Experience Analytics

Experience Analytics are crucial for understanding user interactions with content and enabling data-driven personalization. By collecting and analyzing user data, you can uncover behavior, preferences, and motivations, allowing for targeted experiences that boost engagement, conversions, and overall business success. You can use experience analytics in Contentstack Personalize to improve your content personalization strategies by:

• Identifying high-performing content: By analyzing user engagement metrics, you can pinpoint which content resonates most with your audience and personalize experiences by recommending or promoting similar content to individual users.
• Understanding user preferences: Analyzing user interactions with different content types, formats, and topics can reveal valuable insights into their preferences. This information can be used to tailor content recommendations and personalize the overall user experience.
• Optimizing content for different audience segments: By segmenting your audience based on demographics, behavior, or other relevant criteria, you can use experience analytics to understand the unique preferences of each segment and personalize content accordingly.
• Testing and refining personalization strategies: Experience analytics allows you to experiment with different personalization tactics and measure their impact on user engagement and conversions. This data-driven approach helps you continuously optimize your personalization strategies for better results.

Segmented Experience Analytics

For Segmented Experiences, analytics track and display only impressions when activated.

A/B Test Experience Analytics

For A/B Test Experiences, analytics track and display impressions and conversions when activated.

Minimum requirements to calculate insights

Once the A/B Test experience is activated, we wait for one of the following conditions to be met before calculating insights:

• Either a total of at least 1000 impressions across all variants
• Or at least 30 conversions across all variants.

Once either condition is satisfied, users can access near-real-time summary reports and insights to identify the best-performing variant

The A/B Test Leader Determination Logic

The A/B Test Leader Determination Logic is a systematic method for identifying the winning variant in an A/B test. It starts by defining clear objectives and key performance indicators (KPIs). Currently, Contentstack Personalize uses the "probability to be best" insight to determine a winning variant.

Variants are then tested on a similar audience segment, and data is collected over a set period. Statistical analysis compares each variant's performance against the control group, considering factors like statistical significance and confidence intervals. The variant that best meets the KPIs is declared the leader, enabling data-driven decisions that enhance personalization strategies.

We employ the following conditions to determine if the currently leading variant can be declared winner:

• The probability to be best of the leading variant is >= 95% AND
• At least 14 complete days have passed since the A/B Test version was first activated.