LexisNexis Risk Solutions: Facilitating a Seamless Migration from Product A to Product B

Project Overview

Overview

The research aimed to understand the challenges and opportunities associated with migrating internal users from Product A to Product B. This study focused on user sentiment, training needs, and key motivators for adoption, helping to refine the migration strategy for future phases.

Problem Statement

Internal users expressed concerns about data discrepancies, training gaps, and limited access to support when transitioning from Product A to Product B. Despite both platforms sourcing data from the same provider, inconsistencies in data accuracy and presentation created confusion, raising doubts about migration feasibility.

Research Objectives

User Sentiment & Readiness: Can internal users navigate Product B with minimal support, and how do they feel about the migration?

Training & Support Needs: What kind of education, onboarding materials, and guidance do users require?

Motivators for Migration: What factors would encourage users to transition to Product B seamlessly?

My Role

As the Lead of this project, I:

✔ Designed and executed the research study, incorporating usability testing, user interviews, and sentiment analysis.

✔ Synthesized key findings to identify data accuracy issues, training gaps, and user concerns about search usability.

✔ Collaborated with product managers, engineers, and training teams to develop targeted recommendations for platform improvements.

✔ Advocated for implementation of a Chatbot, improving support accessibility, which was successfully adopted.

✔ Measured user satisfaction post-migration, demonstrating an increase to 80% satisfaction in Phase 2, which enabled us to move forward with Phase 3 (Voluntary Migration).

Research Approach

Methodology: Mixed-methods research including interviews, usability testing, and sentiment analysis.

Participants: Internal users of Product A who would transition to Product B.

Data Sources: Prior insights from NPS surveys, usability feedback, and real-time observations during platform testing.

Key Findings & Insights 🔎

1. Data Accuracy & Presentation Needs Improvement

Users observed data discrepancies between Product A and Product B, despite data being sourced from the same provider.

Some critical data fields were missing or incorrect in Product B, raising concerns about reliability.

Recommendation: Investigate and synchronize data presentation to minimize confusion and improve trust.

2. Training & Onboarding Gaps

Users need structured training materials to navigate Product B effectively.

Preferred formats:

Video tutorials
Interactive tours highlighting key features
Search optimization help guides

Recommendation: Develop diverse training materials that cater to different learning styles and user needs.

3. Search Usability & Interface Enhancements

Users struggled to distinguish between different search options (e.g., IBAN Complete vs. IBAN).

Recommendation: Provide clear tooltips and onboarding messages to differentiate search functionalities.

Additional Enhancement: Adopt a color scheme that highlights searched keywords, improving search experience.

4. Need for Easy Access to Support

Users found help and feedback options difficult to locate in Product B.

Screenshot analysis revealed that most participants overlooked the existing Help/Feedback section.

Recommendation: Improve visibility and accessibility of support channels, such as:

Chatbot (NEW)
"Help" or "Contact Us" buttons prominently placed in the UI.

💡 Implementation Success:

One of the key recommendations that was successfully adopted was the integration of a Chatbot on Product B. This real-time support tool now provides instant answers to common user queries, significantly improving the user experience and reducing dependency on human support.

5. Migration Sentiment & Motivators

Most participants were confident in migrating to Product B, provided that:

Data quality improves
Sufficient training is provided
Support is more accessible

Opportunities for Incentives: Users suggested adding:

Early-adopter rewards
Exclusive features for first adopters

Impact & Business Value

1. Increased Satisfaction Leading to Phase 3 Migration

📈 User satisfaction increased to 80% in Phase 2, giving us confidence to move forward with Phase 3: Voluntary Migration.

2. Data-Driven Migration Strategy

📊 Findings from this research directly informed the phased migration strategy, ensuring that support systems and data accuracy issues were addressed before moving into voluntary adoption.

3. Improved Training & Support Accessibility

🎯 Developing structured onboarding resources and implementing a Chatbot for real-time assistance.

4. Path to Full Adoption

🚀 The voluntary migration phase (Phase 3) will be followed by the sunsetting of Product A in the second half of the year, leading to a final forced migration of all users.

5. Defined Key Success Metrics for Phase 3

📊 To ensure a smooth voluntary migration, we established KPIs to track adoption, engagement, retention, and satisfaction. These success metrics provide data-driven insights into user behavior and help refine future migration strategies before moving into the final forced migration phase.

📍 How We’ll Measure Success:

Increased adoption & engagement → More users completing registration and actively using key features within 30 days.

Higher retention rates → Majority of users transitioning to Product B as their primary tool, reducing reliance on Product A.

Data-driven decision-making → Using FullStory, analytics tracking, and survey insights to refine the final forced migration strategy.

Recommendations & Next Steps

1. Address Data Discrepancies

✅ Investigate missing or incorrect data fields in Product B.

✅ Implement consistent data synchronization between platforms.

2. Optimize Search Usability

✅ Differentiate search functionalities with clear explanations.

✅ Implement color coding for search results.

3. Improve Training & Onboarding

✅ Develop video tutorials, interactive guides, and structured help documents.

✅ Personalize training based on user experience levels.

4. Enhance Support Accessibility

✅ Improve Help & Feedback visibility.

✅ Continue monitoring Chatbot engagement for further refinements.

5. Conduct Phase 3 Voluntary Migration Study

✅ Track adoption preference rates as we transition to voluntary migration.

✅ Prepare for final forced migration phase in the second half of the year.

✅ Monitor key KPIs to measure success, including:

📌 Adoption & Engagement Metrics

Migrated User Registration Completion: Number of users who complete the registration process in the new application. (Tracked via registration logs)

Feature Adoption within 30 Days: Number of migrated users actively setting up/using key features in Product B (e.g., IBAN Complete, core tasks previously done in Product A). (Tracked via FullStory event monitoring and backend logs)

Search Activity Comparison: Average number of searches per migrated user in Product B vs. Product A. (Tracked via FullStory)

Primary Tool Usage: Percentage of migrated users using Product B as their primary tool (e.g., using it >80% of the time). (Tracked via user session tracking in FullStory)

📌 Retention & Churn Metrics

Churn Rate Post-Migration: Number of users who stopped using Product B after migration, categorized by their previous activity level (active/inactive in the past 12 months). (Tracked via user activity logs)

User Retention Post-Migration: Percentage of users who stop using Product A within 60 days of migration. (Tracked via login and usage analytics)

📌 User Sentiment & Satisfaction

Net Promoter Score (NPS) for Migrated Users: NPS scores split by users who prefer Product A vs. those who prefer Product B. (Tracked via post-migration NPS survey)

Conclusion

This research played a critical role in shaping the migration strategy for internal users moving from Product A to Product B. By addressing data concerns, usability challenges, and training gaps, we ensured a smoother transition with minimal disruption.

📊 Key Outcomes:

User satisfaction increased to 80% in Phase 2, validating our approach.

Successful implementation of a Chatbot, reducing reliance on human support.

Clear path to Phase 3 (Voluntary Migration) and eventual sunsetting of Product A.

Moving forward, ongoing user engagement and data-driven refinements will ensure a successful full migration to Product B by year-end.