Context
GfK founded in 1934 in Nuremberg, Germany, is a global leader in market research and consumer insights. GfK - Newron is a next-generation predictive analytics platform designed to transform how businesses access, understand, and act on data insights. As GfK transitions from traditional consultancy-driven model to scalable SaaS solution, there is a growing need for a faster, more intuitive, and self-serve experience.
Outcome
The recommendation experience has been optimized by reducing user steps by 1.5 and seamlessly surfacing insights during the explore phase. Task-based testing showed a significant decrease in completion time from 2:46 to 1:00 minutes, demonstrating improved efficiency. Early feedback from potential customers has been positive, with excitement about the tool’s capabilities. However, we learned that data quality and accuracy remains a key concern for our customers.
Reducing
Cognitive Load.
We improved workflow efficiency to enhance legibility and provide faster access to data insights.
Enhanced content hierarchy providing insights in a systematic method e.g. show high level proof, if customer requires more context we can drill deeper into more evidence of this recommendation.
Optimising
Workflows.
Customers struggled to quickly find useful recommendations and take action based on insights, so we streamlined decision-making for a faster, more efficient experience.
The paradox of choice: The previous 4x4 grid view forced users to switch pages for more details—an inefficient workflow that didn’t align with their need for quick scanning and immediate action.
Ensuring
Consistency
To ensure consistency and scalability, we developed a 52+ component system and a component library to maintain design quality across all touch-points.
Further concepts were explored through Apple Watch prototypes, aiming to enhance data accessibility on the go.
Building
Trust.
To continue building trust with our customers, we developed feedback loops, and a prediction score to ensure we continuously improve data accuracy and usefulness.
Probability scores are based on historical data and predictive modelling. These scores are a measure used to assess the likelihood of a positive event occurring.
A feedback widget collects user ratings and comments with minimal effort, providing insights without disrupting the customer journey.