Scaling Teams Through Data-Driven Decisions
Objective
To equip IBM’s UX research teams with robust data instrumentation and actionable insights, bridging qualitative research with behavioral data to optimize user experiences across cloud platforms.
Challenge
- Fragmented data insights due to poor instrumentation and disconnected tools.
- Outdated user personas leading to misaligned product roadmaps.
- Complex and siloed workflows, reducing cross-product collaboration.
Approach
Establishing a Jobs-To-Be-Done Framework
Defined a JTBD framework to prioritize user goals and challenges, aligning teams with key opportunities for improvement. This provided a shared understanding across development, design, and research teams.
Enhanced Behavioral Analytics Using Instrumentation
Partnered with data scientists to deploy advanced analytics using data collected via Amplitude and other tools. These analysees provided actionable insights into behavioral data, enabling teams to uncover user pain points and track flow optimizations.
Cross-Team Bootcamps
Facilitated UX research bootcamps to align product teams on a unified vision, fostering collaboration and breaking down silos. These workshops helped integrate behavioral insights into roadmap planning.
Results
Revised Personas and Roadmaps
- Roadmaps now reflect diverse user needs, improving user satisfaction metrics by 40%.
- Cross-team collaboration led to more cohesive feature rollouts.
Enhanced Conversion Rates
- 25x improvement in Blockchain provisioning workflows, boosting conversion rates to 2.5%.
- Behavioral insights directly informed design optimizations.
Conclusion
This case study highlights how data instrumentation and user-centered frameworks transformed cross-functional collaboration and user experience outcomes at IBM. By redefining personas and aligning teams, we achieved tangible results in conversion and satisfaction.
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