Transforming Customer Experience In Manufacturing With Microsoft Azure OpenAI Service

In order to retain customers and stay competitive, machinery and manufacturing firms must understand their customers’ specific needs, preferences, and challenges. Beyond the initial sale, customer engagement through the equipment lifecycle strengthens brand loyalty, generates recurring revenue through service contracts and parts sales, and provides valuable insights for product improvement. Manufacturers who prioritize ongoing communication and build trust with their customers are in a better position to navigate challenges and secure repeat business.

Microsoft commissioned Forrester Consulting to interview 20 representatives from 16 organizations and conduct a Total Economic Impact™ (TEI) study to better understand the benefits associated with Microsoft Azure OpenAI Service.¹

In the full TEI study, Forrester projected that an industry-agnostic composite organization would see risk-adjusted operating income growth of between $33.6 million and $169.0 million over three years, which is driven by increased top-of-the-funnel engagement, improved conversion rates, and reduced churn. Over the same three-year period, the composite is also projected to recognize between $12.3 million and $28.4 million in cost savings due to increased employee productivity.

This abstract will focus on the machinery and manufacturing industry’s use of Microsoft Azure OpenAI Service and their value to their organizations.

As part of the broader TEI study, Forrester interviewed two representatives from manufacturing organizations:

• Senior director at a US-based manufacturer of imaging products with 7,000 employees.
• Head of engineering at a global industrial supply manufacturer with 160,000 employees.

Azure OpenAI Service presents a unique opportunity for machinery and manufacturing firms to elevate customer engagement. AI-powered knowledge bases empower customer support agents to provide enhanced technical guidance to clients in real time, improving customer satisfaction scores and reducing the amount of time required to address customer inquiries. Additionally, organizations use Microsoft Azure OpenAI Service to quickly generate and translate marketing materials, product documentation, and RFPs, freeing up staff to devote more time to customer-facing solutions. Azure OpenAI Service also analyze customer data and equipment performance, enabling more personalized service offerings and leading to improved customer satisfaction, retention, and upselling opportunities.

INVESTMENT DRIVERS

The interviewees’ organizations adopted Microsoft Azure OpenAI Service to:

• Enhance customer service with AI-powered knowledge bases. Interviewees reported that they adopted Microsoft Azure OpenAI Service in part to create intelligent internal chatbots that access and process through a vast internal knowledge base of FAQs, troubleshooting guides, and product manuals. Without a centralized, language-enabled knowledge base, customer service representatives and sales agents were often unable to provide contacts with up-to-date answers to their inquiries, leading to long wait times, low customer satisfaction scores, and lost sales. The senior director at the imaging manufacturing firm stated: “[When evaluating a purchase], customers want to understand how to use a product, what regulation is behind it, and how to learn about it. That can get complex. The idea is to help this process with AI.”
• Create marketing campaigns informed by sentiment analysis. The interviewees shared that previously, their organizations grappled with mountains of unstructured data, including from customer conversations, notes on their CRMs, and service call notes. They needed a solution that could integrate these datasets and leverage sentiment analysis to understand exactly where customers and prospects were in the buying cycle to create targeted marketing campaigns that resonate with specific customer segments.
  
  The head of engineering at an industrial supply firm reported that prior to adopting Microsoft Azure OpenAI Service, their data on customer interactions was scattered across a few platforms, leading to operational inefficiencies: “The challenge before Microsoft was that every marketing tool provided inconsistent data points. … Translating unstructured data into structured data is very manual and time-consuming. It would have been impossible for us to do the sentiment analysis we do today.”

• Streamline document creation. The interviewees noted that prior to implementing Microsoft Azure OpenAI Service, developing product documentation, technical specifications, and requests for proposal was often a time-consuming process. They also noted that translating these documents into multiple languages led to additional costs. To save their marketing and product teams time, the interviewees sought ways to quickly create and translate documents. The senior director at the imaging manufacturer reported: “We have tens of thousands of SKUs, and they all have product descriptions in dozens of languages. Anytime I wanted to translate anything, even if it was a brochure or a prospecting email or a battle card, I would have to source that translation through a third-party partner, pay for the translation, and validate internally with native speakers.”

Key Results

The results of the investment for the interviewees’ organizations include:

Increased revenue. The interviewees reported that using Azure OpenAI Service improved their understanding of customers, leading to an increase in customer engagement and revenue. They specifically highlighted how they used the solutions to score opportunities and create stage-specific marketing campaigns.

• Interviewees reported that the generative AI solutions built on Azure OpenAI Service enabled them to analyze customer interactions and determine customer sentiment and buying stage. This allowed the manufacturers to identify customers or prospects who were expressing dissatisfaction with current equipment or nearing a service contract renewal. Armed with this knowledge, the interviewees sent personalized content and promotions to customers who were most likely to convert, leading to an increase in qualified leads and conversion rates.

*For the composite organization presented in the full TEI study

• The senior director at an imaging manufacturer stated: “We are using generative AI in Azure to apply spend more intelligently based on customer signals and customer behavior, as opposed to a sequential marketing plan. We’re trying to understand where the customer is in the buying cycle and what buying group they are looking at. I then only spend money on [marketing] tactics that are in context of their need and that leads to improved performance at a lower cost overall. If all goes well, our digital marketing costs will be reduced by at least 50%.”

• The interviewee further detailed the Azure OpenAI Service sales use case: “Now the system will automatically place accounts in the appropriate marketing stream for the stage they are in. If I know that this account just signed with a competitor, I now know that I don’t need to spend money on mid- to lower-funnel tactics on that account. … If the account is six months or a year out from renewing their contract, we can employ tactics that generate conversations for us.”

Improved customer service. Interviewees noted that they used Microsoft Azure OpenAI Service to build an AI-powered knowledge base to help their agents and salespeople better serve prospective and existing customers.

• The AI-powered knowledge base enabled the organizations’ salespeople and customer service agents to type questions into the chatbot and immediately get up-to-date answers to customer inquiries. Equipped with the knowledge base, employees were able to quickly access product data, manuals, and pricing information, creating seamless customer interactions that led to reduced resolution times, improved customer satisfaction (CSAT), and reduced churn.

*For the composite organization presented in the full TEI study

• The interviewee went on to estimate the financial impact of the productivity gain: “We computed the savings to create a chatbot that can help the agents. It’s €600,000 per year of savings, mainly because there are resources to help with technical support questions. Out of seven [technical support] FTEs, we could reallocate three of them.” 
• In addition to the language-enabled knowledge base, the interviewee reported that their organizations were working on deploying an externally facing chatbot with Azure OpenAI Service that could independently resolve complex customer inquiries. They shared that additional departments, such as HR and legal, have also built internal chatbots to help employees access up-to-date information.

Time savings on document creation and translation. The interviewees reported that implementing Azure OpenAI Service unleashed time savings in creating a range of marketing and product materials.

• According to the interviewees, Microsoft Azure OpenAI Service significantly reduced the amount of time required to craft technical documents, such as product specifications, user manuals, and RFPs. Azure OpenAI Service’s large language models automatically generate drafts based on existing templates and technical data sheets, populating key sections and suggesting improvements to reduce the amount of manual effort required for technical writers. The senior director at the imaging manufacturer described the impact of the time savings: “[Azure OpenAI Service] is empowering our marketing teams as they’re generating content. It gives us the ability to generate content at scale, with the same amount of people that we have or even with less people.”

• The interviewees also reported that they used an Azure OpenAI Service solution to generate personalized emails for diverse customer segments. These messages highlighted specific product features relevant to a customer’s industry, targeted promotions based on the customer’s characteristics or purchase history, or specific proposed solutions based on individual needs. This level of personalization not only improved customer relationships, but also saved marketing staff time. The senior director at the imaging manufacturer stated: “With personalized emails, it gets rid of the ‘blank-page problem.’ It will give you something to start with and then you can iterate on it. When you consider content generation, iteration, and personalization, it’s a 20% to 30% productivity gain.”
• Beyond generating content, interviewees also reported that they used Azure OpenAI Service to translate content, leading to significant time and cost savings. The senior director at the imaging manufacturer stated: “Translation services are expensive, and many of them employ machine learning now anyways. Having generative AI available to us is really allowing us to have a much faster, much, much cheaper option for translating materials. Instead of spending $5,000 to $10,000 outsourcing a translation, we can use a chatbot to get 90% of the way there, and then validate it with a native speaker internally.”

Strengthened security and compliance posture. According to the interviewees, there was widespread interest in adopting generative AI before the implementation of Azure OpenAI Service. The interviewees speculated that without Azure OpenAI Service, their employee base would begin using publicly available AI tools to create marketing materials or personalized emails, leading to potential data privacy concerns. The senior director at an imaging manufacturer stated: “If you are not implementing AI in an easy and accessible way, your employee base will just use their personal tool and that’s a big risk. Giving employees easy, fast, and private access to ChatGPT is easy with Microsoft Azure’s back end, and that is a big risk reduction because at least the data stays with you. You can keep it in-house rather than throwing [data] into the wild.”

APPENDIX A: ENDNOTES