# DRIVER VARIANCE

Under Get Started load the dataset "01 Travel". The dataset looks like this.

The "amount" is the monetary value of sales. Nights is the "units" sold column . Visits is the number of visits to the site. Bookings is the number of "checkouts". Amount minus Commission is Net Sales. Net Sales minus COGS is Margin.

Hit on submit and you get the first report. An increase of travelers coming to France represents the most important item in terms of Price and Volume Variance. Variance Running Total converges at 33,000 which equals the difference between the two years.

Let's play with drivers now. Set "Show variance as" to "Price, Volume & Mix, Drivers" variance and hit submit. The increase average ticket sale fell, but was compensated by more visits and more checkouts of customers wishing to travel to France. .

We can drill down the first row result to understand more of the reduction in average ticket amount. It mainly concerns travelers to France, whose number and conversion rate as we know swelled.

If we choose "Price, Volume, Mix, Drivers Variance" we get a slightly different results that splits the change in average ticket sale (shown as "average ticket" variance) from the overall impact of the "mix" of accommodations we are selling (shown as "mix" variance). Both are going down in this case.