Nano Insights market data dashboard overview

Case study / 2023

Nano Insights

Visualising data for the UK’s largest bank.

Team

Design lead & project manager

Development team, Pune

Client account managers and analysts, Hong Kong

Background

Nano Insights is a confidentiality alias for a marketing and insights company. Its detailed survey data was presented through PowerPoint and Excel, making it cumbersome to explore and limiting interactive decision-making for a major banking client.

Visualising data for the UK’s largest bank.

01 / Navigating clarity

Navigating clarity.

The product began as PowerPoint and Excel sheets, which made navigation difficult. We organised the dashboard into four key sections, with three mirroring familiar parts of the earlier product.

02 / Dashboard interaction

Dashboard interaction.

The left navigation block became the central hub for markets. Each dashboard used a top-to-bottom filter hierarchy, while colour and opacity helped users find and stack relationships without losing the overall view.

03 / Bar charts

Bar charts.

Bar charts were used to show relationships between a limited number of data points and markets. Their simplicity made straightforward connections and associations easy to read.

04 / Stacked bars

Stacked bar charts.

Stacked bars added another layer of comparison, showing multiple attributes within a market and the composition of each market response.

05 / Scatter plots

Scatter plots.

Scatter plots gave an overarching view of market trends across multiple markets. Paired with a dual axis, they revealed broader relationships while keeping finer detail available for closer analysis.

06 / Radial charts

Radial charts.

Radial charts were used for data points that add up to a fixed total. Concentric circles made percentage breakdowns and comparisons between markets easier to understand.

07 / Bubble charts

Bubble charts.

Bubble charts visualised relationships across X, Y, and Z axes. Each visualisation style was planned with the data-processing team and Power BI developer so it could translate into a functional model.

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