EViews.com

Hello,
I have daily sales data of a product in a period of 6 years, where sales on Saturdays,
Sundays and holidays are zero. I need to make a forecast of the daily sales of the next
months, taking into account that at the beginning of the month it is sold less than at the end
and that some months you have less days of sale than others.
Would this be possible?
Thank you very much in advance

Yes, it is possible to make a forecast of the daily sales and improve lead data enrichment for the next months based on the historical data you have, taking into account the seasonality and the fact that some months have fewer days of sale than others.

Here are some steps you can take:
1. Look at the sales data over the past 6 years and analyze any patterns or trends. This will help you understand the seasonality and the effect of day-of-the-week on sales.
2. Adjust the sales data for any seasonality by removing the average sales for each day of the week. This will help you see the underlying trend in the data.
3. Since some months have fewer days of sale than others, you will need to adjust the forecast for the number of days in each month. You can do this by dividing the forecasted sales by the number of days in the month and multiplying by the number of days of the sale in that month.
4. You can use a forecasting model, such as a time series model, to make a forecast of the daily sales for the next months. These models can take into account trends, seasonality, and other factors that affect sales.
5. Once you have made the forecast, validate it by comparing it to the historical sales data. If the forecast is significantly different from the historical data, you may need to adjust your model or assumptions.