Create audiences with Dynamic Customer Profiles

Key Terms

This section defines key terms to help you get started. You can skip this section if attributes, data sources, and data management platforms are intuitive to you.

Attributes

Attributes describe what you know about your individual customers: their favorite products, lifetime value scores, VIP or loyalty memberships, gender, and other historical data. These attributes help you create tightly tailored experiences for every known customer who comes to your site.

Data source

A data source such as your CRM, ESP, data warehouse, or DMP stores individual customer attributes under corresponding customer IDs. To use these attributes to personalize your customers’ experiences on your site, create a DCP table and corresponding table attributes.

DCP table

A DCP table stores records extracted from your data sources and makes them available for targeting. Each row in the table represents a customer, and each column represents an attribute describing customers.

DCP table attribute

You can think of table attributes as the column headers in a DCP table. Each attribute represents a discrete piece of information contained in the customer records extracted from your data source.

DCP service

Optimizely Web Experimentation's DCP service collects and handles the data that you use to deliver personalized messaging. The third-party data that you send to Optimizely Web Experimentation is stored here.

Optimizely Web Experimentation uses a method called aliasing to connect the attributes kept in different tables to a single Optimizely Web Experimentation User ID. This single ID lets Optimizely Web Experimentation deliver customized experiences based on the data you have on individual customers across different tables. See aliasing in the developer documentation.

Currently, even when we provision or upgrade an account to Personalization Professional, DCP is not automatically included.  You need to separately place DCP as a standalone feature on the allow list. The same is true for your own free employee account.

Create a DCP service

To set up Dynamic Customer Profiles, first create a DCP service in Optimizely Web Experimentation. A DCP Service collects, stores, and processes the customer data that you’ll use to deliver personalized messaging.

1. Go to Account Settings. under your profile.

   

2. Select the Dynamic Customer Profiles tab.
3. Name your new DCP Service and click Create DCP Service.
   

   

   You can associate each Optimizely Web Experimentation Account only with one DCP Service, so you will not see the option to create a DCP Service if one already exists.

4. Link the Optimizely Web Experimentation projects that should be able to target based on data stored in this DCP Service. You can add multiple projects to the same service at any time.

Create a DCP table

Create a table to store records extracted from your data source:

1. Go to the Audiences dashboard.
2. Select the Attributes tab and click Create New Table. Optimizely Web Experimentation gives you a preview of the steps required to create a table.
3. Click Create New Table.
4. Tell Optimizely Web Experimentation how your table is organized. Enter the Table Name and identify how your web page stores the customer IDs to be used in this table: in a cookie, JavaScript variable, query parameter, or Optimizely Web Experimentation End User ID cookie.

   

In the example above, the customer IDs for the table are stored in a JS variable called locator_name. When using the JS variable option, ensure that the variable is global. You will not be able to refer to embedded properties using dot notation such as object.locator_name.

Optimizely Web Experimentation syncs the IDs in your new data source with Optimizely Web Experimentation User IDs, so you do not have to manage identity. As your visitor data updates, Optimizely Web Experimentation's DCP Service automatically connects and adds this information to your customer profiles.

Sometimes, customer IDs are stored in multiple locations. For example, IDs may be stored in cookies on some pages and as JavaScript variables on others. In this situation, use our REST APIs to alias this information. See also Customer profiles (DCP).

Define table attributes

Identify the customer attributes (text, Boolean value, number, or date) that you want Optimizely Web Experimentation to store in this table. Define this value type in the drop-down menu.

Check the Content-enabled box next to any values that you want to display directly in the browser. For example, if you want to show a visitor her “gold” level membership as part of a personalized experience on your site, check the Content-enabled box for the membershipLevel attribute.

Above, membershipLevel and purchasedLast60 are attributes you use in Optimizely Web Experimentation. Membership level value is also available for display in the browser.

Attribute names are case sensitive, so membershipLevel and MembershipLevel register as different attributes.

Upload your data

You can upload data to your table in the following ways.

• The v1.0 REST API lets you stream the data, one visitor at at time.
• You can upload data in bulk as a CSV. Every table is provisioned an Amazon S3 bucket. When you drop CSVs here, we will automatically begin uploading them into our system.
• You can upload small files (5mb or less) in the browser via Direct Upload.

Learn how to set up a streaming API or the bulk CSV upload.

The Data Upload page for each table contains a link to download a pre-configured CSV file you can use as a template for uploads to that table. (This is a great place to start if you have trouble with the header formatting!)

Make sure your CSV file is formatted as follows:

• Each column in the header row must be a registered attribute name. A CSV may contain a subset of the registered attributes.
• The header row must include a customerId column. All rows must contain a valid customer ID under this column.
• If a column header does not correspond to a registered attribute name, the upload will fail.
• If an attribute value does not respect the attribute's datatype/format, the upload will fail. See CSV datatype requirements.

Check that your upload is successful by going to Audiences. Open the Attributes tab and select a table.

Click Actions (...) and select Upload History.

The Data Upload History view provides a chronological view of your upload attempts.

If your latest upload was unsuccessful, check the formatting of your CSV and try again.

Common mistakes include:

• Uploading a .xlsx file instead of a .csv or .tsv
• Forgetting to register attributes before uploading data
• Not having a column labeled “customerId” - remember, all IDs must take this format
• Having “,” in an Attribute Value and saving the file as a .csv instead of .tsv

Create an audience

Create an audience using the customer attributes you added to your DCP table:

1. In the Audiences dashboard, click Create New Audience.
2. In the Audience Builder, name the audience (such as Platinum buyers).
3. Expand the list of External Attributes and find the table you just created. To use a table attribute as an audience condition, drag and drop it into Audience Conditions. Use logical conditions to create your new Audience. The following images show the membershipLevel and purchaseLast60 atttributes.

   

   

4. Click Save Audience.

See Target audiences using the Audience Builder.

Build a campaign

Congratulations! You can create a personalization campaign with your new audience, powered by your dynamic customer profiles.

To add 1-to-1 personalization to your campaigns, see exposing content attributes with DCP.