I need more features, should I create an enrichment table?

I need more features, should I create an enrichment table?

Probably not.

Only create an enrichment table when the activity needs many features that CANNOT be associated with another activity



Why should enrichment tables be used sparingly?

Enrichment tables should be used sparingly because they can slow down your queries when you need to use them in a dataset.



When do you need an enrichment table?

If you are creating an activity and find yourself wanting more features, first consider if the features you want can be added to a related activity instead. It's very easy to borrow features(#how-to-borrow-features-from-other-activities-when-building-a-dataset) from another activity when constructing a dataset.

Enrichment tables are only needed when a specific activity has many features that cannot be associated with another activity. The activities that need enrichment are often commonly used in datasets and need to be sliced and diced by their various dimensions.



Examples of activities that commonly need enrichment

  • viewed_page (or started_session)
    Columns from the enrichment table: utm_medium, utm_source, utm_content, utm_campaign, ip_address, screen_width, ad_source, device_type, referral_url, referral_domain, fbclid, gclid, etc

  • purchased_product
    Columns from the enrichment table: product_name, product_description, sku, manufactured_by, volume, weight, etc.



How to "Borrow" Features from Other Activities when Building a Dataset




Still have questions?

Our data team is here to help! Here are a couple ways to get in touch...

šŸ’¬ Chat us from within Narrator

šŸ’Œ Email us at [email protected]

šŸ—“ Or schedule a 15 minute meeting with our data team