OpenText Core Experience Insights - Phrase Strings Integration and Automation

Common Integration Use Cases Between OpenText Core Experience Insights and Phrase Strings

1. Measure localization engagement across product content

Data flow: Phrase Strings ? OpenText Core Experience Insights

Send release, string update, and locale-specific content events from Phrase Strings into OpenText Core Experience Insights to measure how localized content changes affect user engagement. Product and localization teams can compare adoption by language, region, or release version to identify which translations or terminology choices improve task completion and reduce drop-off.

2. Identify underused translated features and content gaps

Data flow: OpenText Core Experience Insights ? Phrase Strings

Use usage analytics from OpenText Core Experience Insights to detect screens, workflows, or help content with low engagement in specific markets. Feed those insights into Phrase Strings so localization managers can prioritize missing translations, refine terminology, or assign review cycles to the content most likely to improve adoption.

3. Prioritize translation work based on actual user behavior

Data flow: OpenText Core Experience Insights ? Phrase Strings

Push interaction data such as feature usage, page views, and abandonment points into Phrase Strings to help teams rank translation backlog items by business impact. This enables localization and product teams to focus effort on high-value strings, customer-facing workflows, and regions where poor language coverage is affecting conversion or support demand.

4. Validate the impact of localized content releases

Data flow: Bi-directional

After a localization release is published in Phrase Strings, OpenText Core Experience Insights can track whether engagement, task completion, or retention improves for the targeted audience. Phrase Strings can receive the resulting performance metrics to support translation quality reviews and continuous improvement cycles, helping teams prove the value of localization investments.

5. Support A/B testing of translated copy and terminology

Data flow: Phrase Strings ? OpenText Core Experience Insights

Publish alternate translation variants or terminology sets from Phrase Strings and use OpenText Core Experience Insights to compare user behavior across versions. This is useful for testing button labels, onboarding text, help prompts, and error messages in different languages to determine which wording drives better completion rates and fewer support escalations.

6. Improve digital workplace adoption in multilingual environments

Data flow: Bi-directional

For internal portals, knowledge bases, or employee apps, OpenText Core Experience Insights can show which content employees use most by region or language. Phrase Strings can then be used to update or localize the most important internal content, while subsequent usage analytics confirm whether the changes improve adoption, self-service, and employee productivity.

7. Create a closed-loop content optimization process

Data flow: Bi-directional

OpenText Core Experience Insights identifies where users struggle, hesitate, or abandon tasks. Phrase Strings receives those insights to trigger translation updates, terminology corrections, or content rewrites. Once updated content is released, OpenText Core Experience Insights measures the effect, creating a continuous optimization loop for multilingual digital experiences.

8. Reduce support volume by improving localized self-service content

Data flow: OpenText Core Experience Insights ? Phrase Strings

Analyze which help articles, guided workflows, or in-app instructions are frequently accessed but still lead to repeated visits or exits. Send those signals to Phrase Strings so teams can improve the translated content, making self-service resources clearer and more effective. This can lower support tickets and improve customer satisfaction in non-primary languages.