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Utilizing Generative AI to Enhance Order Experience

Abstract Neurons System

Businesses are going through a significant transformation with the emergence and focus on artificial intelligence (AI). Businesses are evolving with the adoption of AI disciplines like machine learning (ML), natural language processing (NLP), robotics, and many others. AI technologies are already on a path to magnify gains in productivity, efficiency, and adaptability.

Forbes Advisor lists in their AI statistics and trends that AI is expected to contribute a significant 21% net increase to the United States GDP by 2030, showcasing its impact on economic growth. This is a direct impact of AI and automation product enhancements that are driving consumer demand across various industries.

As AI evolves, generative AI models are sweeping to attract e-commerce business. Generative AI utilizes AI models to learn patterns and create new content, audio, video, code, images, text, simulations, gaming, and structured data. This branch of research and application to businesses has become popular with generative AI tools like ChatGPT, Bard, and Dall-E2.

Per a June 2023 study done by IBM, three out of four CEOs surveyed believe the organization with the most advanced generative AI will have a competitive busineess advantage and half of CEOs report they are already integrating generative AI into products and services.

Incorporating generative AI into order management systems can bring tremendous benefits. This improves, streamlines, and automates business processes and optimizes inventory and capacity. Also, this provides an enhanced predictive and intelligent promising, providing a personalized and customer-driven interactive buying and post-purchase experience, reducing overall resource and operational overheads.

Below are various order management use cases that businesses can explore and incorporate generative AI.

Inventory and capacity optimization 

Generative AI can study demand and supply patterns to help generate inventory and capacity scenarios including peak operations, market fluctuations, and environmental, social and corporate governance (ESG) related disruptive patterns. These scenarios simulate various potential outcomes to represent various inventory levels and can be tuned for optimal inventory management strategies that reduce overstocking, plan safety-stocking, avoid stockouts, and capacity management strategies like planning labor, storage space, and equipment.

Predictive accurate promising

Generative AI models can simulate buy-to-fulfill scenarios that help in visualizing supply chain scenarios and identify potential bottlenecks, process gaps, and areas for improvement. As the system learns, the system can be made to adapt new process flows to improve the overall order orchestration and fulfillment processes and allow for more promising accuracy.

Personalized experience  

Order management systems can look at historical data such as customer buying behavior, order history, profiles, and preferences. It can then incorporate generative AI to model personalized buying as well as a post-purchase experience like tracking orders, order status communications, recommendations around product upsells, cross-sells, and substitutions to help simplify behavior patterns like inquiry, repeat orders, etc.

Interactive customer service 

Generative AI models can perform NLP tasks, such as providing responses to customer interactions in a streamlined and automated manner. This includes looking up orders, product recommendations, order status inquiries, price comparisons, product availability, and delivery date promises based on historical as well as current market situations. This can streamline customer service processes, provide clear and upfront information, and improve response times.

Improve fulfillment lead times and reduce overheads

Generative AI helps in simulating the outcomes of various lead time settings such as delivery lead-time to include warehouse operations, 3rd party vendor fulfillment overheads, and transportation and carrier times. This will help improve order fulfillment estimates and manage customer expectations better.

Enhancing customer experience, exceeding customer expectations, and optimizing the supply chain have become crucial for e-commerce businesses to be competitive. Generative AI has the potential to drastically change how businesses view post-purchase in the future.

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Ninad Manelkar

Ninad Manelkar is a Commerce Practice Director with subject matter expertise in order management solutions at Perficient Inc. He has more than 25 years of IT experience and is responsible for helping clients with order management strategy, roadmap, solution design and delivery.

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