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Special configuration steps in the datasource wizard

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Overview

Some datasource types require additional configuration steps beyond the standard source and field mapping setup. This page documents these special configurations.

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Website Events (Reelevant Analytics)

The website events integration tracks user behavior on your website and stores it in Reelevant.

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Setup

  1. In the configuration wizard, the Configure Reelevant Script step provides a JavaScript snippet.
  2. Add the snippet to your website.
  3. Perform a few navigations on your website to verify the integration.
  4. Click Validate to confirm.

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Google Tag Manager

GTM integration lets you send website events through your existing tag management setup.

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Setup

The Setup Google Tag Manager step provides:
  • A datasource id to use in your GTM tag configuration.
  • A company id to use in your GTM tag configuration.
After configuring the tag in GTM, navigate your website and click Validate.

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API Key Integrations

Integrations like Partoo require an API key:
  1. The Configure an API Key step provides instructions specific to the integration.
  2. Enter your API key.
  3. Click Validate to verify the connection.

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Best Products

The Best Products datasource computes which products perform best based on tracking events:
1

Configure product datasource

Select the product datasource that contains your product catalog.
2

Configure tracking datasource

Select the analytics datasource that contains tracking events.
3

Configure queries

Set the tracking event type and time range for the computation:
4

Define Best Product field

Select the field in which you want to add the computed count.

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Merge Aggregation

A merge aggregation enriches the rows of one Datasource with fields taken from another Datasource, matched on a shared identifier. You configure it as an aggregation on the Datasource you want to enrich — you do not build or maintain a separate combined Datasource, and you query the enriched Datasource directly. The Datasource you enrich (the main Datasource) keeps all of its rows and its own identifier. For each row, the merge aggregation looks up the matching record in the dependency Datasource and copies the selected fields onto that row. Rows with no match keep the merged fields empty.
A merge aggregation adds fields from the dependency Datasource into the main Datasource. It never removes or replaces the main Datasource’s own rows.
1

Select the main datasource

The Datasource whose rows you want to enrich. Its row set and identifier are preserved.
2

Select the dependency datasource

The Datasource to pull additional fields from. Its fields become aggregation fields on the main Datasource, and you choose which to keep in the field mapping.
3

Map the shared key

Choose the field on the main Datasource and the matching field on the dependency Datasource. A record from the dependency is merged when its key equals the main Datasource’s key.

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Worked example

A product catalogue Datasource (the main Datasource) holds a product id and name. A pricing Datasource (the dependency) holds an item_id and a value. Mapping id to item_id merges the pricing fields onto each product row: The catalogue keeps all three products. A83 has no matching price, so its merged fields stay empty.
The merge re-runs whenever the main or dependency Datasource refreshes, so the enriched fields stay up to date. A dependency Datasource cannot be deleted while a merge aggregation still depends on it.

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Via the API

You can add the merge aggregation to an existing Datasource directly, without creating a separate combined Datasource. <datasource-id> is the main Datasource (the product catalogue) throughout. First declare the merged field on the Datasource with the configure_fields step. The field pulled from the dependency carries "source": "aggregation", while the Datasource’s own fields keep "source": "user":
Then attach the merge aggregation with the patch step. datasourceId inside the aggregation is the dependency Datasource (the pricing Datasource):
  • Each merged field is declared with "source": "aggregation" in configure_fields, and its name listed in the patch step’s fieldNames. Its rulesPerSources path reads the value from the matched dependency record.
  • query maps the shared key: the dependency field (item_id) is matched against the main Datasource’s field, referenced with { "type": "path", "value": "id" }.