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The SAP Emarsys report shows which AI-driven trends will become key to sustainable growth for companies in this sector. In the first part of the series, we describe 6 of them. Growing in importance are the abilities to analyze customer needs in detail, personalize offers and their promotion in advanced ways, create unique shopping experiences, and take a smart approach to every stage of the purchasing process.
Integration tailored to today’s customer
The key to success in the retail market is good organization and a strategy built with an understanding of the industry’s complexity. Integrating all sales channels, along with automating supply and pricing control, allows companies to maintain both control and process flexibility at the same time. Innovative AI-supported analytical tools ensure the right speed and smoothness of daily operations.
Today’s customer makes purchasing decisions with a phone in hand. With that in mind, we can tailor shopping experiences to their needs. Some consumers discover products online and buy them directly through an online store or app, while others go to a physical store to see the products in person first and verify the information they already have. That’s why companies, as part of an omnichannel approach, integrate the operation of their supply system, sales department, marketing, and returns strategy, ensuring effective use of data at every stage.
Shifting demand, dynamic pricing
Based on data analysis, artificial intelligence offers demand predictions and detailed recommendations for optimal pricing. Dynamic shifts in demand are characteristic of today’s market, where customers are under constant influence from content promoted online, especially on social media. On top of emerging microtrends such as briefly fashionable Labubu figurines or Dubai chocolate, there’s also seasonality and regional preferences to account for. Predicting what will become popular, and when, becomes a real challenge.
AI-based systems forecast not only the emergence of a given trend but also its decline. With these predictions, companies can get ahead of competitors relying on conventional methods. This way, businesses reduce both understocking and overstocking, along with the associated financial losses and environmental harm. A full picture of current supply is made possible by IoT devices placed on pallets or individual products.
Optimal price selection maximizes profits without limiting demand. These algorithms draw on data from many sources: online transactions, social media, and in-store IoT devices, to determine, with high accuracy, the impact of even minimal changes on demand. Based on patterns detected by AI, dynamic pricing enables a high degree of personalization and can be adjusted for specific customer segments.
Personalizing the shopping experience
The rapid development of technology allows for shopping experiences of previously unmatched quality. Particularly impressive is the ability to incorporate AR and VR technology into the customer experience, turning shopping into engaging entertainment while also addressing a number of challenges the industry faces. Interactive 3D product models and precise size recommendations enable more informed purchasing decisions, which in turn reduces the number of returns. Both sides of the transaction save time and money, while consumer satisfaction and repeat-purchase intent increase.
Personalization is a key element of this innovative approach to customer experience. According to the SAP Emarsys AI in Retail Report 2024, 40% of surveyed customers believe that most marketing emails they receive are not tailored to their needs and preferences, and 29% consider customer service too impersonal.
With AI support, marketing departments can create email variants based on customer profile data and extensive predictive analytics on purchasing decisions, resulting in higher open rates and growing engagement. This effect, following the introduction of AI-supported solutions, is confirmed by 78% of surveyed marketers.
Returns as a profit opportunity
For customers, returns have shifted from an unpleasant necessity to a standard part of shopping habits. 33% of American consumers admit to buying more products with the intention of returning some of them after trying them on, and the average consumer returns 8 items per year.
In response to this behavior, retailers should adopt strategies that not only limit the resulting financial losses but also build new profit opportunities.
First, the number of returns itself can be reduced by ensuring accurate product recommendations, with appropriate product descriptions and dedicated technological solutions making it easier to choose the right size or variant. Beyond that, when a return is necessary, costs on both sides can be reduced through conditional free or low-cost return options, or the option to repurchase using the original payment. An eco-friendly approach can also generate value, for example, by adopting a strategy of reusing and reselling products instead of discarding them.
Returns are also another source of valuable customer data and consumer habits, which can be used to target promotions and tailor offers and sales methods.
The eco-friendly approach: expectations and regulations
When it comes to eco-friendly solutions, development directions are driven on one hand by customer expectations and on the other by changes in legislation. Under EU directives, companies operating in member states will be required, by 2030, to completely stop using certain types of single-use packaging. Similar laws, including, for example, charging producers recycling fees, have come into effect, or will soon, in the UK, parts of the United States, and some of the largest Asian countries.
Customers care about their purchasing choices having as little environmental impact as possible. Retailers and manufacturers can give them a sense of agency through transparency about the practices they use, and by offering opportunities for personal involvement such as paid options to choose sustainable delivery or eco-friendly packaging. Transparency is often expressed by sharing information about the exact composition of products, the origin of materials used, and related certifications. The industry is moving toward a situation where as much packaging as possible is recyclable or reusable, for example, through in-store refill programs at brand locations. In the future, instead of focusing on eye-catching packaging, companies will build their brand image through unique experiences associated with it.
Customer opinions
When asked about the growing use of artificial intelligence in retail services, consumers approach the changes with reasonable caution, but also optimism that the benefits of new solutions are noticeable to them. Particularly useful and encouraging is the increasingly accurate personalization of promotional content. According to the SAP Emarsys report:
A key concern that users highlight is data privacy. As many as 73% of consumers worry about how AI uses the data they share with companies while shopping, and only 24% have high trust in AI-driven sales services. In addition, 87% of respondents consider transparency around the further use of personal data important, and 77% believe retailers should prioritize the ethical use of AI.
ERP solutions for direct sales
The SAP Cloud ERP solution for the apparel industry automates the activities characteristic of this vertical market based on built-in AI and its database. In-memory technology enables instant processing of huge volumes of compressed data.
The platform enables:
SAP offers a wide range of solutions for the retail industry, covering tools that support assortment management, supply chain, omnichannel experiences, customer service, as well as finance and HR.
To discuss how integrating AI with your ERP system can serve you — contact us
Schedule a consultation with SUPREMIS to learn more.
If you're interested in improving how your company operates, get in touch with us to learn more.
Find out more
