In our latest product update, we revealed automated sales predictions to cost control. Once enabled for a site, Rotaready will intelligently forecast daily sales figures for each of your revenue/cost streams.
You can now copy our predictions into your own weekly sales forecast or simply inspect a date to learn how we’ve predicted your sales.
Benefits of automated sales predictions
If your business has several years of data, smart automation is great way to help you forecast for demand – allowing you to plan your staffing, budgets and resources more effectively, with advanced notice. Using Rotaready predictions, we’re confident we can improve on your existing forecasts, and save you time!
For new sites, automated predictions will help reduce uncertainty by matching your demand with anonymised knowledge of similar businesses.
Here’s a few examples of how it could benefit your business:
Automatic sales predictions for up to two weeks in advance means forecasting now takes only seconds
Improved forecast accuracy when benchmarked against your existing sales forecasts. Achieved by calculating seasonality, trends, and the impact of weather and special dates for each revenue/cost stream
Accurate sales predictions to inform other demand-sensitive aspects of your business, such as inventory and staffing levels. More accurate staffing levels removes the risk of over or under staffing and increases business productivity as a result
Flexible predictions allowing you to adjust sales figures if you know something we didn’t
How we predict your sales
We automatically train and deploy Machine Learning models which are tailored to accurately predict sales per site and revenue/cost stream. By feeding in historical sales data and demand features, like seasonality, special dates and weather, the model learns the factors contributing to daily sales. This delivers greater accuracy than traditional ‘uplift’ or ‘moving average’ methods of forecasting.
If you’re also able to supply existing sales forecasts, we can compare the Rotaready prediction with your own and ensure that our predictions improve on what you use already.
What our predictions look like
Above is a prediction for a restaurant’s Wet sales cost stream for a particular date. The sales trend describes the typical sales for a normal day. The model then calculates the effects of individual factors on the restaurant’s sales for this date.
We see that the bank holiday increases sales by over 30 percent and that the weather forecast also has a positive effect on the total sales for the day.
The row displaying the date describes the yearly factors of seasonality, whilst the Monday row tells the day of the week’s impact on sales.
Unlocking the future
We’re extremely excited to release sales predictions as we know how much value it will add to your business. But it doesn’t stop here… with every new partner integration, from EPOS to reservation systems, we’ll be able to better understand your business drivers and continually improve the quality of our automated predictions. This leads the way to real-time insights, accurate demand forecasting, and optimised rota scheduling in the near future.
We’re releasing automated predictions to sites with several years of sales data first. Please get in touch with firstname.lastname@example.org if you’d like to give it a try.
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