5 stand-out retail use cases for generative AI + Elasticsearch

Personalization enables organizations to offer highly tailored experiences that appeal more directly to the specific interests or pain points of a customer or employee. Search technology is already powering the personalized digital experiences that customers experience everyday. In fact, 88% of online shoppers are more likely to continue to shop on websites that offer a personalized experience, according to a study by Wakefield Research. 

ESRE provides robust search capabilities, allowing retailers to build fast, highly relevant search experiences for their online stores. When combined with the generative capabilities of large language models, customers can get results tailored to their location, demographic, or preference — leading to improved customer satisfaction and conversion rates. Precision context windows with Elastic also help reduce data footprint and expenses.

Outstanding support starts with getting answers for your customers. Generative AI can analyze and learn from historical customer data including customer support interactions, from emails and chat logs to support tickets. It can generate automated responses based on this data, providing quick and accurate answers to frequently asked questions or common issues. This saves time for both customers and support agents, streamlines self-service support, and allows agents to focus on more complex or personalized inquiries. 

ESRE serves as the perfect backbone for this use case, helping customers find information quickly and easily with semantic search. The Elasticsearch Relevance Engine includes a proprietary out-of-the-box semantic search model as well as a production grade vector database and hybrid search ranking. It gives developers a flexible foundation on which to build rich semantic search, vector search, and hybrid search applications, which can be used by service agents. Elastic also includes native support for role-based and attribute-based access control, so customers and agents only see information they have access to.

GAI holds immense potential for the retail industry by aiding in the identification of fraudulent activities and the detection of anomalies. Through the process of pattern learning from existing data, generative models can predict new data points that align with the learned patterns. Retailers can leverage these capabilities in combination with Elastic to compare real-time customer interactions and transactions with predicted patterns. This integrated approach helps retailers proactively identify uncommon or fraudulent behavior that may otherwise elude detection through conventional rule-based systems alone.

New technology that enables a guided shopping experience is becoming more prevalent. Retailers can now imitate the online shopping experience by pairing real-time demographic information with potential purchase preferences. This information is then correlated, in real time, with in-store video screens — such as smart shelves — which aim to deliver this information as part of the interactive experience of choosing a product. This amounts to dynamically combining data across disparate sources and presenting it together with a unified experience. Generative AI coupled with ESRE makes this task easier with a single platform to consume data and insights. This is done while enabling privacy and security via Elastic’s native support for role-based and attribute-based access controls.

Retailers can collect data from various sources, such as sensors, equipment logs, and historical maintenance records, to build a comprehensive data set. With Elastic, powered by ESRE, retailers can activate this information to automate monitoring, accelerate root cause analysis, and optimize operations by applying machine learning. This helps drive increased productivity, faster innovation, and more trustworthy customer experiences. Retailer supply chain and operations teams can continuously monitor this data in real time to identify patterns and anomalies that may indicate potential inventory issues or equipment failures.