OpenText Core Case - Optimizely Integration and Automation

Common Integration Use Cases Between OpenText Core Case and Optimizely

1. Personalized Case Status and Self-Service Experience

Data flow: OpenText Core Case ? Optimizely

OpenText Core Case can send live case status, milestone updates, and resolution timelines to Optimizely so customers see personalized self-service content based on their case stage. For example, a claims customer logging into a portal can be shown relevant FAQs, next-step guidance, or escalation options tied to their specific claim type and status. This reduces inbound support volume and improves customer satisfaction by making the digital experience more relevant and transparent.

2. A/B Testing of Case Portal Content and Workflows

Data flow: Optimizely ? OpenText Core Case

Optimizely can test different portal layouts, help content, form designs, and call-to-action placements used in case submission or case tracking experiences. Performance data from experiments can be used to refine how users open, update, or resolve cases in OpenText Core Case. This helps teams improve completion rates, reduce abandoned submissions, and identify the most effective digital journey for customers and employees.

3. Personalized Knowledge and Guidance Based on Case Attributes

Data flow: OpenText Core Case ? Optimizely

Case metadata such as issue type, customer segment, product line, or compliance category can be passed to Optimizely to personalize content recommendations. For instance, a support portal can display targeted troubleshooting articles, product guidance, or policy reminders based on the active case context. This improves first-contact resolution and ensures users receive content that matches the exact nature of their request.

4. Conversion Optimization for Case Submission Forms

Data flow: Optimizely ? OpenText Core Case

Optimizely can be used to experiment with intake forms that feed directly into OpenText Core Case, such as claims, complaints, or service requests. Teams can test field order, required inputs, help text, and conditional logic to determine which version produces the highest submission completion rate and the cleanest case data. This reduces manual rework for operations teams and improves the quality of incoming cases.

5. Targeted Outreach for High-Priority or At-Risk Cases

Data flow: OpenText Core Case ? Optimizely

When OpenText Core Case identifies high-priority, overdue, or sensitive cases, that information can trigger tailored digital messaging in Optimizely. Customers or partners can be shown specific banners, reminders, or next-step content that encourages faster action, such as uploading documents or responding to a request. This supports faster case progression and reduces delays caused by missing information.

6. Experimentation on Customer Support Deflection Content

Data flow: Bi-directional

OpenText Core Case can provide case volume, issue categories, and resolution outcomes while Optimizely tests different support content strategies such as article placement, chatbot prompts, or guided troubleshooting paths. The combined data helps organizations measure whether optimized content reduces case creation or shortens resolution time. This is especially valuable for customer service teams looking to deflect repetitive inquiries without harming user experience.

7. Compliance and Regulatory Messaging Personalization

Data flow: OpenText Core Case ? Optimizely

For regulated industries, OpenText Core Case can pass case type, jurisdiction, or compliance status to Optimizely so the digital experience reflects the correct policy language and required disclosures. A compliance review case, for example, can trigger region-specific instructions, document requests, or legal notices. This helps ensure consistent communication while reducing the risk of users seeing irrelevant or non-compliant content.

8. Closed-Loop Optimization of Case Resolution Journeys

Data flow: Bi-directional

Optimizely can test different digital journey variants, while OpenText Core Case returns operational outcomes such as resolution time, reopen rate, escalation rate, and customer satisfaction. Together, the platforms create a closed-loop process for improving the full case lifecycle from intake to resolution. Business teams can use this feedback to continuously refine both the customer experience and internal case handling efficiency.