Send a message to Ryax Technologies

Listing summary

  • Predict your sales by taking into account your seasonal parameters Retail
  • €260.00  / use (try free)

Analytics status

  • Available

Business benefit

The major positive impacts to be expected by running this analysis are essentially on :
▪ total turnover
▪ sell-through rate

Data inputs (mandatory)

We'll be using historical sales data containing the following information :
▪ Date : historical timestep of observation (could be daily, monthly, weekly…)
▪ SKU :SKU ID, item identification number
▪ Revenue : sales in quantity or revenue

Data Output

You get the predicted sales per SKU in the format you need

Technical description

This analysis is made using a procedure called Prophet. It is forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.

Limitations

It works best with time series that have strong seasonal effects and several seasons of historical data.

Description

Having troubles predicting your sales with your business being impacted by seasonal factors? This analysis gives you the ability to predict your future sales by taking into account all your seasonal parameters - holidays, events, commercial impacts... add them as constraints for the model and it will return related sales forecast.

We recommend to perform this analyis in a timeline matching the product lifecycle, for example, at the stock arrival date. It can either be an automated analysis sent periodically through mail or a regular process pushed to your favorite supply chain ERP/demand planning tool