Self-Service Benchmarking
Context
The SiriusDecisions Command Center® is a robust self-service benchmarking platform that was created to help B2B clients understand how they compare to their peers and make data-informed business decisions. The platform was built using client data that the company’s benchmarking analysts had been collecting for over 15 years.
Problem
The continued accuracy of the benchmark data relies heavily on users interacting with the platform and submitting their data. However, the platform was incredibly complex and overwhelming to a new or infrequent user. The SiriusDecisions Command Center® was being underutilized and its value was diminishing as its data was becoming outdated.
Goal
The objective was to create an entry point with a decreased learning curve to self-service benchmarking in order to increase adoption.
Process
Customer Interviews
Stakeholder Interviews
Affinity Diagramming
Journey Mapping
Competitive Analysis
Solution Sketching
UX Storyboarding
Wireframing
Prototyping
Concept Validation
Usability Testing
Tools
Miro
Sketch
InVision
Keynote
Powerpoint
Role
UX Design
UI Design
UX Writing
The Solution
Recommendations tailored to the user
The landing page encourages exploration without the upfront investment of learning complex software.
First-time users are shown the metrics with the highest chances of prompting an initial engagement that will capture enough data to serve up personalized content.
Metrics that are popular amongst a user’s peers are recommended to ease the burden of identifying metrics they should be tracking to be successful in their role.
Simplified data entry
Expandable cards help users validate their choice at a low interaction cost, while minimizing cognitive load.
The modal’s simplified entry point allows for comparison to be done as a quick, focused task, with the option to do a more advanced analysis within the benchmarking platform.
While there is an option to enter your data for comparison, peer data is not gated in order to ensure users experience the core value of the product as quickly as possible.
Metric collections that tell a story
Correlated metrics are presented as a set to help users better interpret the data.
Comparing a group of related data simultaneously produces faster results.
Users can easily leverage benchmark data by exporting their results as PowerPoint slides.