The Segments Report allows you to compare size and key metrics of different segments of visits and see how they changed over time.
With the Segments Report you could:
- find out conversion rate for any process, for example, in how many visits users added a product to a basket and in what percentage of those visits users actually made a purchase
- compare conversion rate for visits from different devices and how it changed over the last three months,
- evaluate impact of different behaviours on financial metrics such as revenue, cost and profit or behavioural like time spent on site, number of interactions.
Representation of the Segments Tree in the Report
The Segments Reports shows data for a currently (1) selected segment on the tree, (2) its direct subsegments (children) and just number of visits (3) their direct subsegments (grandchildren).
Table of Metrics
The table at the top of the report view contains currently (1) selected segment and (2) its direct subsegments (children), as defined in the tree. If a branch has defined label, the label will be displayed, otherwise the filtering rules.
Visits in the Segment
Visits in the Segment means the number of visits which meet segment’s filtering criteria. The percentage values are relative to number of visits in the selected segment, therefore, the value in the top row (black background) will always be 100%.
Margin of Error and Confidence Intervals
The bars next in the Visits in the segment column are based on the percentage values. Semitransparent areas on the bars indicate margin of error for visits share and provide you with a quick way to check how precise a result is and if differences in sizes of segments are in fact statistically significant.
You can hover the bar to see the exact values of confidence intervals. The confidence intervals are calculated at 95 per cent (or 0.95) confidence level which means that there is a probability of at least 95 per cent that the result is reliable.
|Avg Visit Duration||Average time spent on website during a visit, in seconds. The value is calculated as (A) totalTime/Visits in Segment.|
|Avg Sections per Visit||The average number of times (M) Section event was tracked during a visit. This should not be read as number of different Sections user visited as that could just as well be multiple impressions of the same Section. The value is calculated as (A) Sections/Visits in Segment.|
|Avg Events per Visit||The average number of (E) interactive and (M) meta events tracked during a visit. This metric can often be a better indicator of users’ engagement than visit duration which can be greatly affected by long periods in which users are idle. The value is calculated as (A) Events/Visits in Segment.|
|Avg Errors per Visit||The average number of times a (M) Error event was tracked during a visit. Since tracking of errors require custom integration this value might be The value is calculated as (A) Errors/Visits in Segment.|
|Visits with Errors||Number of visits with at least one (M) Error event tracked.|
|Total Errors||Total number of (M) Error events tracked in visits in the segment.|
|Visits with Actions||Number of visits with at least one (M) Action event tracked.|
|Total Actions||Total number of (M) Action events tracked in visits in the segment.|
|Visits with Revenue||Number of visits in which revenue was tracked. For e-commerce websites, that number could be considered to be visits with conversion.|
|Total Revenue||Sum of all revenue values in the segment.|
|Avg Revenue||Average revenue value calculated as: Total Revenue/Visits with Revenue|
|Total Cost||Sum of all cost values in the segment|
|Avg Cost||average cost value calculated as: Total Cost/Visits with Cost|
|Total Profit||difference between Total Revenue and Total Cost|
|Avg Profit per Visit||average profit calculated as Total Profit/Visits in Segment|
Tracking of Financial Metrics
The financial metrics are based on two (A) attributes: revenue and cost. These events are not being automatically tracked by UseItBetter which means that in order to use financial metrics you will need to set up tracking of those attributes.
- (A) revenue – should contain transacted value during a visit.
- (A) cost – should contain any costs related to a visit, which usually are: costs of acquisition, costs of contact with support, affiliate charges and so on.
Values of the two attributes should be provided as numbers (10, 10.5), without spaces, commas or any currency codes. Therefore, values like 10,5 or EUR 10 would be invalid.
Metrics summary contains a combination of Engagement and Financial metrics described above.
Metrics Over Time
Below the table with the metrics is a chart showing how selected metric changed over time in each of the segments.
Each line on the chart indicates a segment. The (1) grey thick line indicates the selected segment and the colours of (2) lines for subsegments match the colours of segments displayed in the metrics table above the chart. By default, the chart shows (3) number of visits in the segments. Click < (left) or > (right) arrows by the chart title to change the metric displayed on the chart.
Just like any other report, the Segments Report shows data based on the time range defined above the segments tree. (4) The period (month, week, day or hour) is automatically selected based on that time range. To change the period, adjust the time range.
Visits in the Subsegments
This section of the report allows to quickly compare sizes of corresponding subsegments in their parent segments. You could use it to:
- compare conversion in the two versions of your A/B test.
- compare impact of different behaviours on your goals
- compare usage of product filters in visits to different categories
The first column of the table contains a list of unique filtering rules or, if added, labels from the branches which are grandchildren of the selected segment. The other columns contain number of visits in each of the segments and their shares relative to their parents.
Grouping of Segments
The grouping by labels supersedes grouping by filtering rules making it possible to group subsegments that are based on different filtering rules.
For example, you could have two different landing pages. Each of those landing pages would have the same goal – to make users register for an acount but would have very different URLs of pages displayed to user after a successful registration.
If you would like to compare the conversion – the percentage of visits in which user registered – for those two landing page and build the segments tree pictured on the left side (1), the conversion rate would be displayed in two separate rows (2).
By adding the same label “Successfully Registered” to the different filtering rules, as pictured on the right side (3), you would group them together for higher readability of your report (4).