Reinventing Shopper Engagement With Microsoft Azure OpenAI Service

In an increasingly competitive landscape, retail businesses are searching for ways to ensure their growth engines are firing on all cylinders. This focus hinges on crafting future-oriented digital experiences that not only anticipate customer needs, but also fulfill them seamlessly. To achieve this, organizations are increasingly adopting generative AI-powered tools that enable them to deliver high-quality digital experiences and improve customer engagement.

Microsoft commissioned Forrester Consulting to interview 20 representatives at 16 organizations and conduct a Total Economic Impact™ (TEI) study to better understand the benefits, costs, and risks 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-funnel engagement, conversion rates, and reduced churn. Over the same three-year period, the composite organization 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 how organizations in the retail and consumer goods space use generative AI solutions to drive customer engagement. As part of the broader TEI study, Forrester interviewed three representatives from two retail organizations: ­

• An executive vice president at a US-based online retailer.
• A head of data and a data lead at a European omnichannel electronics retailer.

The retail interviewees said that prior to implementing generative AI solutions with Microsoft, their organizations encountered a range of issues that prevented them from delivering engaging and personalized customer experiences that can drive revenue growth. From an inbound perspective, both website and store customers often had difficulty discovering the products they wanted. Without a centralized knowledge base, contact center agents, chatbots, and store associates could not provide customers with up-to-date product information, which negatively impacted customer experiences and satisfaction. Interviewees also reported challenges with building outbound engagements. Interviewees said that while the average consumer increasingly seeks content and product recommendations that are relevant to them, it’s practically impossible for human content creators to generate personalized go-to-market (GTM) content at scale.

As the organizations struggled with customer support and marketing content generation, it became challenging to acquire new customers and retain existing ones. To address these issues, the organizations invested in genAI solutions with Microsoft’s Azure OpenAI Service. The investment enabled them to increase revenue through improved content personalization, enhance customer experience with AI-powered contact centers, and reduce costs by streamlining the content generation process.

INVESTMENT DRIVERS

The interviewees’ organizations described a variety of challenges that led them to adopt Microsoft’s Azure OpenAI Service:

• Shoppers respond better to personalized offers, but creating and managing them at scale is difficult. By adopting Azure OpenAI Service, interviewees’ organizations sought to generate content that was either tailored to individual customer preferences (which can improve conversion rates, retention, and average annual spend) or optimized for search engines (which can increase top-of-funnel prospects). But creating personalization at the individual customer level proved operationally challenging — if not impossible — due to the wide variety of retail customers. The head of data at the electronics retailer described their organization’s legacy approach to customer service: “We want to send the right products to the right people. In the past, even if I don’t have a dog, I [was] receiving dog food newsletters. This is because marketing campaigns are done at a general group level, not at the individual level.”
• Shoppers need help discovering and selecting the right product. The interviewees highlighted the need to help customers with everything related to pre-purchase research. They said this could translate into Azure AI-powered search engines to better understand natural language queries and provide more accurate results, which can make it easier for customers to find what they’re looking for. The executive vice president at the online retailer noted: “Having [product pages] organized from actual, real-time reviews helps us with customer experience because they now have all the information they need to evaluate their purchase decisions. [Prior to using Azure OpenAI Service,] we had the greatest amount of data in our industry, but the data was all over the place. We didn’t have all the information organized.”
• Contact centers were inefficient and created negative experiences for customers and agents. The interviewees shared that their organizations struggled to deliver exceptional customer service through their traditional contact centers. High call volumes and slow call handle times often led to long wait times and declining customer satisfaction (CSAT) scores. The organizations sought to improve their contact center experiences by equipping their agents with knowledge bases to help them efficiently respond to customer inquiries. The organizations also aimed to replace aging contact center systems such as interactive voice response (IVR) options with AI-enabled chatbots. The head of data at the electronics retailer stated: “We had tried to make the first customer interaction go through an IVR. Our customers hated it. … [With Azure OpenAI Service,] we want to bring [our Net Promoter ScoreSM (NPS)] back to being positive within the first three months.”
• Creating go-to-market content is time-consuming and difficult to manage operationally. Interviewees said that in adopting Azure OpenAI Service, their organizations aimed to streamline their marketing efforts and to save employee time on creating personalized email content, website and social media copy, and detailed product descriptions.

Key Results

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

Revenue growth. The interviewees’ organizations leveraged Azure OpenAI Service to improve engagement with prospective and existing customers, driving significant increases in revenue.

• Improved conversion rates from personalized, AI-generated content. The interviewees’ organizations use the solutions to generate more personalized content, which they share with prospects through email, social media campaigns, and their websites. The interviewees reported that personalized content leads to an increase in overall conversion rates and a decrease in customer churn. The data lead at the electronics retailer noted: “When we send a personalized newsletter, the conversion rate is double what it would be [with a generic newsletter]. … Previously, we could do two to four personalized newsletters per month; now we can do as many as we want.”
• Increased top-of-funnel traffic from search engine optimization (SEO). The interviewees’ organizations used Azure OpenAI Service to create high-quality, keyword-rich content that was tailored to improve search engine rankings. Interviewees said that by analyzing trends and user behavior, the solutions provided valuable insights for creating targeted and relevant content that attracts larger audiences, drives organic traffic, and expands the top of the sales funnel. The executive vice president at the online retailer described the improvement in SEO: “[Azure OpenAI Service] helped us with our SEO. Because we have good content now, it pushes us into higher rankings. Now we pay less money [for paid search engine campaigns], so there’s millions of dollars of savings because of that.”

*For the composite organization presented in the full TEI study

*For the composite organization presented in the full TEI study

Improved customer satisfaction. The interviewees’ organizations used Azure OpenAI Service to redesign their approaches to their contact centers, which led to an improvement in CSAT and NPS scores.

• AI-powered chatbots to enhance customer self-service experience as well as empowering contact center agents and store associates. By using Azure OpenAI Service’s advanced natural language processing, the interviewees’ organizations were able to create chatbots to respond to complex customer questions quickly and accurately. The chatbots can also adjust to customer preferences and attitudes to provide proactive assistance, improving the overall customer experience. The executive vice president at the online retailer described their organization’s new contact center process: “One metric we pay close attention to is the adoption rate of customers using our chat service instead of calling. We’re seeing high adoption rate and customers like it.”
  
  The interviewee went on to project that the chatbot may save their team more than $500,000 per year in agent time savings in the future.
  
  Interviewees also said they expect that as the chatbots become more mature, they will deflect more inquiries away from customer service teams, leading to time savings for their customer support teams. The head of data at the electronics retailer said, “We should be able to save 20% to 30% of the customer service agents’ and associates’ time.”

*For the composite organization presented in the full TEI study

• Development of AI-powered knowledge bases. The interviewees shared that their organizations used Azure OpenAI Service to build interactive repositories of knowledge that included important FAQs, product details, pricing information, and troubleshooting guides. When customers reached out to customer service or sales agents, the agents could quickly search and retrieve accurate information from the knowledge bases, which enabled them to provide informed and consistent assistance. The executive vice president at the online retailer noted: “The agent can go into this interface and get the answer for a caller. Being able to answer the question on the spot can make the difference of either losing the sale or getting the sale. … It is helping with our NPS.” The interviewee estimated the knowledge base saves their organization’s 3,000-person customer experience team roughly 10% of their time.

Time savings for content generation. The interviewees’ organizations used Azure OpenAI Service to generate a wide range of marketing assets and product information pages.

• Personalized marketing content. With the tools, the organizations automated the creation of personalized newsletters by analyzing customer data, preferences, and purchase histories, which eliminated the need for manual segmentation and customization. Interviewees reported that previously, marketing asset generation was so time-intensive that their organizations were unable to generate personalized campaigns at scale. The data lead at the electronics retailer noted that quickly generating tailored newsletters enabled the organization to increase its revenue: “Compared to last year, we’ve increased [newsletter-driven sales] by 200%. [With Azure OpenAI Service,] you have more accuracy. You are sending the right messages to the right people.”

• Efficiencies in technical product writing. The interviewees reported enormous time savings from using Azure OpenAI Service to create product descriptions. The data lead at the electronics retailer reported: “A person writing product descriptions can do 100 pieces per month. With Azure OpenAI Service, we are doing 1,000-plus per month. The productivity gain is huge, and this is with us limiting the AI to ensure it’s safe and we trust the solution.”
  
  The interviewee went on to say: “With the time savings, staff can evaluate other marketplace processes and onboard new sellers. They stopped doing the manual work, and they do more work on the value chain.

Appendix A: Endnotes