Positive digital experiences get the right content to users at the right time. A content personalization engine can help with that.
A personalization engine gathers data on user behaviors, attributes and preferences, then uses this information to deliver relevant content from the organization's content management system (CMS) to each customer. This process helps engage audiences, as the system learns their preferences and aims to deliver a personalized experience.
Integrated with a CMS, personalization engines can transform the overall customer experience and help organizations better understand their customers' needs and preferences.
What is a personalization engine?
A personalization engine collects and processes data from various sources, such as user profiles, browsing history and purchases. It then applies machine learning algorithms and predictive analytics to make sense of this data, identify patterns and draw insights. As it continuously learns from user behavior, the engine can determine what content or experience is most relevant to every user in real time and improve an organization's approach to personalization.
Personalization approaches can be split into three methods:
- Explicit personalization. This involves knowing the types of content users are interested in based on information about them. That information includes their age; geographic location; or their favorite sports, hobbies, foods or vacations.
- Implicit personalization. This infers what content users may be interested in based on their previous browsing histories or other sources of information. This may include previous purchases recorded in CRM or sales systems as well as demographic data.
- Contextual personalization. This infers content relevant to a user based on information like the user's location or the time. Computers and smart devices can use GPS or Wi-Fi technology to provide a user's approximate location, while a Bluetooth beacon can provide that individual's exact location.
In all instances, it helps to know some details about the user, such as an email address or phone number from a previous login. However, anonymous personalization is possible with techniques like IP tracking and cookies through a content personalization engine.
The personalization engine integrates with a content management system -- often a headless CMS -- to add personalization to the content delivery. This integration lets businesses dynamically modify and deliver content based on user attributes, context and goals. As the engine tailors content to each user's needs and preferences, it can improve engagement, conversions and overall customer satisfaction.
Personalization engines and headless CMS
A headless CMS is a content management system that separates the front-end UX from the back-end content development and management capabilities. This separation can improve performance when serving content to consumers and improve security as the APIs only let users view, not update, content.
A headless CMS architecture can be especially helpful if an organization integrates its CMS with a personalization engine. This type of CMS lets users create and manage content in the back end and then deliver it -- along with custom metadata for personalization -- to a database that the company website and personalization engine can access.
The separation of content creation from delivery means the system can share content and its metadata in an agnostic way, which enables flexibility during integrations with personalization engines.
How to accomplish a CMS-personalization engine integration
Explore the five steps for integrating a personalization engine with a CMS.
1. Choose the tool set
The personalization engine market includes various vendors, including Adobe, Salesforce and Oracle. Organizations should choose a tool set based on criteria that includes the following:
- Existing technologies.
- Business requirements.
- Required system integrations.
- Teams' skill sets.
2. Incorporate behavior tracking
3. Create a metadata tagging scheme
A content personalization engine must be able to pull content from the data published in the headless CMS based on pre-specified criteria. For example, a travel site could show vacations that include certain keywords, such as "winter sports," "Europe," "medium price range" and "deals of the week."
The personalization engine can then match these criteria with information about the user. Teams can also re-engineer monolithic pages to break content into smaller chunks, so users can more easily digest the information.
4. Develop targeting rules
Personalization is all about rules. For example, if a user is under 25 years old, has an interest in life insurance and has a salary less than $100,000, then the website should show that user low-cost life insurance products.
5. Create dynamic content
Depending on the incumbent CMS, organizations can use various approaches to create dynamic content, which teams update or edit frequently. Some content personalization engines only plug into specific CMS products, and others claim to work with all of them.
Other considerations for CMS-personalization engine integrations
If a company uses multiple CMS products, it should consider using a content hub. A content hub acts as the ultimate CMS, combining disparate content silos into a single library. This approach is especially beneficial if the various CMS products are or run as headless. They can share content to the hub independent of the CMS, then share it to the website and personalization engine.
Personalization is about considering capabilities across all content delivery channels, such as email, text messaging and apps. Organizations may need to use different approaches for different channels, which the personalization engine can help with.
Additionally, concerns over privacy and data usage are increasing. Some countries have created legislation, such as GDPR in the European Union, to address these concerns. A facet of GDPR states companies can no longer capture data without explicit permission from users, and these guidelines are applicable worldwide. An organization shouldn't consider personalization without involving its compliance and regulatory teams.
Editor's note: This article was originally written by Jonathan Bordoli and expanded by Jordan Jones.