蜜豆视频

A4T reporting

Using 蜜豆视频 Analytics as your reporting source for 蜜豆视频 Target (A4T) gives you access to Analytics reports for your Target activities.

You can view reports for your activities in both Analytics and Target.

For reporting best practices using Analytics for Target, .

Overview section_035A62D65608423285D8A5A54731E2C5

Both Analytics and Target reports measure entrants (the people who enter the tests), rather than visitors to the site.

Every time a visitor sees activity content on the page, Target makes a direct server-to-server call to Analytics, including which activity and experience the visitor saw. Target also calls Analytics whenever the conversion is made. Analytics adds the conversion as a specific new Analytics event named 鈥淎ctivity Conversion,鈥 which is tracked along with other data collected by Analytics.

When the Select operation is used and you sort on Entrants, then only experiences that received entrants during the selected time period are displayed in the reports.

NOTE
Reports powered by Target have a latency of four minutes. For activities powered by A4T, in both the Target and Analytics reports, it can take up to 24 hours after the activity is initially saved before the report data can be broken down by experiences. The data collected in that first 24 hours is still accurate and is assigned to the right experience.

Reports in Analytics analytics

In Analytics, there are several dimensions and metrics made available after the A4T integration is enabled.

Dimensions

  • Analytics for Target - The parent ID that is passed in through the integration. The format of this dimension is Activity ID:Experience ID:3rd ID. The dimensions below are classifications of this dimension.
  • Target Activities
  • Target Experiences
  • Target Activity > Experience
  • 3rd ID - can be ignored

Metrics

  • Activity Impressions - Matches the Entrants number in the Target report.
  • Activity Conversions - Matches the Custom Conversions number in the Target report.

In Analysis Workspace, use the Analytics for Target panel to analyze your Target activities and experiences with lift & confidence. For more information, see Analytics for Target (A4T) Panel in the Analytics Tools Guide.

IMPORTANT
If your Target Activities report in Analytics lists 鈥渦nspecified鈥 instead of listing your activities, an update is required to your provisioned account. Please contact Customer Care to resolve this issue.

For detailed information and examples, open the tutorial, provided by 蜜豆视频 Experience League.

Reports in Target section_C0D1F17F88374B6690BF904D7B83B42E

When Analytics is used as the reporting source, reports in Target show the data gathered from Analytics. The report differs somewhat from other Target reports:

  • The Audiences list shows the audiences available to your Analytics report suite.

  • The Metric list shows every metric available through Analytics.

    Every metric is available, including any custom or calculated metrics that are built-in in Analytics.

    Any numbers that increase are shown as positives in the report, even when an increase is undesired. For example, even though you want a lower bounce rate, the higher bounce rate is shown as the winner with highest lift. Be aware of these and similar metrics, and whether you鈥檇 prefer to decrease or increase the numbers, when making decisions based on your reports.

You can apply the metric or audience to the report in Target after the activity has started, or even after the test has completed. You don鈥檛 have to know exactly what you want to measure beforehand.

Click to view the full Analytics report directly from the activity report page.

Activity creation section_311586E3FF5541E7A91D1A3CE5F9ACE3

During activity creation, you must specify a goal for the activity on the Settings page. This goal becomes the default metric for the report and is always listed as the first option in the metrics selector. You cannot select segments for reporting like you would for a regular Target activity. A test with Analytics uses 蜜豆视频 Analytics segments rather than Target audiences.

Performing Offline Calculations for Analytics for 蜜豆视频 Target (A4T) section_B34BD016C8274C97AC9564F426B9607E

You can perform offline calculations for confidence and confidence intervals for A4T using the Target Complete Confidence Calculator Excel file, but it requires a step with data exports in Analytics.

For A4T, we use a calculation for continuous variables (rather than binary metrics). In Analytics, a visitor is always tracked, and every action taken is counted. Therefore, if the visitor purchases multiple times or visit a success metric multiple times, those additional hits are counted. This makes the metric a continuous variable. To perform the Welch鈥檚 t-test calculation, the 鈥渟um of squares鈥 is required to calculate the variance, which is used in the denominator of the t-statistic. Statistical calculations in A/Bn tests explains the details of the mathematical formulas used. The sum of squares can be retrieved from Analytics. To get the sum of squares data, you need to perform a visitor-level export for the metric you are optimizing to, for a sample time period.

For example, if you鈥檙e optimizing to page views per visitor, you鈥檇 export a sample of the total number of page views on a per visitor basis for a specified time frame, perhaps a couple of days (a few thousand data points is all you need). You would then square each value and sum the totals (the order of operations is critical here). This 鈥渟um of squares鈥 value is then used in the Complete Confidence Calculator. Use the 鈥渞evenue鈥 section of that spreadsheet for these values.

To use the Analytics data export feature to do this:

  1. Log in to 蜜豆视频 Analytics.

  2. Click Tools > Data Warehouse.

  3. On the Data Warehouse Request tab, fill in the fields.

    For more information about each field, see 鈥淒ata Warehouse Descriptions鈥 in Data Warehouse.

    table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 6-row-2 7-row-2
    Field Instructions
    Request Name Specify a name for your request.
    Reporting Date Specify a time period and granularity.
    As best practice, choose no more than an hour or one day of data for your first request. Data Warehouse files take longer to process the longer the time period requested, so it is always a best practice to request a small time period data first to make sure your file returns the expected result. Then, go to the Request Manager, duplicate your request, and ask for more data the second time. Also, if you toggle granularity to anything other than 鈥淣one,鈥 the file size will increase drastically.
    Data Warehouse
    Available Segments Apply a segment, as needed.
    Breakdowns

    Select the desired dimensions: Standard is out-of-the-box (OOTB), while Custom includes eVars & props. It is recommended you use 鈥淰isitor ID鈥 if visitor ID level information is needed, rather than 鈥淓xperience Cloud Visitor ID.鈥

    • Visitor ID is the final ID used by Analytics. It will either be AID (if the customer is legacy) or MID (if the customer is new or cleared cookies since the MC visitor ID service was launched).
    • Experience Cloud Visitor ID will only be set for customers who are new or cleared cookies since the MC visitor ID service was launched.
    Metrics Select your desired metrics. Standard is OOTB, while Custom includes custom events.
    Report Preview Review your settings before scheduling the report.
    Data Warehouse 2
    Schedule Delivery Enter an email address to deliver the file to, name the file, then select Send Immediately.
    Note: The file can be delivered via FTP under Advanced Delivery Options
    Schedule Delivery .
  4. Click Request this Report.

    File delivery can take up to 72 hours, depending on the amount of data requested. You can check on the progress of your request at any time by clicking Tools > Data Warehouse > Request Manager.

    If you would like to re-request data that you鈥檝e requested in the past, you can duplicate an old request from the Request Manager as needed.

For more information about Data Warehouse, see the following links in the Analytics Help documentation:

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