Please reach out to your Customer Success Manager to get access to this feature if you don't have it accessible right now.

Export raw (CSV or JSON) data from Bloomreach Engagement in a custom-defined structure to any file storage via any of the existing file storage integrations (SFTP, Google Cloud Storage, Amazon S3 or Azure Storage). You can connect to tools/vendors that require bulk data processing (e.g. (email) campaign platforms, CRMs, data warehouses, data lakes etc.).

Watch this short introductory video about this feature:

What does the feature provide

Full flexibility in defining the export output. Specifically, the user can choose:

1. Selecting data structure (customers, events).
2. Filtering customer profiles to be considered in the export.
3. Selecting which attributes to export.
4. Mapping the column names.
5. Selecting format (CSV, JSON, JSON lines).
6. Configuring delimiter (for CSV) and text encoding.
7. Selecting target storage (SFTP, GCS, S3, Azure Blob Storage).
8. Selecting file naming (user-defined time-based naming).

Two types of data:

• Static data, i.e. raw data (customer attributes, event attributes) that were tracked e.g. email, purchase_item
• Dynamic data, i.e. enriched data (customer segmentation, event segmentation, aggregates, running aggregate, expressions) that were calculated e.g. customer total spent

Three ways to trigger exports:

• Manually
• Scheduled
• Requested via API (for manually triggered imports)

📘

Roles and Permissions

In order to have this feature accessible, you need to have additional permission by the Exports Module Admin & Personal Data Viewer (Project Admin is not sufficient).

Use case examples:

• Load partial data into a unified data warehouse / data lake for the purpose of further analysis.
• Campaign and consent data sync.
• Enrichment of data that is already tracked in the platform.
• Triggering campaigns on offline channels, e.g. call centre or store.

What events will be exported?

When defining the time period from which events should be exported, events are exported based on the timestamp attribute, not by the time when event was tracked (these can be two different timestamps, e.g. when a purchase is tracked later with a timestamp in the past).

During export, a temporary file is created first and only once the export is finished, the temporary file is renamed to the final filename.

Customer teams should ensure proper permissions to enable writing files to target storage when configuring authorisation for target storage (SFTP, GCS, S3, Azure).

Step-by-Step Guide:

You can find this feature by clicking through data and assets -> exports -> + new export.

Data source - choose customers or single event type that you want to export

Based on that click on +add filter condition and add customer or event filter to specify what data should be exported

You can apply any filters available to you. If you struggle with this step, read Filtering Data

Data structure - select and name fields in the export file

Name your export and scroll right to see all the details Bloomreach Engagement provides about your customers based on the information that we collect.

If you have a specific file schema, you can order the columns in the export by reordering the attributes in data manager, so it fits your needs. For events export, timestamp will always be the last column.

Be careful when adding and renaming columns, as having two identical column names will result in an error.

🚧

Privacy notice

Some exports will contain personally identifying information (PII). Ensure that export is secured to reduce the risk of a data breach

Format & target - select filename, format, destination & security options

Format

Format specifies how will your final project look like based on your personal preferences. If you select CSV format, determine your Delimiter (which specifies the boundary between separate values) and Encoding.

JSON and JSON LINES files have a predefined Delimiter, hence simply select your Encoding. The difference between them is the way your exported data are written. While JSON writes data in comma-separated values [{"a":1},{"a":2}...], JSON LINES uses a new line for each value
{"a":1}
{"a":2}

📘

Opening a CSV file in MS Excel

To correctly configure and open a CSV file as an MS Excel spreadsheet, follow this external guide. To quickly preview CSV files, we recommend using Notepad++ on Windows, or Sublime on Mac.

🚧

When naming a file, you need to include the file extension. For example, instead of "filename", you should name it "filename.csv".

Target

In the section Target select the place to which you export your data.
Click on the file storage and select an available integration (SFTP, Google Cloud Storage, Azure Storage)
Choose Path to parent directory to set where the Export will be located.
Select File name. Bloomreach Engagement allows dynamic naming. Adding %r after the name of the file will show its timestamp (eg: filename_1589460477.9546165). All other dynamic namings can be found here.

🚧

Folders are expected to exist prior to running an export because Bloomreach Engagement will not create them (Bloomreach Engagement only creates files).

🚧

With custom software, you can relay virtually any data source over an SFTP connection, but remember that Bloomreach does not support the particular data source.

Schedule execution - one-time or repeated action

Now you should be ready to finish exporting your project.

🚧

Please note that the exported data is not modified in any way by the Bloomreach Engagement platform and contains the data in the form sent to Bloomreach Engagement. Therefore, we recommend that you check the data before final processing and validate the format of individual fields.

Viewing and monitoring export runs

In the main Exports screen you can see all of your running, scheduled and finished exports.

Click on a selected export to view all its individual runs and additional information:

• Scheduled time
• Run duration
• File exported (Name of the file)
• Status
• Rows exported / scheduled

Limitations

Bear in mind the following limitations:

• One running export for one definition
  • In Bloomreach, you can set up multiple scheduled exports. But there can be only one running within the export. Imagine you have a Scheduled export called “All customers.” This export should run every hour - 9 am, 10 am etc. But the run takes 1.5 hours, so the run starting at 9 am will run until 10:30 am. Then, the run scheduled for 10 am will begin at 10:30 once the previous one is finished.
• Four different exports running at the same time
  • In Bloomreach, you can set up multiple scheduled exports. But there can be only four different scheduled exports running simultaneously.
• Azure supports exporting up to 48.8GB of data

🚧

Attempting to export all data from Bloomreach Engagement is not possible, as it could easily hit one of the limitations listed above. We recommend exploring other options, such as Bloomreach Engagement BigQuery when attempting to export all data from the platform.