GOODYEAR CASE
IMPLEMENTED UNDER WHITE LABEL
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the client
Goodyear - The world leader in the production of car tires, which includes a huge number of brands of car tires, such as Total Tiers, Dunlop and many others.
The company has a huge network of branded tire services throughout Australia. We were hired to fully automate the process of registering for a service, selecting and selling tires, as well as organising a loyalty system. Adobe Commerce platform was chosen as one of the most reliable and scalable platforms meeting all clients needs.
Tools and integrations
is a data management system. Since the website is designed with multiple different integrations with all kinds of different data sets it was decided to use Keboola which can source raw data from different systems and process it into a structured database. It was used for DWH, Costar, VL, and SFSC integrations
is used by the client as a CRM, so it had to be implemented to share data both ways from website to system and from system to website. SFSC APIs were implemented to push Customer and Vehicle data from Adobe Commerce to SFSC and from SFSC to Adobe Commerce. A RabbitMQ will be used to call the API.
is an ERP software, specifically catering to the automotive industry. It is used as the POS system for Beaurepaires retail locations. Costar APIs are used to maintain stock levels in Adobe Commerce, and sync orders from Adobe Commerce to Costar. Costar is used as the master record for STORE stock levels while DWH is the master record for WAREHOUSE stock levels. Both platforms are utilised to provide warehouse stock data to Adobe Commerce. DWH provides Warehouse data to Adobe Commerce, and Costar provides Store data to Adobe Commerce by calling a Costar API and updating stock data in an Adobe Commerce custom table (same table as DWH Warehouse data). Costar is also used for Stock Management (Stock on Hand) Order Sync Once an order is created in Adobe Commerce, the order information needs to be sent to Costar. A RabbitMQ is used to call an API.
A system used by the company to source vehicle and product data. Vehicle data provides the Recommendation Engine with [year] [make] [model] [series], provides some product data (not full, only for matching) including fitment options for each vehicle, OE fitment options, and Rego / Number Plate. VL also provides images for Wheel Visualizer. The client had a preference to cache data and images locally (where appropriate) for performance reasons, however, some real-time VL API calls still are necessary.
A system used by the company to manage multiple data sets, including Customers and Products. No direct integration between Adobe Commerce and DWH was done, only SFTP Database updates. The database updates both ways, from website to system and from system to website, and includes product creation and maintenance, stock data maintenance, syncing invoice data (from Costar), store maintenance, and Recommendation Engine data.
Effective design focused on the selection of product and service.
A team of designers and engineers has developed a unique website design, which includes both standard e-commerce functionality and unique functions for selecting the appropriate product along with the service, which fully complies with all UX best practices (trends for the best conversion, convenient and intuitive navigation, highlighting the most necessary functionality on relevant pages) and market requirements.
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Development of a management system for a network of
service stations
Since the main task of the website was not so much the sale of products, but the management of the work of service stations, and since the purchase of a product on the website without registering for a service was not supposed, our team had to split the task into two parts:
We developed an online JS calendar system from scratch, which had a separate interface for the management of each individual service station, as well as a separate interface on the site for customers, which allows online registration for the service after making a purchase.
We have completely rebuilt the checkout so that at the end the customer receives a list of requested products waiting for him at the selected service station, along with an appointment for the service.
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Smart selection of products of each
of the presented categories
- For the selection of car wheels, a system called the Wheel Visualizer was developed. This functionality made it possible to visualise any of the car wheels presented on the site installed on a customer's car.
- For the selection of tires, a system called Recommendation Engine was developed. The system allowed the customer to select the most suitable car tires based on the make and model of the car, driving style and usage environment. The flexibility of the system allowed the client to update rebound data by adding new data to the database.
- The functionality of selecting car batteries was achieved through integration with the national database of recommendations from all car manufacturers officially represented on the Australian market.
The smart review system
The necessary functionality was built on the basis of several integrations - HotJar: a smart system for tracking the customer behaviour on the website, combined with a Trustpilot: feedback service, which accumulated reviews about a particular product from many sites and services.
Quality assurance
The QA team carried out full testing according to a pre-developed test plan. Manual testing of the entire front functionality was carried out, including the customer journey, Recommendation Engine, Wheel Visualizer, Service station calendar interface, and data exchange systems. Autotests were written and implemented to test integrations and functional code. At the end of the implementation of each individual functionality, as well as at the completion of work on the entire system, full regression testing was carried out.
