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Nautica Case Study: Harnessing AI and Machine Learning to Personalise the Shopper Experience

Nathalie Gabriel

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December 4, 2024

Nautica’s Background

In 1983, Nautica’s journey began with founder and designer David Chu’s vision to infuse everyday fashion worldwide with the essence of the sea. Starting with a modest collection of six outerwear styles, the brand has steadfastly upheld its commitment to redefining nautical fashion.

Today, Nautica remains dedicated to crafting high-quality apparel that blends versatility and comfort, while innovatively honoring its maritime roots.

Nautica: Manual Tagging

Nautica faced substantial challenges related to its manual tagging process, which was plagued by inconsistencies and inefficiencies. These shortcomings resulted in inadequate search outcomes, diminishing user engagement, and adversely impacting the overall customer experience. As the company’s product catalogs expanded and the speed of seasonal changes increased, Nautica experienced a corresponding rise in labor costs. This escalation placed additional strain on its operational resources and hindered the company’s ability to respond effectively to market demands.In light of these challenges, it became evident that a more streamlined and efficient approach to product tagging was necessary. By enhancing the accuracy and speed of this process, Nautica could not only improve search functionality but also foster greater customer engagement, ultimately leading to a more satisfying shopping experience. Addressing these issues would be essential for reducing labor costs and optimizing operational efficiency in an increasingly competitive retail landscape.

Moreover, as a multinational brand catering to a diverse global audience, Nautica required a solution that could seamlessly integrate across any website while maintaining a white-label appearance.

The Process

  1. Dynamic feed transfer- The initial step involved Selectika assigning a technical account manager to oversee Nautica’s onboarding process. Subsequently, Nautica provided this designated manager with a dynamic feed containing all essential information required for the AI platform to identify the items accurately.
  2. Characterization and Tagging: Once the items were received, Selectika employed advanced visual AI recognition and automatic labeling techniques to analyze the inventory. The platform meticulously extracted characteristics and features from each item, resulting in the generation of at least 20 descriptive tags per item. This tagging process is crucial for enhancing searchability and categorization on the e-commerce platform.
  3. Introduction and Customization: Following the initial setup, the e-commerce team at Nautica conducted a thorough review of the platform’s functionalities. They assessed its capabilities and identified specific requirements for customization to better align with their business objectives. Based on this evaluation, Nautica requested tailored adjustments to the platform to optimize its performance before going live on its website.
  4. Implementation Process: In the final stage of the project, Selectika’s account manager collaborated closely with Nautica’s team to facilitate the implementation of the script onto Nautica’s website. This collaborative effort ensured seamless integration and that the platform operated effectively in a live environment. The partnership between Selectika and Nautica was instrumental in achieving a successful launch and enhancing the overall customer experience on the site.

Catalogue Tagging:

“This tagging system is precise, efficient, and consistent, empowering the diverse range of products offered by Selectika. It was a pleasant surprise to see how the numbers continuously grow. We’ve been pleasantly surprised to see how our numbers continue to grow. We had no idea how much of a positive impact Selectika’s improved user experience would have on our shoppers.”

Helena Hilel, 

Head of eCommerce at Nautica

Shop Similar:

To boost the user experience and engagement Nautica decided to implement Selectika’s Shop Similar product this resulted with an overall boost in conversions and a significant growth in average order value. The exceptional accuracy and comprehensiveness of product descriptions in Shop-Similar’s recommendations are the result of two advanced technologies: the visual AI tagging system and sophisticated machine learning algorithms. These technologies seamlessly work together to analyze and interpret product features, providing detailed insights that enhance the shopping experience.

The visual AI tagging system and machine learning algorithms. These technologies work together to analyze and interpret product characteristics with accuracy and depth.

Shop-Similar proves highly effective for Nautica’s shoppers, increasing engagement and significantly enhancing their chances of finding precisely what they seek.

Nautica’s website performance with Selectika’s AI Auto-Tagging and Shop Similar:

“I love working with Selectika! They are incredibly attentive to our needs and challenges. We’re excited about implementing their “Complete The Look” and “Find My Size” features, as we know these tools will significantly boost our revenue and cart size. Their support and innovative solutions truly make a difference for our business”

 Helena Hilel, 

Head of eCommerce at Nautica