Using segmentation has never been so easy
Thanks to this new engine, all the constraints you may have faced in the past are now gone:
- Segments can be applied on groups of sites,
- No need to save a segment to run an ad-hoc query, everything can be done on-the-fly,
- The cohorts periods are no longer limited to 30 days,
- Any time period can be segmented without requiring to save the dataset.
Data Query 3 is the very first module to benefit from this new engine. In the months to come, the entire Analytics Suite will be using this enhanced engine!
You can save the segments you create. This will allow you to reuse them in your datasets without having to reconfigure anything. They are in the left bar, below your properties and metrics, as well as in the "Existing Segments" tab of the Segmentation Panel.
When saving a segment, a segment-key will be filled in. This is especially useful for making API calls without having to enter the segment details again.
InformationThe recorded segments are common to all sites in your organisation and can therefore be used in any of your operating areas.
Combination of filters on properties of the same event
This segmentation engine will open the doors to the advanced exploitation of your tagging plan. With each tracked event (page view, click, addition to cart, video play, etc.), you will be able to analyse all the properties of these events, whether they are standard or custom.
It will therefore be very easy for you to isolate the visits during which visitors have (1) loaded a product page (2) on any device but a desktop, (3) for any of the listed artists, (4) for Goodies in either accessories or concert categories, filtered on the Known artists only (4) . All of these filters have to be tracked on the very same event, which is very powerful!
Conditions "AND" and "OR"
When you select multiple events in your segment, you can combine them with "AND" and "OR" operators to narrow your search.
It becomes, for example, very easy to select visitors who have:
- EITHER added a concert or festival featuring Alicia Keys or Amy Winehouse to their shopping cart,
- OR added a hoodie featuring Eminem to their shopping cart.
This is also possible to run a similar segment to get all visitors who have:
- BOTH added a concert or festival featuring Alicia Keys or Amy Winehouse to their shopping cart,
- AND added a hoodie featuring Eminem to their shopping cart.
Sequences of events
Sequential segmentation makes its appearance in Data Query 3, allowing you to select visits or visitors based on a sequence of events!
Based on the previous scenario, we could also focus on visitors who have:
- FIRST added a concert or festival featuring Alicia Keys or Amy Winehouse to their shopping cart,
- AND THEN added a hoodie featuring Eminem to their shopping cart.
You're able to combine 3 steps. Please note that they don't have to be strictly consecutive, other events could have happened between steps.
Cohorts of visitors and users
With this first iteration of advanced segmentation, you can quickly analyse visitor behaviour over time, especially to understand how a group of users with common characteristics (e.g. Christmas shoppers) behaved over another period (e.g. during the Christmas shopping preparation period).
You will be able to use either the segmentation "Visitors" (cookies or device ID, therefore mono-device) or "Users" (connected account, useful in cross-device).
The cohort period can be either fixed, or the same as the analysis period. We're also working on adding relative periods to improve the power and flexibility of the module.
Cross-scoped cohort segmentation
Are you looking to analyse the behaviour of certain users of your mobile applications when they use your responsive site?
Or would you prefer to understand how visitors to your store behave when they browse your corporate site or vice versa?
Nothing could be simpler with inter-site segmentation - you can track users or visitors from one site to another.
Good to know
You can create a cohort without associating a property to it. This allows you, for example, to analyse the behaviour of all visitors when they are identified on your sites or applications.