Designing prints, measuring consumer acceptance, and identifying emerging trends are complex tasks, but artificial intelligence (AI) tools like ChatGPT have been rapidly gaining popularity among companies looking to streamline their processes. Mango is one such company that recognizes the value of AI and has incorporated it into their operations.
The Spanish fashion company has developed a conversational generative AI platform called Lisa to design its collections and support customer service processes. It took nine months to create the tool, which enables them to make and evaluate successful designs.
Mango integrated technologies like ChatGPT, Google’s Bard and Microsoft’s OpenAI with their internal platform to maintain control over the query and response process, according to Jordi Álex, Mango’s Director of Information Systems and Technology. “Enriching the response with both external and internal data while training the large language models [LLM] with the Mango DNA was essential to the success of our project.”
The use of AI technology is not new for Mango. Since 2018, its technology team has developed over 15 platforms, each serving different areas of the business. These include Midas, used for pricing; Iris for customer service, which handles over 3.5 million requests every year; and Inspire, used by Mango’s design and photography teams.
Lisa is now consolidating all of these capabilities into a single, unified platform. “It will assist us throughout various stages of the process, starting with trend analysis, where it enables us to synthesize substantial amounts of information,” said Álex. ”It will aid us during the product ideation and design phases by allowing us to experiment with prints and textures, and enable us to analyze customer and consumer feedback.”
Conversational AI will be implemented for post-sale service to optimize customer interactions. “Our goal is to transition from a conversational assistant for specific use cases to an interactive conversational assistant that caters to diverse use cases across various platforms for our consumers,” said Álex. Its use can extend to inventory management, but only for specific processes, as the company will still rely on RFID technology for “real-time control and traceability.”
One unique feature of Lisa, compared to Mango’s other AI tools, is its internal focus. “The tool will be used by various teams, including corporate, design, sales and logistics,” said Álex. “All our teams can access the same digital platform to centralize their text and audio requests.”
The company has not revealed how much it invested in Lisa or its other AI tools, but Álex says that the new tool was developed with relatively little investment and time, given the project’s significant scope. This was made possible by the company’s technological maturity.
To develop Lisa, Mango established two teams. One team comprised tech professionals specialized in architecture, user experience, data science, front-end development (the user-facing part of a website), and back-end development (website infrastructure). The other team consisted of AI platform specialists who focused on developing Mango’s proprietary models.
“It’s been crucial for us to establish strong partnerships with different departments at Mango,” said Álex. “For instance, we train our technology using real-life scenarios that various Mango teams encounter on a regular basis.”
Álex stresses that Mango’s tools are always intended to enhance their people’s capabilities, rather than supplant them. “Our aim with these innovations is to empower our professionals, giving them the best tools to work comfortably and efficiently, and stay up-to-date with the latest trends and synergies between the physical and online worlds.”
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