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A leading lifestyle retailer enhances its catalog quality by 50% with an automated product data feed solution

About the client

The client is a family-owned and operated retailer with locations across Montana, Idaho, and Washington. In addition to having an online shopping platform, the client has twelve stores, bringing convenience to its loyal customers since 1997. The high-quality products usually cater to a country-side lifestyle and are designed with durability in mind. The client is well-known for its brand credibility and product quality. Even though the client carries over 3,500 brands under its name, it believes in gauging the true performance of all its products before promoting them.

Business challenge

The client constantly aims to deliver value in serving its customers, thus earning their trust. Most of the client’s business is generated through its e-commerce platform. Hence to sell its products wherever its customers were, apt creation and maintenance of product data feeds was imperative.
The client was manually building its product/catalog feeds and submitting them to the various recipients or third-party platforms such as sales and marketing, CRM, product information management, and customer engagement platforms, to name a few. These recipients were called ‘subscribers’.
However, manually building and maintaining numerous product/catalog feeds of over 1,20,000 products under 3,500 brands was error-prone andhad a very high turnaround time . Several product/catalog feeds were assembled independently through APIs or SQL. Each feed had a different method of formatting the data with regard to the requirements of a subscriber. This caused data mismanagement and created an immense load on its existing server.
Being a forward-thinking company, the client identified the need to reimagine its online business operations to enable speed and accuracy. The client decided to build a standardized product model. With only 1,100 employees, the client wanted them to spend significant time on strategic initiatives rather than managing product/catalog feeds. Hence, the client aspired to develop an automated system to supply product/catalog data to different subscribers.

Trigent solution

To ensure uninterrupted functioning of its team, the client partnered with Trigent. The team judiciously participated in a knowledge transfer effort to understand the company’s existing interfaces and processes. Leveraging Trigent’s Application development expertise, the client developed an automated product data feed solution aligned with the client’s business requirements.
The data feed application was built leveraging the MERN stack (Mongo, Express, React, Node) and was hosted on MS Azure. The team developed a user interface leveraging React, whereas the backend framework was built leveraging Node.js.
An interface using RESTful APIs was built to edit numerous URL paths that were, in turn, uploaded to Fastly.
The team developed a product/catalog database leveraging MongoDB. The data was extracted from the client’s server and stored in this database.
Furthermore, several templates were developed for publishing the catalogs in different formats. These templates were mapped to the individual subscribers, which would be published at scheduled intervals leveraging Azure Webjobs.

The client could schedule delayed repeatable callbacks based on configurations by using Redis. The completely configurable data feed solution enabled the client to:

Sync specific product/catalog information manually.
Actively monitor the progress and status of over 1 lakh data feeds
The robust system enabled the client to generate customized reports with regard to location-specific performance and employee database, to name a few, and make informed decisions. Power BI was used to generate customized reports. Furthermore, the team facilitated the audits of the process with logs of all ongoing activities.

Client benefits:

The completely automated product data feed solution was able to function independently without any human intervention and led to the following:

Technology stack: