How AI Search Can Boost Retail Sales Through Product Discovery

The pandemic has had lasting effects on the supply chain. Demand for products is on the rise, online shopping has increased, and more consumers are returning items purchased online. To cope with these trends, many retailers are overordering and accelerating their ordering and restocking times.

In 2021, PBS found that it took 80 days for a pair of shoes to get from Asia to retailers in North America, double the time it took before the pandemic. Around the same time, a Utah-based retailer reported inventory levels of just 55% below normal, all due to transportation delays.

One of the keys to helping retailers mitigate supply chain issues today is an AI-driven product discovery platform. Through the use of features enabled by AI and machine learning, retailers can maintain a high-quality user experience by delivering fast, personalized, and relevant search and recommendation results. In the process, customers can always buy products that meet their needs and are in stock.

At Deloitte Retail Industry Outlook 2022, 80% of executives surveyed said consumers will prioritize inventory availability over brand loyalty, highlighting the role product discovery can play in achieving sales goals. If the exact product is not available, suitable items must be provided as alternatives to maintain the sale.

The search bar is the starting point of the customer journey. Whether they make the purchase online or use an e-commerce site to research a product before buying it in-store, nearly half (40%) of consumers begin their search online.

A search experience that doesn’t live up to a customer’s expectations is the quickest and easiest way to lose a sale. A recent report from google found that approximately $300 billion in sales are lost in the United States each year due to poor online search experiences.

The impact on the customer relationship can extend far beyond a bad visit. Google’s report found that 85% of online shoppers view a brand differently after encountering difficulty with product research.

The revenue lost from poor search experiences and the potential revenue generated from good experiences makes investing in a product discovery app a priority for retailers. The right search technology can help retailers deliver up-to-date search results to consumers looking to purchase a product online or research their purchasing options in-store.

Also in Google’s report, 90% of consumers said an easy-to-use search function is essential when shopping on a retail site. AI-powered product discovery platforms can understand customer intent, creating hyper-personalized search and recommendation results for each individual shopper.

The tool takes into account factors such as stock availability and the likelihood that an item will be restocked quickly. AI search can take stock changes into account and notify the customer when stocks of a given product are low. It can also remove out-of-stock products from search results, instead providing smart replacement recommendations that still meet the customer’s search goals.

AI search uses pre-existing data and analytics to drive new products that might otherwise lack the ratings and purchase history needed to organically move them to the top of search results. Without next-generation AI technology, the task can only be accomplished through legacy systems and human intervention, which is more time-consuming, overly reliant on a technician’s skills, and vulnerable to error. .

AI search can be seamlessly integrated into any e-commerce platform or additional applications in a retailer’s technology stack. This means retailers can own and grow the front-end search experience for customers, while the API-based headless architecture provides powerful behind-the-scenes capabilities. It also allows the development team to create front-end experiences that can be integrated into the user interface of each customer segment.

Modern product discovery platforms supporting e-commerce can learn to take into account factors such as inventory levels, customer reviews, and search behavior. AI and machine learning technology enhance the retailer’s back-end experience, managing inventory that is tied to the customer’s search and recommendation experience. At the same time, it creates a high-quality, personalized experience for the customer, which results in higher conversion rates.

Roland Goassage is Managing Director of By group.

Amanda J. Marsh