JATO are the market leader in automotive data. As part of their growth strategy, they wanted to reframe their relationship with customers from ‘data supplier’ to ‘insight partner’.
This meant a large transformation project to radically improve data quality, self-serve options and develop a new suite of best-in-class insight tools dubbed Jato-as-a-Service (JaaS) on a new delivery platform.
Our team has been embedded in their business for over 1 year to deliver parts of this transformation, focusing on UX strategy of the products and building the UI presentation layer that integrates with the backend services.
JATO serves distinct audiences, from dealers to OEMs to Town planners, who only want to see the data that is relevant to them. The key challenge was making their data insightful, actionable and useful to the people that mattered – even when self-serving.
This means we had to simplify large, unstructured data sets into beautiful, intuitive user interfaces, similar to the quality of a consumer-based product. Our solutions had to be fully scalable, flexible, and ready for future product and service development.
A universal React.js-based Component system
One of the most important parts of the JaaS platform is a consistent design and component system. We developed an atomic design system and react.js component library for JATO, which reflects their brand experience guidelines, and enables their in-house teams to roll out new products and services in a consistent way.
Dealer Value Exchange
Dealers are under pressure – they have 90 days to sell a car on their forecourt before they have to buy it themselves, which inevitably leads to discounting and loss of margin.
This means predicting popular models, colours and option packs is business critical. To assist, we developed Jato Dealer Value Exchange, an insight platform that give dealers the ability to upload their own sales data and benchmark it against competitors, thanks to clever normalization processes. Crucially, this allows dealers access to the slice of JATO’s vast data universe that’s relevant to them.
Vehicle Research Tool (VRT) and Feature Based Research Tool (FBRT).
The core of JATO’s business is data capture – they have researchers on the ground all over the world logging car specs to bring their customers the most accurate data in the industry.
However, this process was previously time consuming and manual, using a slow and clunky desktop app, introducing inevitable human error. So, we turned this into a simple, intuitive and responsive app to allow researchers to capture data in the field, enhancing data quality and creating huge efficiencies by automatically normalizing unstructured data.
We provided high-level and solution architecture designs utilizing Identity server for authentication, Squidex for headless content management and a BFF all built in Microsoft Azure with React-based Single page applications for the Front end. React.js style components were built and storybook was utilised for testing and serving as JATO’s component library explorer. Azure DevOps was utilised to CI/CD tasks and pipelines.
Ways of working
JATO uses the Scaled Agile framework (SAFe) to deliver products and technology objectives, Omobono joined as a team within this framework, alongside 8 others around the world. Omobono took part fully in PI planning and all the SAFe ceremonies.
#1First JATO web application to market using the new JaaS platform
100%Adoption by the JATO research community
100%consistency of data entry within the first month
FBRT enables digitisation of our market research model and data management capabilities to deliver our core brand value of ‘Precision under pressure’ in a more accurate, scalable and dependable way.
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