Customer Engagement Suite with Google AI
Through AI-powered features, Google Cloud has assisted thousands of businesses in providing better experiences to millions of customers and employees since it introduced Contact Center AI in 2018. It is now integrating the robust features of Contact Center AI with its most recent generative AI technology to provide a new application, Customer Engagement Suite with Google AI, since new generative AI capabilities are proving to be increasingly valuable for customer service operations.
Provide a complete customer experience to delight your clients
The Customer Engagement Suite with Google AI is an end-to-end application that combines the speed and multimodality of our most recent Gemini 1.5 Flash model with our most sophisticated conversational AI products and omni-channel contact center as a service (CCaaS) features. This makes it possible for customer support departments to provide outstanding and reliable customer experiences across all channels. Additionally, it supports an ecosystem of third-party services that include workforce management apps, CRM software, phone systems, and connectors which include user interfaces, other system connectors, and BigQuery-like data sources.
An exceptional blend of AI-powered talents
Four distinctive features of Google AI’s Customer Engagement Suite have the potential to greatly enhance both the quality of the customer experience and the rate at which generative AI is adopted.
Omnichannel: utilizing apps, voice, email, online, and mobile
Consistent customer experiences across web, mobile, voice, email, and apps are orchestrated by omnichannel engagement. Consumers can communicate with your company through a variety of channels, and the contact center as a service (CCaaS) feature facilitates smooth client interactions while maintaining enterprise-level security and data privacy.
The Conversational Insights solution, formerly known as Contact Center AI Insights, is designed to give operations management and quality assurance teams KPIs, categories of inquiry topics to focus, and areas for improvement based on real-time data analysis from across your customer operations. Unlike other systems that just evaluate a limited fraction of contacts, its native quality management applies AI-based analytics to all of your customer interactions, and the Quality AI function auto-scores all of your customer discussions. These enhance the caliber of customer interaction and the effectiveness of customer service agents.
Multimodal: Using the newest Gemini models
Gemini’s multimodal capabilities allow the Customer Engagement Suite with Google AI application to support multimodal information, such as text, audio, and images.
Using Conversational Agents to develop hybrid virtual agents using rule-based controls and generative AI
The Conversational Agents package offers a special blend of adaptive generative AI and stringent controls with instructions in plain language. By combining the Gemini model’s expanded topic coverage with prescriptive actions for predefined inquiries, these hybrid agents offer dynamic, tailored self-service.
With automation and point-and-click configurations, the Conversational Agents console offers business users a turn-key solution that speeds up the development, deployment, and upkeep of virtual agents. Because virtual agents may be created and controlled without the need for coding, a larger range of employees can find the product easier to use and configure. When you develop hybrid virtual agents, they may handle more queries to boost consumer self-service and free up customer care people to handle more specialized conversations, all while lowering expenses associated with customer operations.
Based on accuracy: Making use of Agent Assist features to raise worker output
To improve the accuracy of the responses the Conversational Agents and Agent Assist solutions produce, the Gemini models they employ might be based on data from your company’s own resources. The Agent Assist tool helps customer service personnel handle client concerns more quickly and accurately by giving them on-the-spot support.
Additionally, it has included new features including live translation, summarization, coaching model, generative knowledge help, and smart reply.
- Based on the context of the current discussion, the generative knowledge help function proactively suggests search queries and is trained on Gemini models for appropriate responses. As a result, customer service agents may interact with customers with more timely and relevant information.
- In order to enhance response accuracy and process adherence, the coaching model may be adjusted using the data from your company to provide customer-care personnel with contextual, step-by-step instruction in real-time during client interactions.
- After every interaction, the summarizing tool sends discussion summaries to your customer service agents. The model enhances the quality of summary for lengthy, multi-issue talks, with a latency of less than five seconds, significantly cutting down on handling time.
- The customer service representative and the customer have a conversation, and the smart reply feature presents the customer’s suggested responses to the representative. A customized model that has been trained on your conversation datasets transcripts of recorded conversations calculates these.
- For chat chats, the live translation tool offers bi-directional translation and automatically recognizes the languages used. More than 100 languages are supported, glossaries and sentence pairs can be customized without the need for additional model training, and professional rephrasing and grammar and spelling corrections are supported.
For instance, Best Buy uses automatic call summarizing to resolve issues up to 90 seconds faster than representatives who would otherwise have to manually record summaries.
