Artificial Intelligence is the branch of computer science that has picked up speed and has shown its presence across industries over the past few years. AI involves programming systems in such a way that they learn and improve over time, on their own, with the help of data.
The benefits of AI in the restaurant industry extend beyond robots taking orders, making and delivering food. AI can also help restaurant owners make sense of data to improve the diners’ experience.
Restaurants are always seeking ways to reduce labour costs. The high staff attrition rate is also a characteristic of the restaurant industry. Increasingly, restaurant owners are looking to AI to address and overcome these challenges.
Let's take a look at a few ways AI and ML can have benefits for the restaurant industry.
Machine learning (a subset of AI) can be used to forecast revenue for restaurants. Using historical data and other external factors such as holidays, weather, local events etc., machine learning models can predict the revenue quite accurately.
SpeQue Sales Forecast
From our experience, we have seen that the SpeQue Sales forecast, for instance, is able to predict the restaurant sales to an accuracy of almost 90%. Apart from historical data, we also use external factors as mentioned earlier. This data is fed into our machine learning models (we have deployed Microsoft’s ML .Net ), which then predict and give us the forecast for coming weeks or months.
Machine learning can also, with a great degree of accuracy, predict sales of dishes depending on external factors as mentioned earlier. This can help restaurants plan better.
Stock prediction and waste management
Restaurants incorporating AI in their restaurant billing software have an advantage of significantly cutting down costs with comprehensive analytical data accumulated by the system that tells the management about the usage of items in their inventory. Tracking and ordering items based on their usage prevents any items from being underutilized or going out of expiration.
This also helps in monitoring, if the staff is following the recipes and delivering proper portions as set by the restaurant to the customers. Avoiding waste and theft by implementing AI has the potential to save a lot of capital for restaurants in purchasing and managing their inventories.
AI-based Recommendations & Suggestions
Machine learning models can also be used to provide curated recommendations based on order history. The amazing thing about these models is it will work for all restaurant types, across cuisines and across geographical boundaries. These suggestions can also help captains and stewards cross-sell or upsell items while taking orders.
SpeQue restaurant billing software recommendation engine uses ML .net to provide 2 types of recommendations (1) recommendations at the dish level: basically looks into historical data to check which items pair best (2) personalised recommendations: works at the individual level. ML models provide suggestions to customers based on their particular order history and food preferences. This kind of curated recommendation is only possible with the use of machine learning.
SpeQue User app uses the 2nd kind of recommendation engine to provide curated, personalised recommendations to customers.
Chatbots have been prevalent for some time now, but the use of chatbots is still in its infant stage in the restaurant industry. While a few big players such as Domino's do use chatbots to take online orders from customers, such implementations are few and far between.
SpeQue Bot on SpeQue user app helps users locate their favourite restaurant based on their location, food preference and budget. It also helps them to check table availability and books their table, without having to make a call. This also reduces the requirement of manpower at the restaurant end and automates the complete inquiry and booking process for the restaurant.
Self Checkout Kiosks
With the increasing cost of manpower (the recent COVID-19 crisis could also be a compelling reason), self-ordering kiosks will definitely be the future of dining.
Guests can spend time studying photos, ingredients, and nutritional information, as well as easily request more food or drinks as the meal progresses. What’s more, self-order technologies tend to reduce the repetitive, transactional demands on servers, freeing them to be friendly ambassadors for your brand. Expect to see more of these types of applications.
AI is, without doubt, the future and we, in the restaurant industry, cannot afford to be left behind in this technological race. As we saw, AI not only helps make operations more efficient, it also helps to improve the dining experience and saves costs in terms of reducing manpower. It also provides deep analytical insights into your business and helps you stay ahead of the game.