer understanding of online customer purchase behavior, a source of traffic, traffic conversion, preferred offers, typical order size, and more. Using this information, you can then influence customers as they place orders by recommending relevant products they might like and minimizing abandonment with timely intervention.

    1. Marketing

Restaurant Software enables clarity into campaign performance and its impact on sales. By harnessing customer data from various source systems, you’ll be able to understand your campaign performance from the guests’ context, and deliver personalized 1-1 campaigns on channels they prefer: during the best daypart, on a day they are likely to respond; all using automated marketing.

    1. Personalizing

Analytical behavioral clustering, propensity models, and churn prediction algorithms can help you uncover customer opportunities and risks. You can dynamically segment customers on multiple dimensions such as day-part, order value, visit frequency, price sensitivity, taste, occasion preferences, and more. By knowing the micro-segment each customer belongs to, you can tailor your messages with specific promotions, reduce churn and give loyal customers more reasons to return.

    1. Compliance

Maintaining brand, safety, and employee training standards across equity and franchise stores is critical. Advanced analytics can help ensure operations and food safety compliance, monitor the status of employee training, identify talent, and understand the impact of employee performance on store performance.

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