Cross Tracker Analysis lies at the heart of T-Stats, and is possibly its most powerful feature. It links together all the individual trackers (accommodation, attractions, Airbnb, footfall, weather, etc) and allows you to compare their performances.  This allows you to discover correlations, such as finding out if rainfall affects visitors to outdoor attractions, or the impact events have on accommodation occupancy.

In Cross Tracker Analysis all the trackers in your T-Stats system are shown on the left hand side of the screen.  All you need to do to include data from a tracker in the chart (see below) is to tick its box.

You can include as many trackers as you like, although the chart can get messy and confusing if you add too many!  It is best to add just two or three at a time.

In the example here, visits to outdoor attractions (green) have been compared with average rainfall (red).  Where we might expect to see stronger footfall numbers at outdoor attractions in May and October, we can see there was also considerable rainfall, which may have had an impact on visitor behaviour.

All the data is compiled from the trackers in your T-Stats system (which includes the National Trackers too).  This really is a feature that can tell you so much about your destination, and is as easy to use as ticking the boxes of the trackers you are interested in.