An American athletic footwear and apparel corporation significantly amplified their approach to efficiently managing their product web pages with robotic process automation.
SITUATION
Our client encountered inefficiencies in managing product images for their online store due to inconsistent file naming protocols from their suppliers. As a result of suppliers using inconsistent naming conventions, our client used a process of manually changing file names that was not only time-consuming but also often impacted the timely release of seasonal products in the online store. Leveraging our trusted partnership and strategic resource optimization from our Mexico Delivery Center, our client selected Everforth Apex as their exclusive technical partner for this budget-conscious project.
Robotic Process Automation Decreased Processing Time By 82% Within One Year
Our Robotic Process Automation (RPA) Development team crafted a forward-thinking solution to automate this labor-intensive process. By harnessing the power of Microsoft Power Automate cloud flow, we were able to significantly speed up renaming images — reducing it from five minutes to an average of 32 seconds per image. This process was essentially error-free and required minimal human intervention.
This automation strategy involved the creation of a bot that could intelligently store third-party seller codes along with our clients’ naming conventions. The bot was configured to operate within a specified folder structure, ensuring it could accurately rename products based on their image, correlating them to a cloud-based reference table for the correct product and vendor codes.
RESULT
The deployment of this automated solution has significantly improved our client’s approach to managing their product web pages. Key outcomes include time efficiency, risk mitigation, and operational streamlining. We achieved an 82% reduction in processing time per image, translating to a savings of four and a half minutes per image. This efficiency amplification allowed for the processing of 3,616 images over a year, saving an equivalent of 38 days of manual labor. The flawless execution of automation eradicated the risk of missing crucial deployment windows, ensuring timely content release aligned with the intended seasons. By transitioning to a 100% automated process, the need for manual involvement was eliminated.
