Video Intelligence for hospitality chains [To improve operational efficiency].
Over a decade of technology advancements, hospitality industry is getting transformed with the help lot of digital solutions. Starting from the room check in to customer engagement.
These days a lot of mobile and web platforms are available to check the best deals & offers, book online, to submit feedbacks etc.
Virtual Reality and Augmented Reality solutions are the new trends to drive in more customers. These solutions will provide a virtual experience prior to their decision making part.
Emergence of AI solutions in hospitality sector
Now at this point of time with the emergence of AI solutions, Chatbots or smart kiosks, are playing a vital role in customer engagement. NLP techniques, bot frameworks etc. are making things into reality here. These systems with conversational interface can handle customer queries related to the property, handles property booking, payment, feedback collection etc.
Video Intelligence- An AI powered solution
All these touch points are focused on customer experience. How about systems that can contribute towards operational efficiency analysis? By using video analytics powered by computer vision and deep learning algorithms, AI systems can track the employees and the various performance metrics. Input will be the video feeds from the CCTV or surveillance cameras deployed in the property premises.
Let us see how we can implement the same in case of a restaurant chain:
Being data driven!
Based on the data collected, we can integrate advanced data analytics techniques. A web and mobile based platform to showcase the following insights:
Footfall Analysis- Analyse avg. time spend in a restaurant
Real time head count analysis to calculate the lean period and optimise workforce accordingly
Calculation of Avg. time taken by a waiter to serve a table
By integrating sales data we can forecast the sales for coming months using predictive analytics
Measuring customer emotions from the video feeds is around the corner. Using facial recognition systems and video analytics, we can measure the emotion level of the customers. It can act as autonomous system to collect customer feedback.