Using T-Stats as a Data Collection and Analysis Tool: Cross Tracker Analysis
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.
What Analytics are Possible?
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 (on the right hand side of the screen) 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 below, visits to attractions (green) have been compared with sunshine hours (red). It can be seen that there appears to be a direct correlation between the two for the first five months of the year – when the weather is brighter, the number of visitors to attractions increases. In June, July and August, the number of visitors to attractions grows irrespective of the declining number of sunshine hours.
Where Does the Data Come From?
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.