Target visitors
Audiences
Optimizely Web Experimentation Optimizely Personalization Optimizely Performance Edge In Optimizely Web Experimentation and Optimizely Performance Edge, an audience is a group of visitors .. /..
Target audiences using the Audience Builder
Optimizely Web Experimentation Optimizely Personalization Optimizely Performance Edge Go to the Audiences dashboard, which lists audiences. Click Create New Audience .
Target audiences with conditions
When you configure audiences to target visitors in your experiment, you build those audiences using conditions. The following sections describe each audience condition, including common ways to use them to target certain visitors.
Target audiences by Referrer URL
Optimizely Web Experimentation Optimizely Performance Edge Optimizely Personalization The Referrer URL audience condition option lets you trigger an experiment based on the URL that your visitors came from, known as the referrer . Typical use cases include setting audiences by the search engine the visitor uses, or excluding certain promotional referrers.
Target audiences with custom JavaScript
Optimizely Web Experimentation Optimizely Performance Edge Optimizely Personalization Custom JavaScript audience conditions let you target your experiment for a uniquely defined set of pages or visitors. To create a Custom JavaScript condition, begin creating an audience ..
Create audiences with Dynamic Customer Profiles
Optimizely Web Experimentation Optimizely Personalization A Dynamic Customer Profile (DCP) is a single, actionable view of your customer built from a combination of first- and third-party customer data. You can deliver consistent, personalized web and mobile experiences for your most valuable customers and measure the impact of those experiences.
Target known visitors with Dynamic Customer Profiles
Optimizely Web Experimentation Optimizely Personalization Use dynamic customer profiles (DCP) with Optimizely Personalization to directly expose content attributes in the browser to deliver 1-on-1 personalization to your customers in your experiments and campaigns. Attributes describe what you know about your individual customers, such as their favorite products, lifetime value scores, and loyalty memberships.
Target group visitor behaviors
Optimizely Web Experimentation Optimizely Performance Edge Optimizely Personalization You can target experiences to specific audiences based visitor behaviors in real-time, and create audiences based on what visitors do on your site. In Optimizely Personalization, you can use behavioral targeting to deliver custom experiences to specific groups of visitors on your site based on their behaviors.
Static and dynamic audience conditions
Optimizely Web Experimentation Optimizely Performance Edge Optimizely Personalization There are several ways to build an audience condition in Optimizely Web Experimentation, and approaches to evaluate and troubleshoot each one. Visitor attributes may change over time.
Build interest-based audiences with adaptive audiences
Optimizely Web Experimentation Optimizely Personalization Optimizely Web Experimentation and Optimizely Personalization's adaptive audiences let you target visitors based on their interests. Instead of relying on extensive data analysis to define explicit behavioral targeting rules, you can create a predicted intent audience condition that captures a certain percentage of your visitors who are most interested in a specific topic.
Migrate from uploaded audiences to list attributes
Optimizely Web Experimentation Optimizely Performance Edge List attributes target visitors based on their membership in an audience you already defined somewhere outside of Optimizely Web Experimentation. With this feature, you import a custom list of users and then create audience conditions based on those lists.
List attributes and table attributes
Optimizely Web Experimentation Optimizely Personalization Use when you defined a group of users in an external system and want to target that audience with an experience. Often better suited to integrations with other vendors, where it can be difficult to understand what has changed since the last time data was uploaded.
Configure list attributes
Optimizely Web Experimentation Optimizely Performance Edge Optimizely Personalization List attributes are a type of external attribute segments visitors that are part of an audience you have already defined somewhere outside of Optimizely Web Experimentation. You can import custom lists of users, and then create audience conditions based on those lists.
Custom attributes: Capture visitor data through the API
Optimizely Web Experimentation Optimizely Personalization Visitors to your website differ by plan type, language, and other characteristics. Sometimes, segmenting the results of your experiments and personalization campaigns based on these characteristics is helpful.
Target URLs to choose where your experiment runs
Optimizely Web Experimentation Optimizely Performance Edge Optimizely Personalization Choose the URLs for an experiment or campaign to determine where it runs on your site. You also can use the URL match types available in Optimizely Experimentation or Optimizely Personalization to target a specific URL or a group of URLs.
Improve custom attribute persistence with browser cookies
Optimizely Web Experimentation Optimizely Personalization Optimizely Web Experimentation and Optimizely Personalization use cross-origin targeting to persist information stored in browser localStorage across origin boundaries. Information in localStorage is used for many things , including Persisting campaign, experiment, and variation assignments.
IP Filtering: Exclude IP addresses or ranges from your results
Optimizely Web Experimentation offers two separate filtering tools under Settings > Advanced . They solve different problems, so it helps to know which one you need Results Filtering removes specific IP addresses from your results pages.
Pages and URL targets
Optimizely Web Experimentation Optimizely Personalization Optimizely Performance Edge Pages are reusable templates that tell Optimizely Experimentation where and when to deliver experiments, personalized experiences, and recommendations on your site. For example, a page might run an experiment on your homepage (where) immediately on initial page load (when).