Using statistical models to predict future sales

Building Models of Customer Behavior using Statistics and Multiple Regression


We also offer online tools for data analysis


Use nonlinear multiple regression to build a predictive sales model.


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Weather, Sales Trend demand forecasting
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Build a model of customer behavior using regression analysis of sales data, weather conditions, holidays, and general sales trends.

Generate Models of Customer Behavior and Sales Trend using Multiple Regression Analysis.  This tool uses nonlinear multiple regression analysis to generate possible models of customer behavior by analyzing patterns in daily sales figures associated with local weather conditions, seasons and holidays, the day of the week, and general sales trend.

View previously built models of customer behavior

View Previously-built Models of Customer Behavior and Sales.  BrainTech, LLC staff and site visitors have used the above tool to create sample models.  This tool lets you view, interpret, and experiment with these previously-saved models.

Sales trend and general summary statistics

Analyze basic Sales Trends and view Sales Summary Statistics.  This tool calculates the direction and relative strength of two variables often associated with sales: the passage of time (a general sales trend), and the day of the week.  Using Pearson's r, partial, and semi-partial correlations, the association between each variable and sales is displayed independently, and then combined and overlayed onto a graph of actual sales.  The source code for the calculations performed in this tool can be found here.

Visualize sales data using a variety of graphs and charts

Generate Sales graphs in various formats, with an option to overlay a demand-trend curve.

If you would like to analyze your own data using these tools, we request that you either log in to your account or create a new account. This ensures that your datasets and analyses remain private and can only be viewed after logging in to your account with your username and password. As a guest, you can work with the sample data sets, but any changes you make to the data will not be saved).
















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