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I am trying to create a forecast using a monthly timeseries data set of marketing expenses for a fictional company. The data looks something like this:

Marketing Expenses Data Set

Using linear regression to forecast future sales, I get the following result:

Linear Regression

My problem lies with the seasonality of the marketing expenses (higher in the summer months for instance). I would ideally like to calculate to forecasted values of future months including seasonality. I read somewhere about ARIMA forecasting, but am really searching for some best ideas on how to accomplish the task.

To be clear, I do not JUST want a chart and trendline, but the data to support it too.

Any help would be much appreciated!

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(Seasonal) ARIMA would be one possibility, but fitting it with plain Excel without specific plugins would be a major pain.

An alternative would be Exponential Smoothing, specifically seasonal Exponential Smoothing, also known as the Holt-Winters method. The formulas can easily be coded in Excel.

I warmly recommend Forecasting: Principles and Practice, 2nd edition, by Athanasopoulos and Hyndman. And I also recommend that you consider looking at R. FPP2 is a good introduction to time series forecasting using R.

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  • $\begingroup$ Thank you! I'll take a look at it. I have R knowledge, but unfortunately my work only allows Excel. Trying to convince them that it's free and not dangerous... $\endgroup$ – Dan Dec 19 '17 at 11:16

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