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    Adroll Walkthrough
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    Contents

    Adroll Walkthrough

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    Article Summary

    Prerequisites

    • Adroll Connection

    Adroll reports

    Most of the reports in Adroll depend on time. The reports Advertisers and Audience Segments do not.

    Here are the options you can input in the time-dependent reports:

    Time-Dependent Reports

    The time-dependent report includes Widgets, Sub Id Stats, etc.

    Select a time period:

    Time-dependent reports support two kinds of time-period:

    1. Date Range -
      • Pulls data in the date range between the start and end date provided, including the end date.
      • You must select a start date.
      • Leaving the end date empty will pull data according to the current time of the river's run.
      • Select a timezone offset to send dates considering the offset.
      • Use the "Last Days Back For Each Run" to expend the start date and pull data a given number of days back before the chosen start date.

    In the example above the river will run with a date range between "01/03/2020" and "30/03/2020".

    1. Predefined date - A date range defined by Rivery:
      • Day - Yesterday.
      • Week (From Monday to Sunday) - Week to date, Previous week, Previous week to date.
      • Month - Month to date, Previous month, Previous month to date.
      • Year - Year to date.

    Flattening Adroll Output in Snowflake

    In the Attribution Campaigns report, the field date has JSON repeated strings structure in its output. The following in an example query in Snowflake SQL to flatten the results. This can be done using a Logic River.

    select value:assist_revenue::integer as assist_revenue,
value:assists::integer as assists,
value:click_revenue::integer as click_revenue ,
value:click_throughs::integer as click_throughs,
value:date::string as date,
value:precise_assists:: integer as precise_assists,
value:precise_click_throughs: integer as precise_click_throughs,
value:precise_view_throughs:: integer as precise_view_throughs,
value:view_revenue:: float as view_revenue,
value:view_throughs::integer
from "SCHEMA1"."PUBLIC"."ADROLL_JSON_DATA",lateral flatten(input => parse_json(date))

    Example results of the above query:


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