Forecasting online sales is quite easy if there is historical data available. If all of sudden you were given extra budget for your search or online display campaign, performing a diminishing returns model will help predict the amount of conversions you can expect to generate with this increased budget. Likewise, if you have to cut online spend, a diminishing returns model will show you the expected conversion volume loss as a result.
Let’s suppose we want to predict the increase in search conversions (dependent variable) based on an increase in paid search spend (independent variable). Would we use a linear or logarithmic-scale to determine our forecast equation?
To view and download free step-by-step instructions on how to predict online sales, go to Smart Digital Spending.com.
