Marketing Mix Modeling (MMM) has long been a valuable tool across industries for data-driven decision-making. Recently, it has gained renewed attention in healthcare and pharmaceuticals as a means of addressing critical questions.
Effective category and product management are crucial to the fashion and apparel industry, directly impacting sell-through rate — a key inventory management KPI and a major driver of overall sales. Optimising sell-through and minimising excess inventory begins with the product buying process.
Artefact, in partnership with Tencent Cloud (International) and Alipay (International), hosted a seminar entitled "AI FOR TOURISM, Harnessing The Power of AI and Data for Travel & Hospitality" at its Shanghai office on 22 October. The event focused on enhancing the service experience for Chinese tourists through AI and data technology, and brought together travel and hospitality brands, including hotels, airlines, resorts, tourism boards and travel retail.
In the dynamic landscape of modern business, data has emerged as a cornerstone of success, driving innovation and informing decision-making. Yet, the mere accumulation of data is not enough; organizations must develop the capabilities to leverage its full potential.
Discrete choice models aim at predicting choice decisions made by individuals from a menu of alternatives, called an assortment. Well-known use cases include predicting a commuter’s choice of transportation mode or a customer’s purchases.
AI has the potential to enhance companies' growth prospects, but its deployment within organizations requires strong business and technological expertise, as well as the establishment of dedicated data and AI governance. Insights from three experts from consulting firm Artefact.
In today's China, beating fraud and staying ethical is essential for long-term success. The post-pandemic slowdown exposes weak spots, echoing Warren Buffett's warning: "Only when the tide goes out do you discover who's been swimming naked". Companies must identify risks and strengthen financial strategies to not only survive but thrive in economic downturns.
Remember Business Objects? If you do, you might see where I'm going with this. We're heading into a period where Large Language Models (LLMs) capable of building business-level software will become increasingly commoditized. It's an impressive technological feat, sure, but it's also a potential race to the bottom. Why? Because while everyone's busy showing off their latest AI parlour tricks, they're missing the real goldmine: the data itself.
The abundance and diversity of responses to ChatGPT and other generative AIs, whether skeptical or enthusiastic, demonstrate the changes they're bringing about and the impact they're having far beyond the usual technology circles. This is in stark contrast to previous generations of AI, which were essentially predictive and generally the subject of articles or theses confined to the realm of research and innovation.
