Step By Step Guide
Upload a spreadsheet containing the last 2 - 5 years of Food and Beverage consumption data.
Ensure that one of the fields in the booking data is 'Consumption'. One of the ways to do that is to provide an aggregate consumption of items per week, along with other parameters which are important to your business.
You can classify your data at a high level category such as Food/Beverage/Others or at a detailed level such as Breakfast/Lunch/Dinner/Drinks et.
Step 2 [Done by Hornbill.AI]
Hornbill.AI parses the dataset and augments it for predictive analytics
Create an AI project in Hornbill.AI using the dataset from Step 1, and select the field 'Consumption' for prediction.
Step 4 [Done by Hornbill.AI]
Hornbill.AI will build an AI model after comparing with Industry's best predictive algorithms and will choose the best one for maximum accuracy for your industry and dataset.
Once the trained model is available in your Project, you can provide a future week and one of the categories as input to the model, and get an anticipated consumption during that week.
Please note that, like any AI program, the impact and accuracy of Hornbill.AI models will depends very much on the the input data is provided to train the AI model.
While we take extensive measure to parse the datasets and remove outlier scenarios which can impact prediction, we would recommend users to prepare accurate and detailed datasets for building your AI project.