A practical guide to GenAI applications for customer experience management
According to a survey conducted by Everest Group, supported by TELUS Digital, customer experience management (CXM) leaders plan to invest heavily in generative AI (GenAI) in 2024, with 55% anticipating a spend of US $1 million or more.
This level of investment is easy to rationalize: CXM leaders face a multitude of challenges that generative AI can help solve. Challenges that include retaining customers in a highly competitive market, enhancing operational efficiencies, reducing costs, gleaning insights from vast amounts of data, being able to adapt to rapidly changing market demands and more.
But when it comes to GenAI implementation, where are leaders specifically focusing their efforts? Read on to learn more about some popular customer experience (CX) GenAI use cases, and how the technology can help CXM leaders maintain a competitive advantage.
Everest Group survey results: Enterprise readiness for generative AI adoption in customer experience management
Everest Group, supported by TELUS Digital, surveyed 200 customer experience leaders from around the world to determine their enterprise readiness for the adoption of generative AI (GenAI). Discover the results.
Understanding generative AI applications in CXM
A key to understanding how to implement GenAI applications is first knowing what you have to choose from. When it comes to customer experience, there is no shortage of applications. Some, however, are proving more popular than others in terms of immediate implementation plans.
Text generation
According to a Forbes article, 57% of customers prefer to interact with companies through digital channels like live chat, chatbots, email, text (SMS), social media and more. Considering customer preference for using functions that leverage text, it's not surprising that over half (53%) of CX leaders regard text generation applications as having "high" potential in customer experience management, according to the aforementioned survey. The following are a few of the text generation applications being used to transform CXM processes to be more efficient and effective:
- Personalized content: The Everest Group survey showed that the majority of respondents ranked personalization of customer interactions as the primary reasons for implementing GenAI solutions in their CXM operations. Providing personalized messaging across multiple channels can enhance customer engagement significantly, with McKinsey & Company estimating that personalization efforts can increase marketing return on investment by 10-30%. From customized newsletters to social media posts, GenAI can be used to create messaging tailored to a customer based on their past purchasing behavior and previous support interactions.
- Generative AI chatbots and virtual assistants: Chatbots leveraging GenAI technology can understand the context of a customer query, enabling the tool to handle more complex inquiries and provide accurate, relevant and natural-sounding responses. Further, these chatbots and virtual assistants learn from previous interactions to continuously improve their output, saving CX leaders the time and resources previously needed to train their virtual assistants to better understand customers.
- Call summarization: Automated summaries of voice interactions produced by GenAI tools can eliminate the need for manual post-call transcription. Call summarization tools leveraging GenAI can also provide salient call details and next-step action items for tailored follow-ups.
- Language translation: GenAI can be leveraged for real-time language translation, enabling human and virtual agents to communicate with customers in their preferred language. As well as enhancing personalization, this GenAI application helps eliminate language barriers, fosters inclusivity and provides a more positive overall customer experience.
- Automatic report generation: CX leaders seeking business intelligence from vast amounts of unstructured data can use generative AI applications to summarize that data and output usable reports. In fact, over half (53%) of respondents in the aforementioned survey plan to deploy generative AI solutions for data and analytics in the next 6-12 months. GenAI can quickly process sales data, consumer feedback and other data sources to provide predictive analytics to forecast emerging trends and changing consumer behavior. This intelligence can help businesses make strategic decisions and weather market changes more readily.
The potential for text generation for GenAI is significant, and the timelines for implementation reflect leaders eagerness to capitalize on the possibilities — almost half (46%) of CX leaders are already in a piloting/deploying stage.
Code generation
Code generation applications use programming and auto complete capabilities to speed up the software development process, improve code quality and assist in bug detection.
For leaders responsible for internal software development teams, this can be a game changer. Not only can programmers work more efficiently, GenAI makes software development accessible even for non-programmers. For example, any user can input a prompt like "Write a query that generates a report for the trailing 12 months that shows the number of password assistance requests handled by our customer support queue" and the code generator will output code snippets based on the specific requirements. With these sorts of mundane tasks covered, more experienced programmers can free up their time to concentrate on complex coding tasks.
Audio generation
One of the most commonly used applications of audio generation in customer experience is interactive voice response (IVR). As compared to traditional IVR systems that provided scripted responses, GenAI-powered IVR systems output context-relevant responses, providing customers with a conversational experience that sounds less robotic and more like a human agent.
Further, generative AI has propelled voice assistant technology forward by providing users with more naturally flowing and context-sensitive conversations, in turn enabling a more efficient use of the technology. "Fundamentally, this is the first time we're able to speak to computers in our language," said Bret Kinsella, the CEO, founder and research director of Voicebot.ai, in an episode of Questions for now, a TELUS Digital podcast.
Kinsella predicts that voice assistants will revolutionize how work gets done by allowing for significantly greater efficiency and efficacy, using agent-assist voice technology as an example. "This co-pilot assistant would actually listen to the call in real time and just be flashing things on the screen based on what they [the customer] are saying," he notes. With GenAI enabled voice technology, new levels of efficiency in customer interactions are being unlocked.
Image generation
GenAI-powered image generation provides a significant advantage for marketing personalization. Email campaigns can be created with different imagery specific to the audience based on their subscriber data. This provides visual impact before the customer even starts reading the email content. For example, a retailer that sells camping gear and knows a customer's location can personalize that customer's email with an image of a nearby campsite or park without having to embark on a world-wide photoshoot.
Image generation also brings a new level of personalization to applications such as virtual try-on features. For example, GenAI-enhanced shopping tools are offered as part of Search Generative Experience, an experimental version of Google Search offered to subscribers in the United States. The search engine's virtual try-on tool allows users to see how apparel from partner retailers looks on models representing a diverse range of size and shapes, skin tones and ethnicities. Using this feature, a customer can see how the clothes will look on someone who closely resembles themself.
Synthetic data creation
One way synthetic data creation is benefiting CXM leaders is through the creation of data for market research. In the past, brands have relied on creating and using personas to better understand and engage with their audience. Now, however, companies can leverage "synthetic customers" created using GenAI. These data-driven customer representations simulate the actions of real-word customers.
The advantage they offer is that rather than being static like a persona, synthetic customers — like real customers — are designed to be dynamic and ever-changing. Commonwealth Bank of Australia (CBA), for example, has been exploring the use of GenAI developed synthetic customers to test products. Dan Jermyn, chief decision scientists at CBA, acknowledged the value of synthetic data during a South By Southwest presentation: "By drawing on simulated experiences of daily life to emulate behaviors, we're testing whether these GenAI chatbots could provide qualitative and quantitative understanding of how customers might respond to changing contexts, everyday financial challenges and new products."
Further, businesses may have access to vast amounts of data containing personally identifiable information, posing a compliance risk. In these instances, synthetic data created by GenAI can be substituted for real-world data to refine marketing strategies with the inherent risk of leveraging personal identifying information.
Video generation
According to a survey of online consumers conducted by Wyzowl, a video production company, 89% of respondents say that watching a video convinced them to buy a service or product. Video is a powerful marketing tool for businesses to leverage, but the time and resources required for video production can be prohibitive. Video generation helps streamline these efforts significantly with a script serving as a prompt.
In addition to creating marketing videos, video generation tools can be used to create engaging instructional pieces for customer support queries. For concepts that could be confusing when explained using text only, video can offer a highly engaging and easy-to-follow means of communication. For example, creating a short explainer video that walks customers through common troubleshooting tasks can help to reduce frustration and improve the customer experience.
Enhancing the customer experience with GenAI
With vast amounts of use cases, there's no question that generative AI is transforming the CXM landscape. While the degree varied, of the 200 customer experience leaders surveyed from around the world in the Everest Group survey, all believe GenAI will have a positive impact on operational efficiencies, customer satisfaction and the reduction of costs.
Getting the most from GenAI requires time, resources and expertise. It's not surprising that many CX leaders plan to work with a third-party partner. In fact, 76% of respondents are planning to leverage an outsourcing partnership in some capacity to help them implement a generative AI solution in their CX operations. Regardless of where you are in your GenAI journey, our team can help! Contact an expert today.
