Determining a Personalization Strategy

To deliver meaningful personalized experiences, it’s critical to determine a personalization strategy that aligns the goals of your organization with the needs and wants of your users. An effective personalization strategy must be driven by measurable outcomes, or key performance indicators (KPIs). Once you define these outcomes, you can use them to guide the segmentation process, which involves identifying the data you need to group user subsets. Equipped with this information, you can plan out the specific content experiences that should be personalized for each segment and delegate tasks across your organization to achieve your business goals.

In this lesson, you’ll learn about important considerations and best practices for determining a personalization strategy, applying them to Clarity’s specific use cases along the way.

Setting Measurable Outcomes

To get started with their personalization strategy, Clarity must understand their broader business objectives and support them with measurable KPIs.

Liferay Analytics Cloud supports the tracking of several KPI metrics, including

• Conversion rate: The percentage of users in a segment who complete a desired action after interacting with an experience
• Average Order Value: The average amount of money a customer spends per transaction on an experience
• Bounce Rate: The percentage of users who leave an experience after visiting a single page
• Engagement Time: The amount of time users spend actively interacting with content in an experience

For example, Clarity wants to increase contact lens subscriptions among returning visitors who previously browsed lenses without purchasing any. To achieve this business objective, they are targeting a 20% increase in subscription conversions for this user group within three months. This is just one of many KPIs that Clarity has established for their business. With these business objectives in place, Clarity can proceed to segmentation.

Identifying Data Needs for Segmentation

After setting their KPIs, Clarity must determine who they are personalizing for and what data they need to do so. To divide their user base into meaningful segments, they should take the following steps:

• Identify Logical Groupings: Determine the user subsets that would benefit from having tailored content experiences on your website, such as new visitors, loyal customers, or users interested in specific product categories.
• Map Data Sources: Compile the data currently available to you via Liferay DXP, Analytics Cloud, or integrated external platforms.
• Evaluate Data Gaps: Analyze your existing data to find out if you require additional information for precise segmentation.

For example, Clarity wants to define a segment for users who frequently browse frames. To do this, they must leverage dynamic user data indicating page visit frequency and product category views. They can compile this information with purchase history data from an integrated CRM to gain a comprehensive view of users in this subset.

Designing Personalized Content

After determining the audience segments they want to target, Clarity must think through the specific personalized experiences they want to provide to each segment. Through this process, they must decide what content variants to create and where to place them to achieve KPIs for a given segment.

Here are some important considerations when designing personalized content:

• Identify User Journey Touchpoints: Highlight important or high-traffic areas of your website as opportunities to deploy personalized experiences, such as the homepage, category pages, checkout page, or post-purchase confirmation.
• Select Personalization Tactics: For the specific locations you’ve identified, determine which types of content would be most effective to personalize, whether banners, product recommendations, or text blocks.
• Prepare Targeted Content Variations: Use distinct images, calls-to-action, or product descriptions in each experience that are geared to the specific needs of a given user segment.

For their Frequent Frame Browser segment, for example, Clarity wants to create three variations of the homepage banner: the first promotes a designer frame brand, the second reminds users to try frames using the virtual tool, and the third displays a carousel of customer testimonials. Clarity can measure and compare the performance of each of these experiences to determine which is the most effective at increasing conversions for this particular user segment.

Planning for Collaboration

Personalization isn’t a one-person task. It requires collaboration across your organization’s marketing, content, data, and development teams. A clear plan ensures everyone knows their role and helps coordinate efforts within Liferay.

These are some best practices for collaborating on personalization:

• Delegate Team Responsibilities: Assign the appropriate teams to manage segments, create experiences, and analyze results, ensuring a balance workload that leverages each team’s specific skill set.
• Establish Governance Processes: Use Liferay permissions and workflows to manage content and segmentation updates efficiently.
• Iterate and Improve: Schedule regular reviews to refine personalization based on performance data.

For Clarity, the marketing team defines and manages segments, while content creators and designers prepare page variants, and the business analytics team tracks performance metrics for each experience. The teams should participate in regular strategy syncs to align all stakeholders.

Conclusion

A robust personalization strategy relies on capturing general business objectives with clear KPI metrics. Once measurable outcomes are defined, organizations can leverage data from multiple sources to create audience segments and deliver personalized experiences to them. By making personalization a collaborative effort among multiple teams, Clarity can set themselves up for long-term success as their business continues to grow.

Next, you’ll learn more about the different types of user data and how you can collect and manage that data ethically.