40% increase in conversion rate for luxury lifestyle brand with automated product tagging

A luxury lifestyle brand sees reduced manual effort, increased product views, and better conversions with automated product tagging.

The big picture


reduction in time to market


increase in conversion rate


increase in unique product views

The global luxury goods market is projected to reach $296.9 billion by 2026. A significant contributor to the growth of the worldwide luxury market is the changing patterns around how people consume luxury. A substantial number of luxury products are being bought online by Gen Z and millennial buyers who gravitate more towards convenience and the availability of omnichannel experiences.

The customer—a luxury lifestyle brand—has made tremendous inroads across geographies and generations with edgy, innovative styles. Their revolutionary take on luxury clothing has encouraged the industry to consider sustainability and eco-conscious clothing as part of the conversation about luxury products.

The customer and Vue.ai teams have been working together to implement tagging to maximize conversion and forward data-driven decision-making to move products onto their site quickly and efficiently.

The need

The customers’ focus was to simplify and reduce the time taken to go to market with their products. To do this, they had to put in place a process that would quicken the tagging process while ensuring standardization across their catalogs.

The customer and Vue.ai teams worked together to implement Vue.ai’s automated product tagging solution that could:

Help the customer tag products at a fraction of the time it took to manually tag products

Enrich customer’s catalog data which in turn would help power filers on the site to assist user journeys and give the ability to forecast trends

Clean and standardize data across the catalog which will help unify shopper experience across channels

Clean and standardize data across the catalog which will help unify shopper experience across channels

Train, identify and detect custom logos on products and develop custom taxonomy as required by the customer

The customers chose Vue.ai as the solutions offered catered to their needs to enhance the quality and reliability of data, deliver custom taxonomies, and integration while ensuring process efficiency.


Data tagging, synchronization and quality assurance are essential parts of the product data generation process. The customer's team had a catalog of roughly 600 new products arriving each season. The workflow involved waiting for batches of products to complete photoshoots and then manually tagging each image. They spent more than a week’s worth of manual effort every season tagging images. The customer also had iconic logos that required data that was unique and exclusive to the brand. This meant custom attributes created specifically for their products. They needed a solution that would be able to identify & tag the iconic logos found on their products.

AI-powered tagging to enable faster onboarding of products

Vue.ai's team worked with the customer team to implement AI-powered instant tagging which ensured:

  • Product tagging is automated across attributes and categories. This reduced the time teams spent on tagging.
  • Products are tagged as soon as the images are available, rather than waiting for a significant portion of the collection.
  • Review processes and feedback on tags are quickly done through the tool, making it faster and significantly reducing go-to-market time.

Automated tagging to bypass scalability challenges and reduce overall manual effort

With AI-powered tagging, the tags extracted by the tool helped the customer enrich their catalog data and:

  • Power filters on the site which assisted user journeys and enabled product discovery.
  • Enrich catalogs from other vendors enabling a cleaner catalog.
  • Use the extracted tags for analysis and forecasting.

AI-powered tagging to standardize data across sources and fill in any data gaps

Standardizing data across the catalog helped the customer unify the shopper experience across channels. It:

  • Identified missing data, incomplete metadata, or duplication of images across sellers.
  • Helped reconcile visually and textually extracted attributes.
  • Highlighted inconsistencies and boosted the confidence and accuracy of attributes based on contextual cues from different sources.

Integration via API and existing PIM management tools resulted in seamless integration and allowed for customization.

The customer-preferred integration method was via API - a connector between Vue.ai & their existing Product Information Management tool. The APIs offered by Vue.ai ensured a seamless integration while also allowing for customizations & complete control over the workflow process.

The downstream effects of the integration allowed for:

  • Maintaining a central repository of all the data extracted from images.
  • Feedback to continuously re-train the systems & ensure optimal accuracy.
  • Standardized set of tags - ensuring rich & uniform product catalogs.

Automated building and training of customer-specific taxonomies to identify highly specific custom logos

The customer used automated product tagging to build their own custom taxonomy and trained networks to identify the highly specific tags.

  • The system understands both text and image-based input. This meant identifying the specificities and tagging the products in a consistent & easy-to-export format.
  • A simple QA process allowed the customer to correct any incorrect tags while forming a feedback loop, improving the network in an iterative manner.

Key takeaways

  • A business strategy that revolves around bringing effective, and exciting online shopper experience to what is traditionally an offline industry is essential for luxury industries to meet the demands of the 21st-century shopper. A big part of this is ensuring the nature and quality of product data on-site is robust enough for shoppers to continue their shopper journey.
  • An AI-powered solution must go beyond generic tags and basic image descriptions to provide business-specific intelligence with rich, consistent, and accurate data. Faster product digitization and decrease in manual labor results in both richer data that can aid in product discovery and a better understanding of the data and how shoppers interact with it.
  • From boosting on-site search results to optimizing pages on the site to helping teams make better-merchandising decisions and inventory planning, Automated product tagging works across the business vertical.