G-Star RAW: Optimizing its omnichannel sales strategy with Google Cloud

Founded in 1989, G-Star RAW is a global denim brand that became known for their unique take on raw denim, a type of denim that is unwashed and untreated. Inspired by military uniforms and vintage workwear from around the world, its clothing lines—as well as its accessories and shoes,—push the boundaries of design by placing innovation, sustainability, and creativity at their core. By challenging the norms of the industry, G-Star RAW's trailblazing style has gradually spread worldwide. The company has more than 4,500 points of sale around the globe, with flagship stores in New York, Paris, Tokyo, and even Shanghai.

Understanding customers better to develop online and omnichannel commerce

"The omnichannel focus is very relevant" says Cezary Skrzypek, BI and Data warehouse manager for the company, "To support this omnichannel strategy, understanding our customers and their behaviors is crucial."

Utilizing data to optimize the company's direction and maximize sales is not a new concept for G-Star RAW. The company already has a data warehouse and numerous dashboards used by the different parts of the business. However, this existing solution was somewhat dated: rigid and technologically out of date, it did not provide G-Star RAW with the complete customer 360 view and the possibility of advanced predictive analytics and integrated AI projects needed to expand its online sales. "We had neither the complete set of indicators nor the full client understanding we needed to formulate an effective strategy, and our previous solution was not able to perform the analyses we required," explains Cezary Skrzypek. "Rather than adapting this previous solution, which would have entailed significant investment in terms of hardware and software, we opted to start from scratch and set up an open and flexible infrastructure designed to suit modern data usage. After comparing different solutions, we chose Google Cloud, simply because it offered the most advanced technology on the market."

Leveraging BigQuery's strength, scalability, and flexibility

In practice, G-Star RAW had some limitations with its previous on premise infrastructure. To fully understand its customers, the company needed to integrate new data sources from social media, as well as from analysis tools such as Google Analytics, and even from the marketplaces it used. Its old data warehouse, which used SQL technology, did not allow such heterogeneous and partly semi-structured data. "Even if that had been possible, we were not sure whether we were getting quality data using the processes in place, nor would it have been possible to perform integration and analysis in real time," Cezary Skrzypek points out. "Our goal was specifically to be able to ingest large volumes of data in real time, so that we could obtain indicators as quickly as possible to adapt our recommendations and, more generally, our product range to suit our customer profiles. Google Cloud, and in particular BigQuery, excels at ingesting large volumes of heterogeneous data and is easily scalable."

New indicators up and running in no time

As opposed to the "big bang" approach, G-Star RAW opted for a step-by-step process, focusing first of all on the analyses it needed to optimize its online sales strategy. The company then began interfacing its Order Management System (OMS) with the new data architecture on Google Cloud, to allow it to access all the information relating to online sales (from acceptance of an order through to inventory management and right up to delivery) in BigQuery. It then integrated all of its new data sources, including social media and Google Analytics. "We are now able to analyze data more efficiently and in more depth, such as measuring the effectiveness of our marketing and advertising campaigns at a much more detailed level," says Cezary Skrzypek.

G-Star RAW has been building on its new architecture ever since. Data from in-store cash registers were the first to be added to BigQuery, allowing the company to analyze sales by channel. Integration of data from the ERP system (SAP) using the Google Cloud Cortex framework is still ongoing. "Cortex's predefined models for SAP significantly sped up the implementation of new indicators," Cezary Skrzypek points out. Finally, G-Star RAW also utilizes Cloud Composer managed services (workflow orchestration) to handle its data flow, and Google Cloud Functions (FaaS) to recover data using APIs.

A modern, scalable, and very affordable data platform

The project, which began in 2021, is far from over. As Cezary Skrzypek points out, "A data project can never really be completed. We are continuing to supplement our new data warehouse in BigQuery all the more easily because the Google Cloud ecosystem is very powerful and boasts all the features needed for integration and analysis. As a result, everything goes much faster."

After setting up some indicators that it couldn't access with its old infrastructure, the company is now tackling the gradual decommissioning of the SQL database it was using for its data warehouse, as well as its old dashboards, to rebuild them in Google Cloud.