Download PDF
For Guess, Cloudinary Eliminates the Guesswork in Delivering Optimal Shopping Experiences
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Apparel
Applicable Functions
- Sales & Marketing
- Business Operation
Use Cases
- Inventory Management
- Supply Chain Visibility
Services
- Software Design & Engineering Services
The Challenge
GUESS was relying on Adobe Scene7 to manage images for its online store. However, Scene7, a Flash-reliant product, made workflows and modern technology updates more challenging. With modern browsers phasing out Flash, GUESS developers struggled to deliver the high-quality web experience it wanted to offer customers. The system being used by GUESS was so volatile that it created regular bottlenecks. Image uploads would fail, photo editors would have to crop photos with extra white space to ensure they’d appear appropriately on the site. Sometimes images wouldn’t look as crisp and high-fidelity as the original once they rendered on the web. These challenges weren’t just a big deal for the development team. They frustrated potential customers as well. Heavier images meant slower page load times, and unnecessary bandwidth usage by visitors.
About The Customer
GUESS? Inc. designs, markets, distributes, and licenses a lifestyle collection of contemporary apparel, denim, handbags, watches, eyewear, footwear, and other related consumer products. GUESS products are distributed through branded GUESS Stores, as well as department and specialty stores around the world, and via e-commerce sites available to 55 countries. GUESS websites act as virtual storefronts that both sell their products and promote their brands. These sites showcase GUESS products in an easy-to-navigate experience, allowing customers to see and purchase from its collections of apparel and accessories.
The Solution
GUESS did a global migration, replacing Adobe Scene7 with Cloudinary within its workflow. Once images are shot in the GUESS photo studio or created in Photoshop, they’re easily uploaded in bulk via FTP directly to G-Image—a custom, homegrown solution that, via APIs, acts as a conduit to Cloudinary. This process allows images to be sorted and labeled properly. Then using Cloudinary automation to adjust image URLs, GUESS is able to ensure that all images are optimized for size, format, and render properly, regardless of the device or browser. GUESS uploads a single version of each image and uses Cloudinary to automatically scale images based on viewport, browser, and other factors without much manual intervention. This is much easier than the previous solution, which required extra steps from the photo studio, such as custom cropping and padding, to ensure images displayed properly.
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
Fire Alarm System and Remote Monitoring Sytem
Fire alarm systems are essential in providing an early warning in the event of fire. They help to save lives and protect property whilst also fulfilling the needs of insurance companies and government departments.Fire alarm systems typically consist of several inter-linked components, such as smoke detectors, heat detector, carbon monoxide, manual call points, sounders, alarm and buzzer. The fire alarm system should give immediate information in order to prevent the fire spread and protect live and property.To get maximum protection a shoe manufacturer in Indonesia opted for a new fire alarm system to monitor 13 production sites spread over 160 hectars. Although the company had an existing fire alarm system, it could not be monitored remotely.It was essential that the new system would be able to be monitored from a central control room. It needed to be able to connect to the existing smoke detector and manual call point. Information should be easily collected and passed on to the Supervisory Control and Data Acquisition (SCADA) system. Furthermore, the system should have several features such as alarm management, auto reporting, being connected to many client computers without additional cost, and run 24/7 without fails. The company also needed a system which could be implemented without changing the architecture of the existing fire alarm system.
Case Study
IoT Applications and Upgrades in Textile Plant
At any given time, the textile company’s manufacturing facility has up to 2,000 textile carts in use. These carts are pushed from room to room, carrying materials or semi-finished products. Previously, a paper with a hand-written description was attached to each cart. This traditional method of processing made product tracking extremely difficult. Additionally, making sure that every cart of materials or semi-finished products went to its correct processing work station was also a problem. Therefore, the company desired an intelligent solution for tracking assets at their factories. They also wanted a solution that would help them collect process data so they could improve their manufacturing efficiency.
Case Study
Retailer Uses RFID Scanner to Improve Efficiency
Patrizia Pepe wished to improve the logistics of their warehouse: accepting incoming goods from their production sites, movement of items throughout
the warehouse, and packaging of goods for distribution to the retail locations. They initially tried to use barcodes for this function. Because barcodes must be individually scanned within a line-of-sight, the acceptance of goods coming into the warehouse was too time consuming. Working with the University of Florence, Patrizia Pepe instituted a five-month pilot project beginning in August of 2009 to test the validity of an RFID solution. The pilot involved tagging of about 60,000 items for the second seasonal collection, and convinced the company to move forward with tagging all items.
Case Study
Monitoring and Controlling Automatic Mixing and Dispensing Machines
As technology advances, textile manufacturing has been transformed from a labor-intensive to a partially or fully automated industry. Automation is significant in all segments of textile production - from spinning to printing, and textile machinery manufacturers are constantly searching for new technologies and automation processes will increase the productivity of their machines. The color paste mixing and dispensing machine is an essential part of the printing and dyeing process. With the advantage of automatically computerized controls and database management, the system can significantly improve its dispensing precision, working efficiency and production quality as well as reducing material consumption.