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Machine learning use case in the F&B industry

Predicting the business viability of restaurants

Predicting the business viability of restaurants using machine learning

To survive in the highly competitive food and beverage industry, restaurants need a strategic advantage. Understanding a restaurant’s strengths and weaknesses, including in-depth competitive market analysis, is essential to the success and longevity of the business. Analyzing foot traffic, customer churn, and related customer and marketing data and transforming it into actionable insights utilizing business intelligence software provides a competitive edge, vastly improving chances of success.

In this use case, we leverage the latest data science and artificial intelligence technology to identify and analyze key factors that determine the restaurant’s viability, such as the type of the restaurant, location of the restaurant, type of cuisine served, and the availability of online ordering.

EVNet

Use case highlights:

  • Machine learning models and data science techniques that gain insights on factors that are significant in determining a successful restaurant
  • Researching and analyzing feasible locations to start the restaurant
  • Performing customer analysis to understand demand and behaviour to gain a competitive advantage

Why Choose IntellectDataTM as your AI and data science partner?

  • Broad-spectrum of products and services employing leading-edge technology, providing a strategic and competitive advantage
  •  Industry-leading expertise developing and implementing digital products and software services incorporating data science, artificial intelligence, image and video analytics, text analytics, predictive analytics, recommendation engines, and visualization
  • Easily integrated with other mission-critical enterprise applications and platforms to solve any data-driven problem
  • Unmatched standards for quality, scalability, and performance create exceptional value, propelling organizations to the next level of insight and action
  • End-to-end services from consulting to full-cycle software development
  • Empower non-experts to use machine learning models and techniques without the need for prior expertise in the field
  • Complete adherence to data and security regulations such as HIPAA, Data protection 2018, etc.

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