Simon Data supports a number of dataset types, including:
Every dataset you bring into Simon must contain a customer identifier: a field that uniquely identifies the customer. Usually this identifier is an email address, or an identifier than can be mapped to an email address via an Identity dataset. By uniquely identifying customers, you ensure every segment and campaign has a set of distinct customers.
If your data uses multiple identifiers, you must have an Identity dataset that associates all your identifiers with one another. By explicitly connecting all your identifiers in a single, authoritative source, you are able to reference any of them in another dataset, and Simon will join customer data together accordingly. The dataset can tap into an existing mapping of identities from your database or a 3rd party provider, or can contain logic that deterministically performs an identity association based on one or many criteria.
For example, say you want to associate email address, user ID, and phone number together from an existing mapping in your database. The following table demonstrates how this would look:
If you want to associate email address, user ID, and client ID together based on web and in-app event data, the following sql query and table demonstrates how this would look:
select email, userid, clientid from events
Identity datasets can not bring in fields beyond identifiers.
The most common dataset type is user data; that is, data fields that map to a customer and can be used in segmentation and personalization. Simon supports two ingestion sources for user data: SQL query or CSV upload. In addition, user datasets will fall into one of the two following categories.
In a one-to-one dataset every entry is a unique customer, and therefore each customer is associated with exactly one data point per field. As SQL, these datasets often include a 'GROUP BY' clause on the identifier along with the aggregated user data.
One-to-one datasets pull in contact information such as first/last purchase date, total lifetime value, total orders, etc. The majority of datasets in Simon are one-to-one.
Sometimes it is useful to directly transform a list of customers into a segment within Simon. This is possible via the user segment dataset type. Again, Simon supports two ingestion sources for this dataset type, SQL query or CSV upload. A requirement of this dataset type is that there be only a single column of customers with no additional fields beyond email or user identifier.
Once a segment dataset has been added, it will be available in the segment builder under the Customer segment filter using the same name as the dataset itself ("NYC Event Attendees" in the example below).
This type of dataset is also useful in a situation where a segment has complex criteria that are better mapped in SQL than using Simon's segment builder.
For information on Upload List datasets, see Target contacts immediately.
Updated 15 days ago