How Adobe Target Works

Adobe Target integrates with websites by means of one of two JavaScript libraries. at.js or mbox.js

  • at.js: The at.js library is the new implementation library for Target. The at.js library improves page-load times for web implementations and provides better implementation options for single-page applications. at.js is the recommended implementation library and is updated frequently with new capabilities. We recommend that all customers implement or migrate to the latest version of at.js.

  • mbox.js: The mbox.js library is the legacy implementation library for Target. The mbox.js library is still supported, but there will be no feature updates.

Important: All customers should migrate to at.js. For more information, see How to Migrate to at.js from mbox.js

You must reference one of the Target JavaScript files on every page on your site. For example, you might add it to your global header.

Each time a visitor requests a page that has been optimized for Target, a request is sent to the targeting system to determine what content to serve to a visitor. This process occurs in real-time—every time a page is loaded, a request for the content is made and fulfilled by the system. The content is governed by the rules of marketer-controlled activities and experiences and is targeted to the individual site visitor. Content is served that each site visitor is most likely to respond to, interact with, and ultimately purchase, to maximize response rates, acquisition rates, and revenue.

In Target, each element on the page is part of a single experience for the entire page. Each experience includes multiple elements on the page. A page is optimized with a single line of code in the <head> of each page you want to track.

The content that displays to visitors depends on the type of activity you create:

Activity Type Details

Create an A/B Test

The content that displays in a basic A/B test is randomly chosen from the assets you assign to the activity, according to the percentages you choose for each experience. As a result of this random splitting of traffic, it can take a lot of initial traffic before the percentages even out. For example, if you create two experiences, the starting experience is chosen randomly. If there is little traffic, it's possible that the percentage of visitors can be skewed toward one experience. As traffic increases, the percentages should become more equal.

You can specify percentage targets for each experience. In this case, a random number is generated and that number is used to choose the experience to display. The resulting percentages might not exactly match the specified targets, but more traffic means that the experiences should be split closer to the target goals.

  1. A customer requests a page from your server and it displays in the browser.
  2. A first party cookie is set in the customer's browser to store customer behavior.
  3. The page calls the targeting system.
  4. Content displays based on the rules of your campaign.


Auto Allocate identifies a winner among two or more experiences and automatically reallocates more traffic to the winning experience to increase conversions while the test continues to run and learn.


Auto-Target uses advanced machine learning to select from multiple high-performing marketer-defined experiences, and serves the most tailored experience to each visitor based on his or her individual customer profile and the behavior of previous visitors with similar profiles, in order to personalize content and drive conversions.

Automated Personalization

Automated Personalization (AP) combines offers or messages, and uses advanced machine learning to match different offer variations to each visitor based on their individual customer profile, in order to personalize content and drive lift.

Experience Targeting

Experience Targeting (XT) delivers content to a specific audience based on a set of marketer-defined rules and criteria.

Experience Targeting, including geotargeting, is valuable for defining rules that target a specific experience or content to a particular audience. Several rules can be defined in an activity to deliver different content variations to different audiences. When visitors view your site, Experience Targeting (XT) evaluates them to determine whether they meet the criteria you set. If they meet the criteria, they enter the activity and the experience designed for qualifying audiences is displayed. You can create experiences for multiple audiences within a single activity.

Multivariate Test

Multivariate Testing (MVT) compares combinations of offers in elements on a page to determine which combination performs the best for a specific audience, and identifies which element most impacts the activity's success.


Recommendations activities automatically display products or content that might interest your customers based on previous user activity or other algorithms. Recommendations help direct customers to relevant items they might otherwise not know about.