Auto Forecasting
Learn more about Moselle's AI forecasting and the various models you can utilize to automatically forecast and plan your inventory for the upcoming 12 months.
AI-Generated Unit Forecast
Moselle offers three different machine learning forecasts to help you automatically predict the next 3 to 12 months, depending on your plan. These models are excellent starting points for your business and intelligently learn from your historical sales data. As you continue to use Moselle, the forecasts will improve over time.
Statistical Models
Ensemble 1 - ARIMA weighted model
This is a statistical model that uses lagged moving averages to predict future values. The model employs deep learning to automatically tune and blend various forecasts, providing the most accurate prediction for your business.
Ensemble 2 - Exponential Smoothing weighted model
This is a statistical model that uses lagged moving averages and seasonal trends to predict future values. The model employs deep learning to automatically adjust and combine various forecasts, offering the most precise prediction for your business.
Probabilistic Models
Tuned Probabilistic Model - Prophet-based model
A model for nonlinear trends forecasts yearly, weekly, and daily seasonality, as well as holiday effects. Examples of holidays that can be incorporated into this trend include Amazon Prime Day, Black Friday, and Boxing Day. The model uses deep learning to automatically tune and blend various forecasts, providing the most accurate forecast for your business.
The model can also be influenced by custom data, such as a marketing calendar or spending, which you can upload.
Deep Learning Models
Temporal Fusion Transformer (TFT)
This model is specialized in deep learning models for time series forecasting. It is designed to handle complex patterns by incorporating multiple types of data (historical trends, seasonality, events, and holidays). It can also provide insights into which variables or time periods drive forecasts.
Gross Revenue to Unit Forecast
Sometimes, you might already have a revenue goal or forecast set outside the Moselle app, and you want to input the overall gross revenue to determine and break it down into a unit forecast for replenishment and allocation.
Top Down Forecast
Input gross revenue for each channel by month in the goals table for a given scenario plan.
Convert
Once complete, your converted unit forecast will be displayed on the planning page forecast table.
The AI will approximate the revenue for each active SKU in your catalog and will follow these rules.
Revenue is split based on the probability of sales for each SKU.
For some SKUs, it might be determined as a new SKU, and it will find the best comparable item to plan out the future item. Comparables can be overridden.
For some low-selling SKUs, sales will be shifted to the nearest full unit while revenue goals are maintained.
Depending on the catalog size, this conversion process can take up to 30-40 minutes as it tries to find the best forecast result.
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