Harnessing Elephants Memory:Reimagining Customer Service with Google Cloud

Elephants are renowned for their extraordinary memories. They can remember important locations like watering holes or food sources for years, even decades. This is crucial for their survival, especially during droughts. This unparalleled ability to remember and learn is what sets elephants apart. In a similar vein, modernized customer service no longer focuses solely on resolving issues in the moment.? Instead, it draws upon data and insights to create a lasting memory of every customer interaction. This comprehensive understanding of each customer's history, preferences, and past experiences allows businesses to provide proactive and personalized support, transforming customer service into a powerful engine for building relationships and loyalty.

To build this memory, customer service functions are facing greater urgency to modernize their operations, driven by increasing interaction volumes, expanding customer engagement channels and costly agent turnover. AI holds enormous potential to address these challenges. As per a McKinsey report, Generative AI in customer service functions could increase productivity by 30-45%. Moreover, Generative AI could further reduce volume of human-serviced contacts by up to 50%. But it’s difficult for customer service operations to adopt AI at scale because of outdated technology stacks, poor interoperability across systems and security & privacy concerns.??

Google Cloud helps unlock this AI opportunity by providing an end-to-end, comprehensive customer service technology offering that leverages leading AI innovation, seamless integrations and connectivity across the Google ecosystem, and enterprise readiness at scale to deliver the following key benefits:

• Boost agent & employee employee productivity?

Let's talk about how to make agents and employees more productive. When they work better, they can improve customer service by being more helpful and giving the same good service every time. Keeping good employees and making them happy is important because a lot of companies lose half of their agents every year.?

In customer service, agents often dig through various systems (policy, billing, and so on) to find the customer’s details they need. What if agents didn’t have to hunt for info anymore? What if they can see all the info in one place? This would speed up their response time instead of typing the same thing into multiple systems. It’s like giving agents Google’s search skills to help them right away. Or, use AI to make short versions of call notes or emails, and even tell agents what to do next. Agents wouldn’t need to type up notes for the next person to follow up on. These summaries could be made like magic, cutting down on processing times and getting answers back faster.?

• Improve self-service & deflection rates?

Self-service options are essential for handling common questions and reducing the burden on agents, especially during peak times. Additionally, deflection rate is a valuable metric that measures the effectiveness of directing customers to the right assistance channel, reducing costs and enhancing customer satisfaction.

Virtual agents built on google cloud platform can handle customer questions in a more natural, human way. Google can figure out what you mean when you search on Google Search. That same ability to figure out intent powers the agents built on google cloud. The agents can smoothly switch between subjects, keep customers engaged, and keep going 24/7. This also works with multi-modal options, putting together text, voice, and even pictures when agents talk to customers.?

Additionally, these virtual agents can live-translate over a hundred languages, kind of like Google Translate but always on. By talking to people in their own language, organizations can relate to their customers better, and make them happier and more productive. Again, we can do this by figuring out what the user means with AI and connecting them with the right expert or giving them step-by-step guides so they can finish their task. Generative AI models can better tell what a person wants because they’re trained on a huge database and can understand a wider range of words and phrases, which helps them know how people really talk.

• Enhance insights & customer predictions?

Finally, businesses have realized that information is key to giving customers unique experiences, which directly affects how many customers they get and keep. Because of this, businesses are now investing more money in things like knowing what's going on around them, learning by doing, and measuring how people feel. So now there is detailed information about customers - how do organizations use it to make things better and sell more products or services, or to keep customers from leaving?

Organizations can directly pull their contact center data into Google analytics and data tools like BigQuery and Looker to dig deeper. Our data cloud isn't just for data scientists; it's for anyone in the company who works with customer information: call center managers, conversation designers, quality control, and call center analysts. Firms can use machine learning models to predict customer lifetime value or churn rates. From there, they can create next best action plans to improve cross-selling or VIP routing and give your best customers the best experience.

With Google Cloud, organizations can figure out why customers are calling (the top questions they're asking), update FAQs, and then link the updated FAQ to their human and virtual agents. As a result,? agents are always giving the latest answers, and there's a feedback loop where new questions are fed back into the insights view.

By mirroring the elephant's remarkable memory, customer service becomes a powerful engine for building relationships and loyalty. How is your organization approaching AI-powered customer service? Share your thoughts below!