Data provision and schemas

Enriching your customer profiles

To build unified and enriched customer profiles in the Lexer CDP, data types, formats, and schemas are required. In this article, we'll look at common subject matter, our different schemas, and provision methods.

Common subject matters

Lexer supports a wide range of subject matter and implementation styles. The below table outlines some common data areas and our supported connectors for these types of data.

Data area	Connector Type	Frequency
Customer	Direct Integration or batch via API or SFTP.	Historic and daily updates.
Ecommerce Transactions	Direct Integration or batch via API or SFTP.	Historic and daily updates.
Retail/POS Transactions	Direct Integration or batch via API or SFTP.	Historic and daily updates.
Returns	Direct Integration or batch via API or SFTP.	Historic and daily updates.
Email Engagement	Direct Integration.	Historic and daily updates.
Master Product fie	Direct Integration or batch via API or SFTP.	Historic and daily (including discontinued products).
Website Engagement	Lexer Javascript Tag Integration.	Real-time.
Other	Subject to scoping.	Subject to scoping.

Lexer Standard Retail Schema

Through our experience working with retail customers, we’ve developed a range of retail attributes to enable valuable customer insight and action.

These attributes are generally powered by supported integration data, but in some cases a solution might entail pushing data directly to Lexer (rather than via an integration).

Lexer generally supports these solutions provided this data is shared in the required format and structure.

Example Email Data Schema

Lexer offers in-platform integrations to easily connect with many popular Email Service Providers (ESPs). These integrations automatically gather data to drive related data points against your customer profiles.

In some cases (for example, with on-premise data) your solution might entail email service data directly to Lexer. In these instances Lexer will work with you to agree the requirements of an optimal data format.

The below table shows a rudimentary example structure for a "contacts" dataset, which would form one part of a broader ESP dataset.

Required Field	Required Format	Example
email	Text string	"[email protected]"
first_name	Text string	"Sam"
last_name	Text string	"Smith"
signup_date	Date	2019-06-21
unsubscribe_date	Date	2019-06-21
list_names	Text string	"Marketing", "VIPs"
email_optin_status	Text string	"subscribed" \| "unsubscribed"
mobile_optin_status	Text string	"subscribed" \| "unsubscribed"

Data Provision Methods

Lexer supports multiple data provision mechanisms. Below are the most common:

Customer profiles, enriched

That's how you can use our data provision and schemas to help unify and enrich you customer profiles in our CDP!