Data Preparation

Audience Hub is built from the ground up to let marketing teams target effectively without having to know any SQL. But unlike other segmentation tools, Census Segments runs directly on top of a data warehouse or other data source. Marketing teams love this because it gives them access to the full world of a company's up-to-date and approved data.

Working with a warehouse directly can be overwhelming. Census provides a number of tools for the data teams to make preparing their data for use with segments and easy and straightforward.

Highlighting Datasets For Segmentation

Segments are built on top of your company's Datasets. Today you are required to set a unique ID for Dataset to be able to get started segmenting your data. Optionally you can also define relationships for your dataset which will unlock further functionality.

Working Across Relationships

When creating segments, you can also create advance conditions by leveraging related datasets and filtering based on its attributes as well.

Relationships defined in datasets are one-to-many, but segments can also take advantage of implicit many-to-many relationships and multi-step relationships automatically. Users simply need to select the related dataset they care about and Census will take care of building the series of joins to associate them.

Segmenting on Event Streams

Datasets also provide the ability to set Dataset Types. For segmentation, one of the most powerful types is the Event type. By highlighting the datasets that contain event data, marketers can create segments that filter on depth of engagement, engagement in certain time periods, specific interactions, as well as filtering on any other data point.

Enriching Datasets

The data warehouse is a vast repository of data generated by your customer interactions: the products the buy, the actions they take and the invoices, orders, documents, and anything else they create in working with your business. This is first-party data, the things only your business knows about your customers.

Effective segmentation often also requires third-party data as well, which is data provided by external services such as demographic and firmographic data. To build a segment with the condition "Give me all of my users that signed up in the last 90 days who work at companies with more than 1,000 employees", you'll need both first and third party data.

Enrichments make it easy to add third party data points to your datasets, so they're available both for segmentation, as well as in your warehouse.

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