Targeting Audiences with Segmentation

Audience targeting ensures that the right content reaches the right users at the right time. Once you are equipped with static and dynamic user data from multiple sources, you can use that data to group users into target audiences with shared characteristics, behavior, or interests. In Liferay, audience targeting is performed via user segmentation, which allows you to define rules and criteria for grouping users. In this lesson, you’ll learn about the fundamentals of audience targeting, along with general best practices for user segmentation.

Identifying Target Audiences

Before you go about defining user segments, you must examine your user base to determine natural or logical groupings that would be good candidates for segmentation. In this process, keep your personalization strategy in mind to make sure that any groupings you create align with your overall business objectives.

Common approaches for examining your user base include the following:

• Analytics Review: Examine traffic sources, page views, bounce rates, and conversion metrics to identify patterns among users.
• Stakeholder Input: Seek insights from marketing, product, and support teams, who often have direct or unique views into key audience groups.
• Persona Development: Create data-informed profiles representing core user types, such as first time customers or users seeking specific services like eye exams.
• Survey Feedback: Record recurring needs or interests directly from user submitted forms.

With these findings, you can identify target audiences based on shared static or dynamic attributes. Clarity, for example, might find that younger users are drawn to style-focused eyewear, while older users tend to prioritize efficient prescription service or insurance compatibility. These two groups may be good candidates for separate user segments that each receive a personalized experience.

Segmenting Target Audiences

Once you’ve identified your target audiences, you can create user segments for them. Liferay segments are defined with specific criteria to group users by shared characteristics. Like user data itself, segment criteria can be either static or dynamic.

Static Segmentation

Static segments are based on fixed or slowly changing data, including

• Demographics like age, gender, and location
• Psychographics like lifestyle, interests, and values
• User affiliations with specific sites, organizations, or roles
• Needs or preferences that are indicated through custom fields

When creating static segments, use clear, meaningful criteria that align with your personalization goals. Take care to ensure that the data guiding your segmentation criteria is up to date. Because static data does not change often, the changes that do occur are more likely to be overlooked.

Avoid setting rules that are overly broad or overly narrow, and try to strike a balance between reach and relevance. Delivering a personalized experience to a segment with only a few users is unlikely to be an effective use of your organizational resources. Similarly, the benefits of personalization are diluted for segments without restrictive enough criteria, as they may contain users with varying needs and characteristics.

Dynamic Segmentation

Dynamic segments, meanwhile, use behavioral data, including

• Actions like page visits, downloads, and product views
• Engagement patterns like dwell time, abandoned carts, and content interactions
• Time-based criteria like visit frequency or recent form submission

When creating dynamic segments, use behavioral triggers to reflect users' intent or their stage in the customer journey. Dynamic criteria should be specific and actionable. For example, Clarity might define a dynamic segment for users who visited the exam booking page but didn’t complete the form submission.

Compound Segmentation

Liferay also supports the creation of compound segments that combine existing segments. You can use this capability to achieve more complex personalization objectives that require both static profile data and dynamic behavioral data. Note that compound segments are even more susceptible to overly broad or narrow criteria, depending on the segments that are combined.

Clarity’s Target Audiences

The goal of audience targeting is not just to segment your user base for the sake of it, but to support concrete business goals, whether boosting conversion rates, improving customer retention, or enhancing user satisfaction.

For Clarity, such business goals might include

• Increasing prescription renewals through personalized reminders.
• Promoting specific eyewear lines to segmented age groups.
• Driving engagement with educational content based on vision health interests.

Clarity can then identify target audiences and create user segments to achieve specific outcomes.

Example user segments might look like the following:

• A static segment that targets contact lens users under the age of 30 for product tips and style blogs
• A dynamic segment that targets users who visited the What’s New page in the last three days to offer discounts or coupons
• A compound segment that combines returning users from California with users who recently viewed premium frames to drive regional promotions

By defining segments with specific, meaningful criteria, Clarity can deliver focused, relevant personalized experiences.

Conclusion

To identify target audiences, you must synthesize your business objectives with the user data available to you from multiple sources. After determining logical user groupings, you can use Liferay’s segmentation capabilities to capture those target audiences with specific criteria, whether it’s static, dynamic, or some combination of the two. Once your user segments are in place, you are ready to begin designing personalized experiences that deliver tailored content to each one.

Next, you’ll review what you’ve learned before moving on to the next module.