In an insightful 11-minute video (below), Andrew Ng, a pioneer in the field of artificial intelligence (AI), posits that AI has the potential to "enable everyone to help write the future." He explains that while AI systems are typically expensive to build and require a team of highly skilled engineers, they are not solely the domain of large companies with vast amounts of data. Ng asks us to imagine a world where a local pizza shop could use AI to predict which flavor would sell best each day of the week. Such a scenario would empower businesses to make data-driven decisions, increasing their profit and productivity and leading to better resource allocation across society. This vision is not just a grand idea; it's a reality unfolding today, particularly in the retail sector.

For instance, at HIVERY, our focus on AI has been to leverage it to make sense of store-level data. This innovation has allowed us to uncover latent shopper segments, helping our customers discover actionable insights for simultaneous demand forecasting and product placement. 'Latent' refers to something that is not yet developed or visible. In this context, it means potential shopper groups that might not be immediately apparent but can be identified through AI analysis. This process enables the identification of groups of "stores" with similar characteristics, regardless of their location. These insights can inform targeted assortments and marketing campaigns, leading to smarter operations through improved store cluster design.

Traditional consumer research methods, including primary customer research and shopper insight panel data, provide valuable insights into the "who" and "why" of shopping behavior. However, they often falter when suggesting "what" to do in stores. This task becomes even more complex when consumers aren't entirely truthful, omit crucial information, or when the consumer and shopper are two different entities. But with the advent of AI, we can now complement these "who" and "why" approaches with data-driven insights on the "what" to do in stores.

New methods in AI enable retailers and CPG manufacturers to test any assortment strategy and assess its impact before rolling it out in stores. This methodology aligns with Ng's vision, at 4:09, of enabling small businesses to leverage AI to spot patterns and make informed decisions. Ng envisions that every store can use its datasets to conduct superior demand forecasting, product placement, supply chain optimization, and quality control. At 7:48 in his video, Ng shows an example of an AI platform that allows users (store owners or manufacturers) to use photos and text commands, and the AI platform does the rest.

Consistent with Ng's perspective that AI should be accessible and beneficial to all, irrespective of the size or type of business, HIVERY's approach represents a new paradigm in retail strategy. By understanding the latent needs of consumers and creating store arrangements that cater to those needs, retailers can optimize their offerings and drive significant business results. This is also highlighted in a recent Gartner Report, underscoring the importance of technologies like AI in enabling customer-centric, store-specific assortments. This supports the concept of "hyperimmersive" retail experiences, a trend gaining traction in the retail industry.

In conclusion, the advent of AI is revolutionizing the retail industry, and companies like HIVERY are at the forefront of this transformation. Through their innovative use of AI, they are equipping retailers with the tools necessary to make data-driven decisions that enhance their business strategies and, ultimately, improve the shopping experience for customers.

Related content you might be interested in:

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• Mastering Assortment Price Pack Architecture: How AI streamlines product across multiple retailers.
• Progressive Grocer - Innovating Category Management: Assortment as a Service
• Harnessing AI to Optimize Retail Space Amidst Shrinking Square Footage