Google Cloud Generative AI for Customer Service Modernizer User Guide

Google Cloud Generative AI for Customer Service Modernizer

Specifications

• Product: Generative AI for Customer Service
• Price Range: $65-90 billion
• Economic Potential: North America

Product Information

Generative AI for customer service is a cutting-edge technology that leverages multimodal models capable of generating text, images, and media to transform customer care operations. It aims to enhance customer inquiries, improve response times, increase productivity by 30-45%, and reduce human-serviced contacts by up to 50%. This technology can also identify opportunities for up- selling, cross-selling, and boosting net promoter scores.

Across industries, the customer service function is being transformed by generative AI. Today’s multimodal models — capable of generating text, images, and other media — are augmenting the work customer care teams already do. Plus, they can act as a stand-alone agent to support customer inquiries.

Not only does gen AI help customers get the answers they need, faster, but it delivers far-reaching benefits and economic value across the organization. The latest research shows that applying gen AI to customer care functions could increase productivity by 30-45% over the current performance baseline.1

Gen AI could also help customer care teams identify and act upon up-sell and cross-sell opportunities. It could boost net promoter scores. It could reduce average handle times. And so much more.
In this guide, we explore the most promising use cases of gen AI for customer service modernization and share key considerations for starting your journey

Elevate your customer service with Gen AI

The economic potential of gen AI in customer operations (North America)1
Across industries, the customer service function is being transformed by generative AI. Today’s multimodal models — capable of generating text, images, and other media — are augmenting the work customer care teams already do. Plus, they can act as a stand-alone agent to support customer inquiries.

Not only does Gen AI help customers get the answers they need, faster, but it delivers far-reaching benefits and economic value across the organization. The latest research shows that applying gen AI to customer care functions could increase productivity by 30-45% over the current performance baseline.1

• McKinsey. (2023). The economic potential of generative AI.

Up to 50% reduction in human-serviced contacts with gen AI1

• Gen AI could also help customer care teams identify and act upon up-sell and cross-sell opportunities. It could boost net promoter scores. It could reduce average handle times. And so much more.
• In this guide, we explore the most promising use cases of gen AI for customer service modernization and share key considerations for starting your journey.

Gen AI is already having a tangible impact on customer service

It helps:

Boost agent and employee productivity.

• Coach your people with real-time recommendations
• Summarize previous interactions
• Connect cross-channel customer experiences
• Transcribe calls live, with multilingual translation
• Provide useful and relevant suggestions with Smart Reply
• Build an internal help desk

Modernize chat and voice infrastructure.

• Access core Contact Center capabilities out-of-the-box
• Leverage the latest AI-powered tools
• Offer a mobile-first experience

Improve self-service and deflection rates.

• Respond to questions with natural language
• Steer conversations based on customer intent
• Enhance conversations with multimodality (text, images, and voice)
• Retrieve information and perform basic transactions
• Create virtual agents grounded with citations

Enhance insights and customer predictions.

• Measure customer service responses and quality metrics
• Enable segmentation and personalized customer responses with customer 360
• Generate FAQs based on conversation insights

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When it comes to customer service, today’s customers have sky-high expectations — all centred around speed, self-service, and specificity. Until now, it’s been hard for traditional customer care models to keep up with this evolving need.

Yet organizations know how important it is. Customer service has the biggest impact on customer loyalty,2 and getting it right can yield major benefits for businesses. That’s why your first step should be to identify the areas which stand in the way of meeting your customers’ expectations and explore how gen AI can improve them.

• Forbes. (2023). Top Customer Experience Trends In 2024.
• Pre-event survey of 113 Google Cloud Next ‘23 Leaders Circle attendees

Wells Fargo is developing a virtual AI assistant called “Fargo” driven by Google Cloud’s DialogFlow CX AI technology to hyper-personalize the customer experience.
The Illinois Department of Employment Security is using Contact Center AI to rapidly deploy virtual agents to help more than 1 million citizens who lost their jobs to file unemployment claims. Virtual agents handle more than 140,000 phone and web inquiries per day, and phone virtual agents handle 40,000 after-hours calls per night. The state of Illinois anticipates an estimated annual savings of $100M based on an initial analysis of IDES’s virtual agent data.

• #1: The factor affecting customer loyalty is customer service
• 73: of business leaders say customer service and chatbots are a priority gen AI use case for 20243

Prioritize quick wins while laying strong foundations

• For fast ROI, start by piloting high-value, lower-risk gen AI use cases such as self-service resolutions, AI-powered agent tools, and AI-augmented operations management.
• In parallel, explore use cases that can deliver the highest ROI, but may require some time to set up. Depending on your business, this could be something like real-time suggestions for next actions, or applications using voice or video. Work with your team to determine the right areas to invest in, remembering that you may need to reevaluate your tech stack and strategy to support these use cases.
• To set yourself up for long-term success, consider standing up a holistic gen AI tech stack. A single-provider gen AI ecosystem can be a powerful force multiplier, driving broader impact and enabling you to respond to changing market conditions faster.
• For example, with Google’s comprehensive gen AI ecosystem, you can easily deploy new use cases without having to stitch together point solutions, while optimizing for flexibility and preventing vendor lock-in. It’s a robust full-stack platform that enables future innovation.

Recipe for AI success
GE Appliances’ SmartHQ consumer app will use Google Cloud’s generative AI platform, Vertex AI, to offer users the ability to generate custom recipes based on the food in their kitchen with its new feature called Flavorly™ AI. SmartHQ Assistant, a conversational AI interface, will also use Google Cloud’s generative AI to answer questions about the use and care of connected appliances in the home.

Read the full story

Centralize data to make it more useful than ever.

You may have been collecting data for years. But have you been using it to its full potential? If your data is still stuck in silos or in different formats, then your first priority should be to centralize and standardize it for easy access by gen AI tools.
Then, think creatively about how to use your data to train or customize models, with a focus on data sources that are competitive differentiators and unique to your business.

Use multimodal data such as images, videos, and audio recordings to reach harder-to-engage groups, such as non-native speakers or those with disabilities. Google’s multimodal model, Gemini, can combine text and visual inputs and translate between modalities.
And remember, customers are more likely to share their data with you if they trust you — so building trust should be a priority.

Transforming customer experiences with data insights
Google Cloud’s technologies allow us to blend digital and human experiences, which has been transformative for our customers. It’s all about being more proactive, leveraging data insights and truly understanding our customers to deliver world class service.”

Vaughan Paul
VP Digital Consumer, Optus

Educate employees about your evolving ecosystem

• Invest in gen AI skills training so your employees can derive actionable insights from these new tools.
• For example, gen AI tools can leverage unstructured conversational data to reveal new insights, such as key drivers of ticket causes and customer sentiment. Armed with this information, employees can productively resolve complex issues.
• Reskill employees as job roles transform. Customer service agents will need to act as a ‘human-in-the-loop’ to provide expert guidance on complex cases, and prevent model bias from reaching the customer.
• And don’t forget to plan for effective change management. Communicate new responsibilities, update internal policies, and create a culture focused on responsible use of gen AI. Encourage employees to flag issues where they see them, especially during pilot phases.

Ensure safe governance and stewardship of customer data

Take a proactive approach to data quality, security, and governance. Add interventions across the entire data lifecycle and establish data governance procedures for new types of data coming in.
With the regulatory landscape evolving quickly, actively monitor regulations to ensure compliance with new laws, and keep track of how your tech vendors are helping you comply.

For example, Google was one of the first in the industry to publish an AI/ML Privacy Commitment, which states that customers should have the highest level of security and control over data stored in the cloud.

Be bold and responsible.

Take a holistic approach to responsible AI. Enact an organization-wide strategy and enterprise-wide controls that encourage thoughtful and safe adoption and scaling of new tools.
Establish a Center of Excellence as the single source of truth for internal policies around responsible AI. This function might focus on training modules for employees, handbooks, and stakeholder management.

And, to build trust and transparency, always explain when and how AI is used. For example, Google watermarks images generated by Google AI tools, and offers image markups for publishers to indicate when an image is AI-generated.
See Google’s Responsible AI guidelines.

Plan for ubiquity and access

• This new computing paradigm uses more data, from more sources, in more flexible ways than ever. Choosing the right foundation models and tools will be critical.
• Offer training in gen Al tools and techniques to a broad range of roles. Enable your teams to participate in rollouts and provide feedback, recognizing that new ideas can come from different parts of the organization.

And think about how Gen Al can support your broader accessibility and inclusivity goals. For example, it can provide multimodal support

• such as audio, video, assistance, and interfaces – to meet individual needs.

There’s more to Gen Al than customer service modernization
Get tips for getting started with gen Al in these areas

Time to take action with gen Al?

• When a new technology moves as fast as Gen Al, it can be hard to keep up. Google Cloud helps you solve for all the considerations outlined in this guide.
• Our gen Al tools are backed with frameworks, tools, and governance structures to help you hit the ground running.

Contact us to set up a time to discuss how to get started on your Gen Al journey.

FAQ

• Q: How can Gen AI benefit customer care teams?
  • A: Gen AI can help customer care teams improve response times, reduce human-serviced contacts, identify sales opportunities, boost net promoter scores, and enhance overall customer experience.
• Q: What are some examples of successful Gen AI implementations?
  • A: Wells Fargo’s virtual AI assistant and the Illinois Department of Employment Security’s virtual agents are successful implementations of Gen AI, showcasing improved customer experiences and significant cost savings.

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