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Today's guest is Nick Masca, Head of Data Science for Growth & Personalisation at Marks and Spencer. Marks and Spencer plc is a prominent British multinational retailer headquartered in London, England, known for offering a wide range of clothing, beauty items, home goods, and food products. Nick joins us on the program to surmise his views on the data-driven challenges currently facing the retail and eCommerce sectors. With a focus on change management rather than traditional digital transformation, Nick outlines the key obstacles retail leaders encounter when leveraging data tools to optimize processes like price setting, supply chain efficiency, and customer experience. He shares insights on the friction that arises when introducing automation, particularly in areas like content development, and how data teams can work closely with stakeholders to ensure seamless implementation. If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!
By Daniel Faggella4.4
162162 ratings
Today's guest is Nick Masca, Head of Data Science for Growth & Personalisation at Marks and Spencer. Marks and Spencer plc is a prominent British multinational retailer headquartered in London, England, known for offering a wide range of clothing, beauty items, home goods, and food products. Nick joins us on the program to surmise his views on the data-driven challenges currently facing the retail and eCommerce sectors. With a focus on change management rather than traditional digital transformation, Nick outlines the key obstacles retail leaders encounter when leveraging data tools to optimize processes like price setting, supply chain efficiency, and customer experience. He shares insights on the friction that arises when introducing automation, particularly in areas like content development, and how data teams can work closely with stakeholders to ensure seamless implementation. If you've enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

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