James Gurd and Paul Rogers discuss the challenges of product data quality in ecommerce with Vidar Trojenborg, co-founder of Emfas, a platform solving real world product data issues for brands including Stronger, Twistshake and Nudie Jeans.
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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 retailer ASKET.
In the podcast, 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.
Chapters:
- [00:40] Introduction to AI in Ecommerce
- [03:30] The Journey to Emfas and Its Purpose
- [06:450] Challenges in Product Data Quality
- [09:30] Bridging the Gap Between Teams
- [12:40] AI Automation and Brand Control
- [15:40] Auditing and Prioritising Actions
- [18:35] Handling Large Catalogues with Rules
- [21:30] Context-Aware AI for Product Descriptions
- [22:20] Translation Challenges in E-commerce
- [27:40] Emfas in the Ecommerce Tech Stack
Want to suggest a topic or guest for a future episode? Contact us via the website or on LinkedIn.