• EP280: The AI Workspace For Product Catalogues - How Emfas Automates Quality Improvements & Solves Data Challenges

  • 2025/03/10
  • 再生時間: 36 分
  • ポッドキャスト

EP280: The AI Workspace For Product Catalogues - How Emfas Automates Quality Improvements & Solves Data Challenges

  • サマリー

  • James Gurd and Paul Rogers discuss the challenges of product data quality in ecommerce with Vidar Trojenborg, co-founder of Emfas.

    Vidar has a lot of experience building ecommerce tech stacks to improve and manage product data, having previously held the role of Head of Data & Technology at ASKET.

    In the po dcast, we explore how AI can automate product data management, improve catalog quality, and bridge the gap between product and ecommerce teams.

    Vidar shares insights on the importance of context-aware AI, the role of guidelines in maintaining brand integrity, and the future of ecommerce technology. The conversation also touches on translation challenges and the integration of Emfas with existing ecommerce platforms.

    Key takeaways:

    • Data quality issues are a common challenge in ecommerce.
    • Bridging the gap between product and ecommerce teams is crucial.
    • Emfas uses AI to maintain content authenticity and tone of voice.
    • The platform automates the auditing of product data.
    • Guidelines can be set for AI-generated content.
    • Emfas can handle large catalogues efficiently with rules.
    • Context-aware AI ensures accurate product descriptions.
    • Translation rules can be customised for different languages.
    • The future of ecommerce will heavily involve AI technology.
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あらすじ・解説

James Gurd and Paul Rogers discuss the challenges of product data quality in ecommerce with Vidar Trojenborg, co-founder of Emfas.

Vidar has a lot of experience building ecommerce tech stacks to improve and manage product data, having previously held the role of Head of Data & Technology at ASKET.

In the po dcast, we explore how AI can automate product data management, improve catalog quality, and bridge the gap between product and ecommerce teams.

Vidar shares insights on the importance of context-aware AI, the role of guidelines in maintaining brand integrity, and the future of ecommerce technology. The conversation also touches on translation challenges and the integration of Emfas with existing ecommerce platforms.

Key takeaways:

  • Data quality issues are a common challenge in ecommerce.
  • Bridging the gap between product and ecommerce teams is crucial.
  • Emfas uses AI to maintain content authenticity and tone of voice.
  • The platform automates the auditing of product data.
  • Guidelines can be set for AI-generated content.
  • Emfas can handle large catalogues efficiently with rules.
  • Context-aware AI ensures accurate product descriptions.
  • Translation rules can be customised for different languages.
  • The future of ecommerce will heavily involve AI technology.

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