This blog was co-authored by Tony Klimas, a partner and president of Horváth US, and Nikolas Spatz, leader of the US retail and revenue management practice.

Investment in gen AI is snowballing. Researchers at Bloomberg Intelligence forecast that generative AI-related product and service revenue will skyrocket from $40 billion in 2023 to $1.3 trillion in 2032. That is not a typo and represents a 42% compounded annual growth rate.

Tech giants Adobe, Alphabet (Google), Amazon, Microsoft and Salesforce are pouring billions into the technology. So are the world's leading advertising agencies, such as Publicis, WPP and Intercom. WPP, for example, said it will invest $318 million annually in AI to serve clients better and manage costs.

Retail leaders know that satisfied customers are their company's most important asset. Happy customers often are repeat buyers. They are also an essential source of favorable word-of-mouth and recommendations that open the door to purchases by new customers. In our company's discussions with c-suite executives at leading businesses around the world, we are advocating that decision-makers use gen AI to create smarter, more targeted experiences for current and future customers for a connected, omnichannel customer journey. Here are six areas where gen AI can add value across the retail spectrum:

1. Identify hidden purchasing trends: AI-driven analytics can scrutinize customer behavior, market trends and social media traffic and sentiment to identify purchasing trends and consumer preferences. Retailers can use the data to adjust their product/service mix, pricing and marketing campaigns to meet evolving customer demands. Additionally, if done correctly, these techniques can drive insight into consumer behavior at the intersection of online and brick and mortar.

2. Build better sales forecasts: AI can take the guesswork out of sales forecasting in a way that can drive competitive advantage. The predictive analytics capabilities of the technology can help improve the accuracy of revenue projections so retail leaders can make more informed, thoughtful decisions about allocating human and financial capital. Even slight improvements in accuracy can lead to bigger overall performance gains.

3. Improve inventory management: Inventory management can make or break a retailer. Gen AI can help retailers improve inventory turns by analyzing historical sales to see how consumer behavior, market trends and seasonality affect stock levels. Better inventory accuracy helps ensure optimal availability of products while also identifying slow-moving merchandise that is at risk of costly markdowns. Ultimately, better inventory management leads to better supply chain management and vice versa.

4. Optimize marketing and promotion spending: AI enables retailers to fine-tune their marketing investments, so those dollars are allocated to channels that yield the best results. The technology can slice and dice relevant sales and marketing data to identify optimal media outlets and campaigns that offer the highest probability of increasing revenue. Done correctly, A/B testing can become seamless and automated, enhancing every dollar of this critical spend.

5. Create customized content: Advertising and social media content are two of the most important tactics retailers rely on to connect with current and potential customers. Gen AI tools can analyze a wide range of data, such as website traffic and browsing data, email open rates and clicks, social media likes and shares, and advertising content. The technology can then create hundreds or thousands of variations of content across the marketing spectrum to identify messaging that resonates the most with customers, improving the relationship and increasing sales.

6. Streamline in-store shopping experience: Despite the move to online retail, the reality is many customers still shop in physical stores for a variety of reasons. As we embrace the new, it is important to remember the old. With generative AI, retailers can optimize inventory and dynamically adapt store layouts in response to shifting customer demands, leading to improved navigation, product visibility, and stock management. Existing examples of integrated AI in physical stores are responsive store displays that change based on real-time data. In combination with personalized customer data and a healthy respect for customer privacy, in the future, store displays could even adapt to each customer for those who opt in, showing them products and services they might be interested in exploring in the store setting.

This holistic, integrated approach, called customer journey mining, combines classic data mining with customer journey mapping to generate statistical insights into customers' behavior. Gen AI allows retailers to complete customer journey mining tasks in weeks, not months.

To leverage gen AI successfully and improve the customer experience and the business's financial and operating performance, retail leaders must set clear objectives. Executives must also not underestimate the importance of subject matter experts to review gen AI output to mitigate the risks of the data, analysis and recommended course of action is consistent with the company's mission, values, strategy and resources.

Gen AI will be a game changer for retailers. The winners in the AI race will be the companies that involve sales and marketing leaders, product managers, software engineers, data scientists and accounting experts. A thoughtful, team approach — that always keeps the customer the focus of attention — will help position the company for sustained growth and improve its competitive position.

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