MicrosoftRetailMarketing PersonalizationAI and Machine LearningGenerative AI / LLMCustomer ExperienceProductivity ImprovementScalability2024MicrosoftMS#0078d4RetailUnited KingdomFor young fashion lovers, ASOS offers engaging, inspirational experiences that help customers find trends and offerings to suit their personal taste. With nearly 900 brand partners and its own brand labels, it aims to…Instead, we were able to achieve great speed by easily integrating our existing microservices into the prompt…Feb 5, 20245Marketing PersonalizationAzure AI Foundry · Azure AI Studio · Azure OpenAI Service02024-02-055
For young fashion lovers, ASOS offers engaging, inspirational experiences that help customers find trends and offerings to suit their personal taste. With nearly 900 brand partners and its own brand labels, it aims to meet every moment of a customer’s life—whether that’s activewear, evening dresses, casual dressing, or face and body. To help make sure it offers each customer a uniquely tailored offer, ASOS invests in digital solutions that make use of emerging technologies, which is why the company wanted to explore how it could use generative AI to further personalize the ASOS experience.
↗Instead, we were able to achieve great speed by easily integrating our existing microservices into the prompt flow solution, and easily publishing to our managed endpoints.” Papinder Dosanjh, Head of Data Science & Machine Learning, ASOS Discover more details CUSTOMER PRODUCTS Azure AI and Machine Learning Azure AI Studio ORGANIZATION SIZE 1,000-9,999 employees COUNTRY United Kingdom BUSINESS NEED Artificial Intelligence INDUSTRY Retailers Explore related stories Stories in this industry Stories about this customer Showing 32 of 98 categories Showing 1-2 of 2 slides Previous slide Next slide We are Microsoft Empowering others Our mission is to empower every person and every organization on the planet to achieve more.
Reported impact
Business outcome
ASOS saw the chance to use Azure AI to handle ChatGPT language models at scale—a tactic that proved essential for accruing knowledge about the latest industry trends as they emerge. “Prompt flow helped streamline our development and testing cycles, which established the groundedness we required for making sure the customer and the solution were interacting in a realistic way,” says Fabon Dzogang, Senior Machine Learning Scientist at ASOS.
Customer Experience
Productivity Improvement
Scalability
Solution
ASOS used Azure OpenAI Service, Azure AI Studio, Azure AI Foundry to personalize customer engagement across channels. For young fashion lovers, ASOS offers engaging, inspirational experiences that help customers find trends and offerings to suit their personal taste. With nearly 900 brand partners and its own brand labels, it aims to meet every moment of a customer’s life—whether that’s activewear, evening dresses, casual dressing, or face and body. To help make sure it offers each customer a uniquely tailored offer, ASOS invests in digital solutions that make use of emerging technologies, which is why the company wanted to explore how it could use generative AI to further personalize the ASOS experience. Key implementation elements included Azure OpenAI Service generates natural-language responses and task automation for the solution; Azure AI Studio provides the workspace for building, testing, and deploying the AI application; Azure AI Foundry supports model orchestration,...
Solution architecture
5 components · 2 layers
Compute
Azure OpenAI ServiceGenerates natural-language responses and task automation for the solution.
Azure AI StudioProvides the workspace for building, testing, and deploying the AI application.
Azure AI FoundrySupports model orchestration, evaluation, and governed deployment of the AI workflow.
Microsoft AzureHosts the application, data, and integrations on scalable cloud infrastructure.
Orchestration
Microsoft Dynamics 365Provides the common business process layer that standardizes operations.
Architecture clues
Emphasizes secure enterprise access to data and AI capabilities.
Uses a microservices-based architecture.
Evidence from the source
ASOS saw the chance to use Azure AI to handle ChatGPT language models at scale—a tactic that proved essential for accruing knowledge about the latest industry trends as they emerge. “Prompt flow helped streamline our development and testing cycles, which established the groundedness we required for making sure the customer and the solution were interacting in a realistic way,” says Fabon Dzogang, Senior Machine Learning Scientist at ASOS.
ASOS used Azure OpenAI Service and Azure AI prompt flow with ChatGPT language models to rapidly develop and test an Azure OpenAI-powered customer experience that helps customers discover new looks.
For young fashion lovers, ASOS offers engaging, inspirational experiences that help customers find trends and offerings to suit their personal taste. With nearly 900 brand partners and its own brand labels, it aims to meet every moment of a customer’s life—whether that’s activewear, evening dresses, casual dressing, or face and body. To help make sure it offers each customer a uniquely tailored offer, ASOS invests in digital solutions that make use of emerging technologies, which is why the company wanted to explore how it could use generative AI to further personalize the ASOS experience.
Instead, we were able to achieve great speed by easily integrating our existing microservices into the prompt flow solution, and easily publishing to our managed endpoints.” Papinder Dosanjh, Head of Data Science & Machine Learning, ASOS Discover more details CUSTOMER PRODUCTS Azure AI and Machine Learning Azure AI Studio ORGANIZATION SIZE 1,000-9,999 employees COUNTRY United Kingdom BUSINESS NEED Artificial Intelligence INDUSTRY Retailers Explore related stories Stories in this industry Stories about this customer Showing 32 of 98 categories Showing 1-2 of 2 slides Previous slide Next slide We are Microsoft Empowering others Our mission is to empower every person and every organization on the planet to achieve more.
“We’ve worked closely with Microsoft in the past and we’ve been early adopters of technology all along, so it made sense to explore using Microsoft technology coupled with our team’s existing knowledge of natural language processing to develop a new kind of experience to engage shoppers.” The company chose to use Microsoft Azure OpenAI Service and Azure AI prompt flow to build an AI-powered experience that customers could interact with as soon as they arrive on the ASOS website or app.
Review how this reference was scored and trace each normalized claim back to its documented source.
01
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value61/100
Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth15/25
Rewards named components, data flow, integrations, and architecture detail.
Outcome specificity16/20
Measures whether the reported benefit is concrete rather than a generic claim.
Quantified impact0/25
0 metrics describe measurable impact.
Deployment scale10/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence88%
Source authority20/25
The main evidence is an official vendor-published customer story.
Claim traceability23/25
11 of 12 key fields link to a named source.
Direct evidence20/20
5 direct source quotes retained.
Date provenance10/10
The publication date comes from the source page or publisher.
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