CA Technologies Mobile App Analytics

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Overview of the project

CA Technologies came to Bletchley Park for help designing and building their Mobile App Analytics (MAA) product, a mobile delivery analytics tool for enterprise-scale customers such as Verizon Wireless. Unlike existing solutions, MAA needed to scale easily to support an unlimited number of apps and app versions, with both global and app-specific performance and usage instrumentation and monitoring. The timeline was tight, with the goal of developing a prototype to be shown at

Mobile World Congress in 2014 just 3 months later. Bletchley designers were working directly with CA stakeholders from the start. We burned through a huge amount of work in a short period, and the initial demonstrations of a prototype went exceptionally well as a result. That kicked off an 18-month engagement, as Bletchley took the MAA product through several releases, and provided a solid design direction for its future evolution.

Partner Vendor Relationship

A key to the process was working with an engaged and knowledgeable stakeholder. By partnering with CA and encouraging regular participatory feedback, Bletchley was able to interpret the original concepts and focus on designing and delivering the product that was needed, filtering our experience through their domain expertise.



Performance Map

Moving from a pin based (single metric) map, to a heat based (multi metric) map, users can easily determine both positive and negative areas of usage, performance, and problems at a glance.

Surfacing Problems

Rather than show a basic list of recent problems, we switched to a dynamic list by app, by problem type. Users can spot trends over a period of time quickly.

Collaborative Front-end Development

Our designers and engineers integrated with the CA user interface development team. We were able to iterate rapidly, and refine the product through multiple incarnations with the active participation of product stakeholders.

Collaborative Front-end Development

Design-Driven API Development

Starting with the raw data and a vision of the desired user experience, Bletchley’s design engineering team worked with the back end team at CA, evolving their existing APIs to support the powerful visualizations desired for MAA.

Design-Driven API Development

Continuous Feature Evolution

Unlike most app analytics tools on the market, MAA allows users own and track multiple mobile apps instead of just one. Communicating application context and allowing for analysis across multiple applications were unique UI requirements. We proposed a filter authoring tool that allowed users to specify not just the app, but various other parameters including platforms, devices, carriers, and locations.

Revision 1

Initial Design

Initially filters were conceived as tabs below the main navigation, to allow quick switching between different filters. This was somewhat awkward in practice, however, and took the user out of the page they were on to make changes to a filter. It also wasn't quite structurally correct, since filters persisted across all sections in the navigation.

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Revision 2

Feedback Turned Into

We moved filters to the top level and made filter selection an overlay panel. This immediately increased user understanding of what filters are and how to use them. We maintained the ability to quickly switch between filters by introducing Saved and Recent filters.

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Revision 3

Final Product

Over time the number and complexity of filters continued to expand, so we redesigned the filter panel to allow for any number of filters that now could have multivariate definitions (rather than a simple single list of options).

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Sophisticated UX

Our team is uniquely capable of synthesizing concepts and raw data into a vision for product user experience. The Bletchley team's integration of design and engineering allows rapid feedback between disciplines to arrive at the best implementation.

Screen Detail

Screen Detail
Screen Flows

We show which screens users arrive from, and where they go next

Tap Points

Heatmaps show where users interact with each screen

Usage Metrics

We included both visual representations and hard numbers

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