SpringServe: Setup guide#
This guide explains how to collect data from SpringServe.
Introduction#
SpringServe is a video and connected TV (CTV) ad serving platform. The SpringServe connector ingests performance reports from SpringServe, enabling automated data fetches for campaign monitoring and optimization alongside your other data sources.
Limitations#
Collecting data from SpringServe comes with the following limitations:
Data at Hour granularity is only available for the last 48 hours. To collect data further back, use Day or Cumulative granularity instead.
Each report is limited to 500,000 rows. If your selected date range, dimensions, and metrics produce more rows than this, narrow your selection.
Prerequisites#
Before you start collecting data from SpringServe, perform all of the following actions:
Ensure you have a SpringServe user account with access to the data you want to fetch.
Creating a datastream to collect data from SpringServe#
The basics of creating a datastream to collect data from any data source are explained in our guide to Collecting data in Adverity. This guide contains information about the specific steps to create a datastream to fetch data from SpringServe.
Configuration: Choose the data you want to collect from SpringServe#
To choose what data to collect and customize the SpringServe datastream configuration, follow these steps:
(Optional) Rename your datastream.
In Dimensions, select the dimensions to include in your data extract. You must select at least one dimension.
Note
If you select an ID dimension, such as Campaign ID, Adverity automatically includes the matching name field, such as Campaign Name, in your data extract.
In Metrics, select the metrics to include in your data extract. You must select at least one metric.
In Interval, select the time granularity for the report: Hour, Day (default), or Cumulative.
In Timezone, select the timezone to use for the collected data. The default is UTC.
As a result, Adverity fetches data from SpringServe according to the configuration you set.
What’s next?#
Apply Data Mapping to your collected data to harmonize data collected from different sources in Adverity.
Transform your data to meet your needs by creating and applying transformations to your datastream.
Load your data into a warehouse to continue working with your data in Adverity.
Load your data into an external destination of your choice.