How to Navigate Generative AI for Customer Operations: Top 5 Best Practices for Distributors and Manufacturers UpBrains AI

May 26, 2024

Summary: In the dynamic sectors of distribution and manufacturing, achieving high efficiency and ensuring customer satisfaction are of utmost importance. Manual work practices and reliance on outdated software solutions can result in inefficiencies, delays, and financial losses due to errors and mistakes, ultimately leading to dissatisfied customers.

In the dynamic sectors of distribution and manufacturing, achieving high efficiency and ensuring customer satisfaction are of utmost importance. Manual work practices and reliance on outdated software solutions can result in inefficiencies, delays, and financial losses due to errors and mistakes, ultimately leading to dissatisfied customers. These manual processes often force customer operations teams to expend valuable time and resources on routine tasks like managing communications and processing documents.

Generative AI has emerged as a groundbreaking technology with the potential to transform various business functions such as sales, marketing, and customer support. Among its applications, one of the most impactful yet underexplored areas is in the core customer operations of distributors and manufacturers. This technology spans customer and employee touchpoints extensively.

The integration of generative AI into core business operations profoundly influences both customer and employee interactions. It enhances customer support and deeply integrates into the internal processes that manage and follow up on customer requests. The application of generative AI here not only streamlines workflow but also boosts operational efficiency and responsiveness — key factors in improving overall business performance.

This strategic application of generative AI is where its potential impact is most significant on distributors and manufacturers, yet it remains much less discussed and explored. By adopting generative AI, businesses in these sectors can address complex challenges more effectively and position themselves advantageously in a competitive market. This article delves into the central role of Generative AI in enhancing customer operations for distributors and manufacturers.

Overview of Generative AI in Business

Generative AI, a subset of artificial intelligence, refers to large computer models capable of learning human language and knowledge to generate new content, such as text, audio, images, and video, in response to input or commands. Initially prominent in content creation, these technologies have evolved to handle command execution, data processing, and basic reasoning tasks. This expansion broadens their applicability across business including personalized marketing, enhanced customer support with more human-like virtual assistants and automation of business processes:

  • Marketing: Crafting personalized content, generating compelling ad copy, and creating engaging social media posts.

  • Customer Support: Enhancing customer support through AI copilots and assistants to provide more accurate, human-like responses to customer queries.

  • Business Processes for Customer Operations: Streamlining operations and complementing employees in business functions, particularly in order processing.

A pivotal advantage of generative AI-based solutions is their capacity to be expanded to business applications to process complex business data, thereby streamlining operations and supporting staff in various administrative tasks.

The Role of Generative AI in Customer Operations

The essence of customer operations lies in managing the entire lifecycle of a customer order — from intake through processing, shipping, delivery, and support. Many distributors and manufacturers still receive orders through diverse channels, including emails, web forms, applications, and even paper-based methods like fax or phone. While comprehensive software systems exist for managing these orders, they often require significant investment and pose risks like vendor lock-in, particularly for smaller firms. The evolving landscape of order management software now benefits significantly from advancements in generative AI, which enhances the processing of customer communications and order data. This enables AI-powered applications to assist customer support representatives (CSRs) by integrating directly with ERP systems, managing pre-processing of orders, and facilitating professional responses and follow-ups with customers.

By automating customer order processing in an integrated manner with front-office customer support, Generative AI transforms what was once a back-office burden into a strategic asset. This transformation reduces errors, provides better visibility into detailed customer communications, purchases, and business operations, ultimately enhancing overall business performance.

This article explores the best practices for leveraging Generative AI, with a focus on enhancing the work of customer operations teams and CSRs in processing customer orders and managing the business operations of manufacturers and distributors.

Let’s first examine the challenges faced by customer operations teams in order processing.

Challenges in Order Processing for Customer Operations Teams

Order processing is a critical function for distributors and manufacturers, often fraught with challenges such as:

  • Processing Incoming Order Requests: Reviewing and extracting details from purchase orders received via email or other channels.

  • Handling Attached Purchase Orders: Managing orders in various formats (PDFs, Word documents, spreadsheets, and images) to extract key information for data entry.

  • Data Entry: Entering data from emails and attachments into the order management system, a time-consuming and error-prone task.

  • Order Updates: Managing modifications, stock availability checks, and shipping issues.

  • Product Damage and Returns: Handling communications regarding damaged products or returns.

  • Order Errors: Addressing errors such as shipping to the wrong address, shipping incorrect items, and missing items from deliveries.

  • Product Quality Inquiries: Managing customer communications related to product quality and supplier documentation is a key burden of the customer operations teams.

How Generative AI Transforms Order Processing

Generative AI can significantly mitigate these challenges by automating key aspects of the order processing workflow:

  • Understanding Customer Communications: Advanced natural language processing (NLP) capabilities enable AI to extract relevant information from emails and attached documents.

  • Automated Data Entry: AI automates data extraction and entry into the order management system, reducing errors and speeding up the process.

  • Communication Routing and Sorting: AI classifies and routes incoming communications to the appropriate teams or individuals.

  • Task Assignment: AI prioritizes and assigns tasks based on urgency and importance.

  • Order Tracking and Updates: AI monitors orders for updates, tracks stock availability, and communicates changes or issues to the customer.

  • Quality and Supplier Documentation Management: AI facilitates the provision, management, and organization of quality and supplier documentation.

  • Automated Response Generation: AI generates context-aware responses to customer communications and drafts messages for internal teams based on available information.

Top 5 Best Practices for Implementing Generative AI for Customer Operations

  1. Educate and Upskill Your Team: Begin by familiarizing your team with Generative AI concepts and solutions specifically those build for supply chain domain, distributors and manufacturers. Provide training to help them understand how AI can enhance their workflows.

  2. Start Small with Pilot Projects: Identify a suitable area for a pilot project. Launching a small-scale AI-powered automation project allows you to measure its impact and refine processes before full-scale implementation.

  3. Integrate AI Solutions with Existing Systems: Plan for integration of AI solutions with your current order management, ERP, and CRM systems to sync data across tools.

  4. Focus on High-Impact Areas: Identify and prioritize areas within your customer operations that will benefit most from automation. Rank order such areas according to the business pinpoints and impact potential. This targeted approach maximizes efficiency gains and ROI.

  5. Monitor, Optimize, and Scale: Continuously monitor AI performance and gather feedback. Use insights to optimize and scale automation across more functions.

By following these best practices, you can systematically implement generative AI to stay ahead of the competition, positioning your organization for long-term success in the evolving market landscape. Embrace leading AI-powered solutions to streamline your customer operations and unlock new levels of efficiency and customer satisfaction.

AI-powered Customer Operations Workflow Automation Case Study: UpBrains AI

One standout solution in this space is UpBrains AI, a leader in automating team inboxes for customer operations teams, particularly in the supply chain sector for distributors and manufacturers. UpBrains AI offers state-of-the-art Generative AI-powered solutions to streamline the entire customer operations involving order processing workflow:

  • AI-Powered Email and Order Parsing: UpBrains AI automatically parses incoming messages and attachments, extracting and processing order details with high accuracy.

  • Smart Communication Routing: Understanding the context and content of communications, UpBrains AI ensures queries and orders are directed to the right inbox, folder or team members quickly.

  • Intelligent Document and Attachment Classification: Documents are automatically classified, with support for more than 70+ languages.

  • Intelligent Data Extraction and Entry: The AI system intelligently extracts key order information including order line items, customer details, dates and shipping information and sends to existing order management systems, automating data entry and reducing manual workload. Building information extractors does not require extensive training of AI, as opposed to legacy AI systems. UpBrains AI’s extractor have built-in support for understanding supply chain document understating specifically orders and more. The extractors also can be easily customized for specific business needs of each customer as well, and support documents in many languages.

  • Automated Draft Response Generation: UpBrains AI generates draft responses to customer inquiries, ready for CSR review, allowing CSRs to focus on relationship-building and personalized service.

  • Custom AI-powered Workflows: With a no-code, AI-powered drag-and-drop interface, you can build custom workflows to automate various workflows of order processing, customer communication management, and document management.

Conclusion

Generative AI holds immense potential for distributors and manufacturers, especially in automating and optimizing order processing workflows. By addressing key challenges faced by customer operations teams, Generative AI enhances efficiency and frees up CSRs to focus on strategic, customer-centric activities. UpBrains AI stands out as a pioneering solution in this domain, offering comprehensive automation and intelligent processing capabilities. Embracing these best practices can help your organization navigate the exciting possibilities of Generative AI, ensuring a competitive edge in the market. Contact UpBrains AI to schedule a free consultation on the use cases of Generative AI for distributors and manufacturers, and a demo of their AI-powered workflow automation solution for customer operations.

©

2024

All rights reserved.

©

2024

All rights reserved.

©

2024

All rights reserved.