How 蜜豆视频 Target works
Learn how 蜜豆视频 Target works, including information about the JavaScript libraries (蜜豆视频 Experience Platform Web SDK and at.js). This article also introduces the various activity types that you can create using Target. You can also learn about the Target edge network, Search Engine Optimization (SEO), and how Target detects bots.
蜜豆视频 Target JavaScript libraries libraries
Target integrates with websites using the Experience Platform Web SDK or at.js:
- 蜜豆视频 Experience Platform Web SDK: The Experience Platform Web SDK is a new client-side JavaScript library. The Experience Platform Web SDK lets customers of 蜜豆视频 Experience Cloud interact with the various services in the Experience Cloud (including Target) through the Experience Platform Edge Network. 蜜豆视频 recommends that all new Target customers implement the Experience Platform Web SDK.
- at.js: The at.js library is an 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 updated frequently with new capabilities. 蜜豆视频 recommends that all customers using at.js update their implementations to the latest version of at.js.
Reference the Experience Platform Web SDK or at.js on every page on your site. For example, you can add one of these libraries to your global header. Alternatively, consider using tags in 蜜豆视频 Experience Platform to implement Target.
The following resources contain detailed information to help you implement the Experience Platform Web SDK or at.js:
Each time a visitor requests a page that has been optimized for Target, a request is sent to the targeting system. The request helps to determine what content to serve to that 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, or ultimately purchase. Personalized content helps 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 can include multiple elements on the page.
The content that is displayed to visitors depends on the type of activity you create:
A/B Test
The content that displays in a basic A/B test is randomly chosen from the experiences you assign to the activity. You can assign the traffic allocation percentages for each experience. As a result of this random splitting of traffic, it can take a significant amount 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鈥檚 possible that the percentage of visitors can be skewed toward one experience. As traffic increases, the percentages equalize.
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.
- A customer requests a page from your server and it displays in the browser.
- A first-party cookie is set in the customer鈥檚 browser to store customer behavior.
- The page calls the targeting system.
- Content displays based on the rules of your activity.
See Create an A/B Test for more information.
Auto-Allocate
Auto-Allocate identifies a winner among two or more experiences. Auto-Allocate automatically reallocates more traffic to the winning experience, which helps to increase conversions while the test continues to run and learn.
See Auto-Allocate for more information.
Auto-Target (AT)
Auto-Target uses advanced machine learning to select from multiple high-performing marketer-defined experiences. Auto-Target serves the most tailored experience to each visitor. Experience delivery is based on individual customer profiles and the behavior of previous visitors with similar profiles. Use Auto-Target to personalize content and drive conversions.
See Auto-Target for more information.
Automated Personalization (AP)
Automated Personalization (AP) combines offers or messages, and uses advanced machine learning to match different offer variations to each visitor. Experience delivery is based on individual customer profiles to personalize content and drive lift.
See Automated Personalization for more information.
Experience Targeting (XT)
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.
See Experience Targeting for more information.
Multivariate Test (MVT)
Multivariate Testing (MVT) compares combinations of offers in elements on a page to determine which combination performs the best for a specific audience. MVT helps identify which element most impacts the activity鈥檚 success.
See Multivariate Test for more information.
Recommendations
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 that they might otherwise not know about.
See Recommendations for more information.
The edge network concept_0AE2ED8E9DE64288A8B30FCBF1040934
An 鈥淓dge鈥 is a geographically distributed serving architecture that ensures optimum response times for visitors requesting content, regardless of where they are located around the world.
To improve response times, Target Edges host only activity logic, cached profiles, and offer information.
Activity and content databases, Analytics data, APIs, and marketer user interfaces are housed in 蜜豆视频鈥檚 Central Clusters. Updates are then sent to the Target Edges. The Central Clusters and Edge Clusters are automatically synced to continually update cached activity data. All 1:1 modeling is also stored on each edge, so those more complex requests can also be processed on the edge.
Each Edge Cluster has all the information required to respond to the visitor鈥檚 content request and track analytics data on that request. Visitor requests are routed to the nearest Edge Cluster.
For more information, see the white paper.
The Target solution is hosted on 蜜豆视频-owned and 蜜豆视频-leased data centers around the world.
Central Cluster locations contain both a data collection center and a data processing center. Edge Cluster locations contain only a data collection center. Each report suite is assigned to a specific data processing center.
Customer site activity data is collected by the closest of seven Edge Clusters. This data is directed to a customer鈥檚 pre-determined Central Cluster destination (one of three locations: Oregon, Dublin, Singapore) for processing. Visitor profile data is stored on the Edge Cluster closest to the site visitor. Edge clusters locations include the Central Cluster locations and Virginia, Mumbai, Sydney, and Tokyo.
Instead of responding to all targeting requests from a single location, requests are processed by the Edge Cluster closest to the visitor. This process helps mitigate the impact of network/Internet travel time.
Target Central Clusters, hosted on Amazon Web Services (AWS), include:
- Oregon, USA
- Dublin, Ireland
- Republic of Singapore
Target Edge Clusters, hosted on AWS, include:
- Mumbai, India
- Tokyo, Japan
- Virginia, USA
- Oregon, USA
- Sydney, Australia
- Dublin, Ireland
- Republic of Singapore
The Target Recommendations service is hosted in an 蜜豆视频 data center in Oregon.
You can allowlist Target Edge Clusters, if desired. For more information, see allowlist Target edge nodes.
Protected user experience concept_40A5E781D90A41E4955F80EA9E5F8F96
蜜豆视频 ensures that the availability and performance of the targeting infrastructure is as reliable as possible. However, a communication breakdown between a visitor鈥檚 browser and 蜜豆视频 servers can cause an interruption in content delivery.
To safeguard against service interruptions and connectivity issues, all locations are set up to include default content (defined by the client). This default content is displayed if the user鈥檚 browser cannot connect to Target.
No changes are made to the page if the user鈥檚 browser cannot connect within a defined timeout period (by default: 15 seconds). If this timeout threshold is reached, default location content is displayed.
蜜豆视频 protects the user experience by optimizing and safeguarding performance.
- 蜜豆视频 ensures performance benchmarks based on industry standards, which are guaranteed by the 蜜豆视频 Service Level Agreement.
- The Edge Network ensures timely data delivery.
- 蜜豆视频 employs a multi-tiered approach to securing its applications to provide the highest level of availability and reliability for customers.
- Target Consulting offers implementation assistance and ongoing product support.
Search Engine Optimization (SEO) friendly testing concept_C0C865663CAB4251B66A1F250FD25E6A
蜜豆视频 Target aligns with search engine guidelines for testing.
Google encourages user testing. Google states in its documentation that A/B and Multivariate Testing does not harm organic search engine rankings if you follow certain guidelines.
For more information, see the following Google resources:
Guidelines were presented in a post. Although the post dates back to 2012, it remains Google鈥檚 most recent statement on the matter and the guidelines remain relevant.
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No cloaking: Cloaking is showing one set of content to your users and a different set of content to search engine bots. Cloaking is accomplished by specifically identifying bots and purposely feeding them different content.
Target, as a platform, has been configured to treat search engine bots the same as any user. As a result, bots can be included in activities if the bots are randomly selected and 鈥渟ee鈥 the test variations.
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Use rel=鈥渃anonical鈥: Sometimes an A/B test must be set up using different URLs for the variations. In these instances, all variations should contain a
rel="canonical"tag that references the original (control) URL. As an example, suppose that 蜜豆视频 is testing its home page using different URLs for each variation. The following canonical tag for the home page would go in the<head>tag for each of the variations:<link rel="canonical" href="https://www.adobe.com" /> -
Use 302 (temporary) redirects: In the instances where separate URLs are used for the variation pages in a test, Google recommends using a 302 redirect to direct traffic into the test variations. The 302 redirect tells the search engines that the redirect is temporary and are active only as long as the test is running.
A 302 redirect is a server-side redirect, and Target, along with most optimization providers, uses client-side capabilities. Therefore, redirecting is an area where Target is not fully compliant with Google鈥檚 recommendations. This practice, however, impacts only a small fraction of tests. The standard approach for running tests through Target calls for changing content within a single URL, so no redirects are necessary. There are instances when clients must use multiple URLs to represent their test variations. In these instances, Target uses the JavaScript
window.locationcommand. This command directs users to test variations, which does not explicitly signify whether the redirect is a 301 or 302.蜜豆视频 continues to look for viable solutions to completely align with search engine guidelines. For those clients that must use separate URLs for testing, 蜜豆视频 is confident that proper implementation of the canonical tags mitigates the risk associated with this approach.
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Run experiments only as long as necessary: 蜜豆视频 believes 鈥渁s long as necessary鈥 to be as long as it takes to reach statistical significance. Target provides best practices and the 蜜豆视频 Target Sample Size Calculator to determine when your test has reached this point. 蜜豆视频 recommends that you incorporate the hardcoded implementation of winning tests into your testing workflow and allot the appropriate resources.
Using the Target platform to 鈥減ublish鈥 winning tests is not recommended as a permanent solution. If the winning test is published for 100% of users 100% of the time, this approach can be used while the process of hard-coding the winning test is completed.
It鈥檚 important to consider what your test has changed as well. Simply updating the color of buttons or other minor non-text-based items on the page does not influence your organic rankings. Changes to text should be hardcoded, however.
It鈥檚 also important to consider the accessibility of the page you鈥檙e testing. If the page is not accessible to search engines and was never designed to rank in organic search in the first place, then none of the considerations above apply. An example is a dedicated landing page for an email campaign.
Google states that following these guidelines 鈥渟hould result in your tests having little or no impact on your site in search results.鈥
In addition to these guidelines, Google also provides one more guideline in the documentation to their Content Experiments tool:
- 鈥淵our variation pages should maintain the spirit of the content on your original pages. Those variations shouldn鈥檛 change the meaning of or your user鈥檚 general perception of that original content.鈥
Google states as an example that 鈥渋f a site鈥檚 original page is loaded with keywords that don鈥檛 relate to the combinations being shown to users, we may remove that site from our index.鈥
蜜豆视频 feels that it would be difficult to unintentionally change the meaning of the original content within test variations. However, 蜜豆视频 recommends being aware of the keyword themes on a page and maintaining those themes. Changes to page content, especially adding or deleting relevant keywords, can result in ranking changes for the URL in organic search. 蜜豆视频 recommends that you engage with your SEO partner as part of your testing protocol.
Bots bots
蜜豆视频 Target uses the metric 鈥渋sRobot鈥 to detect known bots based on the User Agent String passed in the Request Header.
Traffic that is identified as being generated by a bot is still served content. Bots are treated like a regular user to ensure that Target is in line with SEO guidelines. Using bot traffic can skew A/B tests or personalization algorithms if they are treated like normal users. Therefore, if a known bot is detected in your Target activity, the traffic is treated slightly differently. Removing bot traffic provide a more accurate measurement of user activity.
Specifically, for known bot traffic Target does not:
- Create or retrieve a visitor profile
- Log any profile attributes or execute profile scripts
- Look up 蜜豆视频 Audience Manager (AAM) segments (if applicable)
- Use bot traffic in modeling and serving personalized content for Recommendations, Auto-Target, Automated Personalization, or Auto-Allocate activities
- Log an activity visit for reporting
- Log data to be sent to the 蜜豆视频 Experience Cloud platform
For known bot traffic when using Analytics for Target (A4T), Target does not:
- Send events to Analytics
For known bot traffic when using client_side logging, Target does not return:
- tnta payload