Attributes Data

Cortex extends the value of your business’s unique data by enabling anyone to transform that data into Machine Learning Pipelines. The types of data supported by Cortex fall into four categories: events, attributes, items, and ID mappings.

Dataset Description Example
Events * Timestamped actions taken by your users. Customer ABC completes a purchase event at time T.
Attributes Characteristics or traits of your users. Customer ABC has job title ‘Professor’, and age 49.
Items Metadata attributes for the items that your users interact with, via events. Item XYZ has category ‘shoes’, and price 49.99.
ID Mappings Associations between one set of IDs and another. Customer ABC has cookie ID 123.

* required

In this guide, we’ll provide an overview of Attributes data and discuss the various ways that it may be ingested into Cortex.

What are attributes?

Attributes provide information about the characteristics or traits of your users. Attributes data is optional in Cortex, but recommended — the more data at Cortex’s disposal, the wider the set of predictions you can make, and the more accurate your predictions will be.

Attributes data can include any descriptor of the users tied to your events data. For example, if you’re tracking customer purchase behavior via Events data, you may supplement that data with user attributes from a Customer Data Platform (e.g. age, gender, geo, loyalty status, etc.).

The below table shows what a sample of Attributes data might look like for a set of subscription customers. Note that Cortex must be able to match each user’s attributes with their user’s events, so please be sure to either (a) reference the same set of IDs, or (b) send a separate ID Mapping data source into Cortex.

user_id age location membership loyalty_status
1asdvn329 41 US-CA paid gold
d189dhl99 27 US-MA free silver
as1k2f0f0 63 US-AK free
0sdf10933 44 CN-BC free silver
kdfgf30gh 36 US-IL paid gold

When you upload a file like this, Cortex stores the attributes with a timestamp indicating when each was ingested. This allows your pipelines to access a historical record of attribute values over time. For example, by recording that User 1asdvn329 was a paid member on January 1st but churned to a free member on January 8th, your pipeline will know the user’s membership type at the time of each of their events.

How do I send Attributes data into Cortex?

There are two ways that you can ingest Attributes data into Cortex:

1) Batch File Uploads

Attributes data can be batch uploaded to Cortex in files exported from, say, your data lake or CDP vendor. To do this, schedule a recurring file upload into a cloud-based directory hosted by either you or Vidora. Cortex provides flexibility around both the format of these files (CSV, JSON, Parquet, etc.) as well as the type of directory into which they’re uploaded (Amazon S3, Google Cloud, Azure, etc.).

2) Direct Integrations

Vidora integrates with several third party platforms (CDPs, data warehouses, analytics providers, etc.) commonly used for enterprise data storage. For more information about the data source integrations supported by Cortex, click here.

Related Links

Still have questions? Reach out to support@vidora.com for more info!

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