Personalization Campaign

In Optimizely Web Experimentation, the Personalization Experimentation feature allows you to simultaneously test and tailor experiences for different audiences.

Personalization experimentation involves the systematic testing of personalized content or experiences for different audience segments to determine what resonates best with each group. This process allows businesses to deliver more targeted and engaging experiences to their users, ultimately improving user satisfaction and achieving specific business goals.

With personalization experimentation, the goal is not just to deploy personalized experiences but also to test and optimize them. 

Personalization vs. Split Testing

Personalization doesn't work like A/B or MVT testing, where you compare different user experiences. Instead, it targets specific content to particular groups of visitors.

How Split Tests Inform Personalization

After running a split test, you may find that a variant works better for certain visitors, such as new users. In this case, you can use personalization to show only new visitors the variant experience. By analyzing split test results and using reporting segments, you can make informed decisions about what content to personalize for different visitor groups.

When to Use Personalization

Use personalization when split testing shows that certain visitor groups respond better to a specific experience. This could include tailored messaging or elements aimed at specific segments of your audience.

Advantages

Personalization lets you control which visitors see specific content.

Disadvantages

Without testing first, personalization can lead to incorrect assumptions about which content is best for each visitor segment.

Personalization experimentation

Before diving into personalization experimentation, experimentation team will need to identify the distinct audience segments they want to target. These segments can be based on various factors, such as demographics, behavior, preferences, or any other relevant criteria.

It is also helpful to know your customer journey to be able to analyze where in the journey you would like to improve their experience

Key performance indicators (KPIs) relevant to the personalization goals need to be defined and measured. These metrics could include conversion rates, engagement levels, time spent on the site, or any other relevant metric that reflects the success of the personalized experiences.

After running the experiment, experimentation team will analyze the performance data to identify which personalized variation is the most effective for each audience segment. Based on the results, they can optimize and refine the personalized experiences for better outcomes.

Iterative Process: Personalization experimentation is an iterative process. As user preferences and behaviors change, experimentation teams continuously test and refine their personalized content to ensure ongoing relevance and effectiveness.

By combining the power of personalization and experimentation, businesses can create a more dynamic and adaptive digital experience for their users, fostering deeper connections and achieving improved business outcomes.

Learn more about Experimentation-in-personalization campaigns.