Brands and companies continually try to improve brand perception and gain customer preference. Considering the last decades of digitization, technological advancements, the hype around AI, and most recently, Generative AI, both opportunities and challenges have risen for companies. Specifically for Retail and Consumer Packaged Goods (CPG), Generative AI can improve brand-consumer interactions and further personalization. This can be especially important in gaining a competitive advantage, as consumers seek a shopping experience that is both seamless and engaging.
As studies show, 17% of shoppers have already used Generative AI for inspiration (Salesforce, 2023); both centennials and millennials are interested in gifting, home decor, and outfit ideas. Salesforce also claims that over 50% of retailers are already using or exploring Generative AI for specific use cases. For example, 55% are implementing it to enable digital shopping assistants, while 41% consider this use case.
For CPG, Everest (2023) identifies several areas with potential applications across the value chain, including “product development, digital commerce, sales and marketing, supply chain, and in-store operations.” Delving into digital commerce, Generative AI can accelerate website design, search experience, and recommendations. In-store operations include potential applications like planogram design and store analytics.
These, among many other use cases, have the potential to automate many tasks, generating efficiency and gains in productivity. According to McKinsey & Co. (2023), Retail and CPG expect a 1.2-2% increase in productivity bolstered by use cases in functions similar to those proposed by Everest, including customer service, marketing and sales, and supply chain, among others. As these industries are heavy in customer-facing, use cases include Generative AI agents to assist in-store associates with product recommendations, summarization of customer cases, GenAI chatbots for customer support, creation of personalized content, and more. Applications such as Generative AI chatbots can streamline customer support, automate tasks, and expedite the testing of concepts and ideas.
However, along with these opportunities, there are several challenges. Including addressing data privacy and security, training and fine-tuning to guarantee understanding of industry-specific terminology and company information, and others such as ensuring proper guardrails are in place.
