Daily User Interaction Metrics by Media Product Type
Daily User Interaction Metrics by Media Product Type can be used to request and retrieve the total number of post interactions, story interactions, reels interactions, video interactions and live video interactions, including any interactions on boosted content; aggregated by day and broken down based on the media product type namely: Ad, Feed, Reels, Story.
Read more about this end-point here
When running this pipeline for the first time, it will fetch data for 365 days. |
Configuring the Credentials
Select the account credentials which have access to relevant Instagram Social data from the dropdown menu & Click Next
Data Pipelines Details
- Data Pipeline
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Select Daily User Interaction Metrics by Media Product Type from the dropdown
- Account
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Select the name of one or more accounts for which you would like to retrieve the data.
Setting Parameters
Parameter | Description | Values |
---|---|---|
Insert Mode |
Required Specifies the manner in which data will get updated in the data warehouse : UPSERT will insert only new records or records with changes, APPEND will insert all fetched data at the end, REPLACE will drop the existing table and recreate a fresh one on each run.Recommended to use "Upsert" option unless there is a specific requirement. |
{Upsert, Append, Replace} Default Value: UPSERT |
Datapipeline Scheduling
Scheduling specifies the frequency with which data will get updated in the data warehouse. You can choose between Manual Run, Normal Scheduling or Advance Scheduling.
- Manual Run
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If scheduling is not required, you can use the toggle to run the pipeline manually.
- Normal Scheduling
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Use the dropdown to select an interval-based hourly, monthly, weekly, or daily frequency.
- Advance Scheduling
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Set schedules fine-grained at the level of Months, Days, Hours, and Minutes.
Detailed explanation on scheduling of pipelines can be found here
Dataset & Name
- Dataset Name
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Key in the Dataset Name(also serves as the table name in your data warehouse).Keep in mind, that the name should be unique across the account and the data source. Special characters (except underscore _) and blank spaces are not allowed. It is best to follow a consistent naming scheme for future search to locate the tables.
- Dataset Description
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Enter a short description (optional) describing the dataset being fetched by this particular pipeline.
- Notifications
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Choose the events for which you’d like to be notified: whether "ERROR ONLY" or "ERROR AND SUCCESS".
Once you have finished click on Finish to save it. Read more about naming and saving your pipelines including the option to save them as templates here
Still have Questions?
We’ll be happy to help you with any questions you might have! Send us an email at info@datachannel.co.
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