Path

The new Path behavioral report enabled you to analyze your user’s top paths. Choose between path by collection of events (contains) or steps (starts with…), customize advanced settings, and display the results using the sunburst visualization or in a table.

Path analysis can be used in two ways – sequential path, or non-sequential path:

  • Sequential Path: Define a sequence of events you want each path to consist of.  Use any of the following options:
    • Starts with: The first event in the path. 
    • Followed by: Any events succeeding the first event. Additional events could have been between the first event and this one. You can add additional steps up to a total of 10.
    • Followed directly by: Any events succeeding the first event, with no events in between. You can add additional steps up to a total of 10.
    • Ends with: The last event in the path.
  • Non-Sequential Path: Any paths that included a list of events. Choose between path that contain any of the events in the list (OR logical operator) and all of the events in the list (AND logical operator) .

Show top n paths allows you to limit the result set to anything between 1 and 50 rows.

Advanced options allow you to use advanced functions of the Path Analysis:

  • Path completed in: 
    • Single session: Only show the events performed within the same session. I.e. if the session was broken before the user completed the defined path he will not be included in the analysis.
    • User lifetime (not yet available): Combine all of the user sessions to a continuous string of events. Would include users who completed the defined path even if it was done over multiple sessions within the report’s specified date range.
  • Events to show:
    • All events in path: The default option – will show the full list of events the users performed in the path.
    • First events in path (not yet available): Only show the first X events in the path.
    • Last events in path (not yet available): Only show the last X events in the path.
    • Only these events: Filter out any events not specified here – in case you are only interested in specific events and want to ignore the rest.
    • First sequence of these events: Only show the first occurrence of a specific sequence of events. Define the sequence by selecting the events in the order you expect them to appear in. Additional events that occurred in between these events will also be shown, but events preceding or succeeding it will not. If the sequence repeats itself more than once during a path, only the first occurrence will be shown.
  • Show recurring events:
    • Every time: The default option – will show the full list of events the users performed in the path.
    • Once: Identical events repeated consequentially (with no other events in between) will be filtered and only shown as one event. For example, the sequence: “click, click, click” will be shown once: “click”.

Sunburst Visualization

The SunBurst visualization is designed for and particularly useful for analyzing paths, though it also supports other distribution queries.

The required result for SunBurst visualization is two columns:

  • string / comma+space delimited list of strings
  • number

In the basic configuration (one string per row) the SunBurst visualization is a standard donut chart, showing the distribution of each item in the first column out of the total of the second column (like pie chart).

Example – Events Distribution (Donut)

Query:

select event_name, count(*) as count
from cooladata
where date_range(context)
	and slicers(context) 
group by event_name
order by count desc
limit 100

events

 

However, it can do much more!

For path analysis, use the path_to_string() function. It returns the first column as a list of string, comma+space delimited. The SunBurst visualization treats every string in the list as the next step in the session’s path, and displays it as a following (outer) ring.

Use the path_count() function to limit the number of rings in the visualization (see example below).

Hovering or clicking (to pin the selection) over any part of the visualization will show the items in that section as a sequence below the chart (above the legend), and the share of that section out of the total as a percentage. Point to the center of the circle to show the text explanation of what is shown.

Example – Path Distribution

Query:

select path_to_string(path) as path, count(*) as count
from cooladata
where date_range(context)
	and slicers(context)
	and path_count()<5
cluster path by session
group by path
order by count desc
limit 100

path

The legend can be turned on/off.

Exporting the results will provide the same output as the standard table view output (CSV).

 

Sankey Visualization

Sankey visualization is a flow diagram in which the width of the arrows is shown proportionally to the flow quantity.

Like Sunburst, the required result for Sankey visualization is two columns:

  • string / comma+space delimited list of strings
  • number

Sankey displays the users’ journey in a flatten way than until his exit point.

It’s available in CQL report and in Path report.  

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Cohort

Cohort

A Cohort is typically defined as a group of people who share a common characteristic over a certain period of time.

A Cohort report breaks down user data into groups that share common characteristics or actions within a defined time frame. For example, to see how many users registered to your website in the last few weeks broken down by week and then see how many of them returned.

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This example report shows a row (cohort) for each week indicating users who were active (meaning performed any event) in the website. Each column represents a bucket of users –

  • The leftmost column named Users indicates the total number of users who were active during the first week.
  • Column 0 represents the number of users (of those that were active in the first week) that came back and were active in the second week. The second week starts from the date shown in the second row on the left (meaning 2016-05-19).
  • Column 1 represents the number of users that were active in the second week (as represented in Column 1) that came back and were active in the third week and so on. The second week starts from the date shown in the third row on the left (meaning 2016-05-26).

This report can also be displayed as percentages, by turning on the Percentage slider 6-35.

The example above shows that as time goes by, fewer and fewer users are coming to the website (to begin with), as shown in the lower rows of the Users column for each week. The report also shows that as time goes by, the chance of these users returning increases, as shown in the buckets (columns) of the lower rows.

Note: Any event can be included in a Cohort report. However, if you include an event for which the Include in Path option is not selected, then a Where condition must be defined for this event name with an exists operator; otherwise, empty results may be returned.

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To create a new Cohort report:

  1. In the CoolaData Administrator console, click Reports reports.
    – OR –

    In the Dashboard window, click the Add Reports 6-15 button. A list of reports is then displayed.

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  1. Click the + button to add a new report. A dropdown menu of report types is displayed. Select Cohort. The following displays –

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  1. In the Users who field, select the first thing to happen –
    • Did anything – Users who performed any event.
    • Did – Select a specific event from the dropdown menu.
  1. In the And then field, select the next thing to happen –
    • Did anything – Users who performed any event.
    • Did Select a specific event from the dropdown menu.
    • Did not do Select an event that the user did not do from the dropdown menu. This means that the user did nothing more or performed any event excluding this one.
    • Did nothing – No events occurred within the date range of the report.
  1. In the Group cohorts by field, select –
    • Time – Define the timeframe of the cohorts. For example, 2 Days.

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    • Limit – If Group cohorts by equals Time, then the Limit specifies the maximum number cohorts that are displayed, even if more can fit into the time range of the report. The timespan of each cohort is determined by the Cohort every field (described above).
    • Count Users –
        • In each cohort – Each user event is counted in each cohort that it appears.
        • Once – Each user event is counted once – in the first event in which it occurs within the filters and time range of the report.
    • Property – Select a property by which to group the report.

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  1. In the Measure field, select the thing to be counted and displayed in the report –
    • Select a function, such as COUNT, MIN, MAX, SUM, AVG and so on.

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    • Select the thing to be measured, such as Users or a property. When Users is selected, only the COUNT function is available.

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If you selected Users, then an additional field is displayed –

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In each bucket – Counts each user each time that user’s event appears in a bucket (for example each week or day).

Once – Counts each user once, the first time that user’s event appears in a bucket.

Recurring – Only counts users that were active in consecutive buckets, meaning if the user is not active in a specific bucket, then that user is not counted in that bucket and in subsequent buckets even if they are active.

For example, if a user performed an event in bucket week 0, 1 and 3, then –

      • If In each bucket is selected, then that user is counted in weeks 0, 1 and 3.
      • If Once is selected, then that user is counted in week 0.
      • If recurring is selected, then that user is counted in weeks 0 and 1.
  1. In the Bucket every field, define the timespan of each bucket. Limit – Specifies the maximum number buckets that are displayed, even if more can fit into the time range of the report.

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  1. Define the report’s date range and define the report’s filter if you would like it to be different than the dashboard in which it appears.
  2. In the Description field, fill in any description of the report.

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  1. Click Apply and then click the Compute button to display an example of the results of this query, as shown below – !!!!!!!!!!!!!!!!

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  1. Select one of the graphic representation icons. !!!!!!!!!!!!!!!

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As you select various visualization options, the chart appears at the bottom of the window accordingly.

    • Table
    • Single number visualization
    • Line chart
    • Area chart
    • Bar chart
    • Column chart
    • Pie chart
    • Geo chart
    • Pivot table

Set the visualization options and sliders that appear underneath according to your preference –

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    • Theme – Selects the color to be applied to the report.
    • Show Bucket 0 – Percentage –Hides the first (leftmost) column, which represents bucket 0.
    • Percentage – Displays percentages in the report instead of quantities.
    • Running Total – Displays a running total that accumulates the columns. This option is only relevant when the Once option is selected in the Measure field.
    • Captions – Enables you to configure various titles that appear in the report.
  1. To publish this report –
    • Click the three dots in the top-right corner of the page to display a toolbar.

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    • Select the Publish option.

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    • Fill out the window to specify the recipients to receive this report, the frequency and the time of day.The new report now appears in the Dashboard and is sent to the specified recipients daily.
  1. Click Save.

 

Cohort analysis breaks data down into groups which usually share common characteristics or actions within a defined time frame. Cohort analysis helps identify patterns in the life cycle of customers, adapt, and tailor the service to specific cohorts. A group of people who share a common characteristic or actions within a defined period form a cohort, represented by a row in the returned result set.

The date range selected in the report will specify at which date the first cohort begins.

Cohort

To define a cohort:

  1. Choose the start and end actions: these can be anything, nothing, or specific events.
  2. Add any conditions to the start and end actions: click the arrow icon to expand the step conditions.
  3. Group cohort by time or property: If grouping by time, users can be counted once or again in every cohort.
  4. Choose what to measure: Other than counting users, you can also measure the value of any other property over time for these users. If counting users they can be counted in one of 3 ways:
    • Once: only counts the user once on the first occurrence of the event throughout his life cycle
    • In each bucket: the user is counted each time he performed the event
    • Recurring: each cohort user is counted only if the user’s activity occurred consecutively in each bucket throughout the duration of the cohort.
  5. Choose the bucket duration: buckets are the collections of users by time when the second step was performed, measured from the time the first step was performed. You can choose to group by any time range.
  6. Define limits for cohorts and buckets: if cohorting by time you can choose how many cohorts to include. If cohorting by property, the cohort will show all available values for this property.

 

Reverse Cohort

It is also possible to analyze a sequence of two events in the reverse order, i.e. what happened prior to a certain event.

The same definitions apply, with the change of the first step happening after the second step.

Reverse Cohort

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Ranking

The Ranking report is used to identify the best or worst performing items within a dimension, such as: channels, regions, affiliates, products, and so on, based on any of the measurements that Cooladata records. For example: the top ten countries with the most users, or the five campaigns with the least total orders.

The ranking settings include the following options:

  • Ranking criteria: top or bottom X items
  • Dimension to be ranked: e.g., city, device, etc.
  • Function and measure to rank by: e.g., count distinct users, sum of purchases, etc.
  • Sort order: ascending (ASC) or descending (DESC).

You can select to display the ranking report using any of the visualizations.

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Drillthrough Reports

Drillthrough Reports enable you to drill through (zoom in) to a section of a report by clicking it, and opening another preconfigured report, filtered to that category’s data.

For example, define a report broken down by days, and another report broken down by hours. By linking the first to the latter, you can click any date in the first report chart to zoom in to that day’s hourly breakdown. The same would work for any breakdown, not just by time, considering the linked report supports filtering by the selected property (see more below).

Notes:

  • Can link from the following visualizations: Table, Line, Area, Bar, Column, Combo, Pie, Geo.
  • Cannot use linked report in Embedded Reports

 

Define Drillthrough Reports

  1. In the report editing page, from Report Options  choose Drillthrough Reports:
  2. In the opened window, choose up to 5 reports (from the same project) that will be linked to from this report. An indication will be added to the report page that Drillthrough Reports are in use – “Drillthrough” label next to report options.
  3. Make sure the linked reports you choose support filtering by the X axis dimension, i.e. include this property in the data.
    For example, if you link a report running over Cooladata to a report running on an Aggregation Table, the Aggregation Table must include the property used as the first report’s X axis.

 

Drillthrough from Chart

Once a drillthrough has been defined, click any point in the chart to select the x axis value the linked report will be filtered by.

  1. Hover over a point in the chart. You will see an indication in the tooltip: “Click to drill through“.
  2. Click the point to choose from a list of linked reports.
  3. Once a report has been selected it will be displayed instead of the current report (i.e. in the same preview area).
    The new report will be filtered by the data point you clicked.
    For example, if you chose to drill through on a specific date, say January 1st, 2017, the new report will only show data for January 1st, 2017.
  4. The report header will show a Back icon to return to the last report shown.

 

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CQL

CQL (CoolaSQL) is the query language provided by CoolaData for answering complex behavioral questions using a simple language. The CQL report enables the analyst to type free syntax to generate any query. Using the CQL report you can query any data source in CoolaData – internal, external, and integrations. CQL enriches the basic SQL syntax, and has been specifically designed so that even a beginner SQL user can utilize its powerful clauses. CQL supports multiple powerful proprietary clauses, functions, and special fields, which allow easy analysis of typical behavioral patterns such as path analysis, cohort analysis and funnel analysis.

To create a new CQL report:

  1. In the CoolaData Administrator console, click Reports reports or in the Dashboard, click the Add Reports 6-15 button.
  2. Select the CQL report.
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  3. Type in the name of the report in the top-left corner of the page.
  4. Enter a query written in CQL into the center of the page. The default contents of the CQL report is the basic general SQL layout, as follows:
    CQL default

    • select — add any properties and functions here
    • from cooladata — only replace this to query external data sources or integration, otherwise, required.
    • where date_range(context) — allows the report to interact with the date range picker in both the report view (above) and inside any dashboard using it. See more in Date and Time Functions.
    • and slicers(context) — allows the report to interact with the filters in both the report view (above) and inside any dashboard using it.
    • limit 100 — limits the number of results returned. This is recommended to be included in any query, to save processing time and return results faster.

    Any of the text above is fully editable. Add GROUP BY, ORDER BY, HAVING, JOIN, behavioral functions, or any other common SQL clauses to further elaborate the report.

  5. Define the report’s date range and define the report’s filter if you would like it to be different than the dashboard in which it appears.
  6. Click the Compute button. For example, the following query counts the number of events received by CoolaData today.
    Select event_name, count(*) as cnt
    
    from cooladata
    
    where data_range(today)
    
    and filters(context)
    
    group by event_name
    
    order by cnt desc

    Events are available in the CoolaData database within an hour or two of being received. Before then, the following message may be displayed when you click Compute: No data in the selected date range.

  7. Beneath the syntax box you will see a validation check; when red – an error will be displayed specifying any error found in the query. When green, the query is valid and can be computed. A valid query has no errors and will run in CoolaData. Verify whether the query is valid by looking to see the message Query is valid, as shown below:
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  8. Click “Compute” to see the results, and choose any visualization you wish.
    basic cql
  9.  

    Publish the report:

    • Click the three dots in the top-right corner of the page to display a toolbar and select the Publish option
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    • Fill out the window to specify the recipients to receive this report, the frequency and the time of day.

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