Tag: Data Analytics

Customer service in the B2C domain has gone through a “rollercoaster” wave since the end of the global pandemic. 72% of customers plan to remain loyal to brands that provide fast and exceptional customer service. 78% of customer service agents find it challenging to balance between speed and quality of service. This has increased from just 63% in 2020. Rising service-related work pressure has increased labor turnover by 19% in customer servicing teams.

According to this McKinsey article, two-thirds of millennials expect to receive real-time customer service. Three-fourths expect a consistent cross-channel experience. It comes as no surprise that more companies are turning to AI technology to scale their customer service to the next level.

In this blog, let’s learn more about how AI can be leveraged to deliver highly personalized customer service even at scale. 

What is AI-powered Customer Service?

AI-powered customer service is all about leveraging AI technology to scale every aspect of customer’s interactions with the brand. Depending on business requirements, customer support teams can utilize this technology in different ways. 

For instance, AI-enabled chatbots can provide immediate responses to customer queries, instead of making them wait for a human response. According to HubSpot, 90% of customers rate it important to receive a prompt response (within 10 minutes) from service agents. 

How does this benefit customer-focused companies? Besides increasing engagement, AI-enabled customer service tools can provide cross-selling and upselling opportunities. Besides, it works to reduce manual work, thus also the operational cost of customer support.

A Zendesk CX Trends report also found that customers are now comfortable with companies collecting their personal information. This enables companies to provide a personalized experience to their customers. 

In 2024, 80% of customers have had a positive experience while interacting with an AI-powered customer service tool. 

How does AI-powered customer service deliver a personalized experience at scale? Here are some ways:

  1. Leveraging customer data and insights

76% of customers want companies to leverage their data to provide a personalized experience,

With AI technology, customer support teams can have a more personalized interaction with customers. This requires them to completely understand the customer profile. On initiating this interaction, AI-powered tools provide customer service agents to understand their:

In turn, this is effective at improving the agent’s productivity and efficiency in addressing the customer query or problem.

  1. Self-servicing capabilities

In the wake of the COVID-19 pandemic, more customers started to migrate to self-service digital channels as their “first point of interaction.” 81% of customers try to take care of their issues before contacting a live agent.

AI-powered self-servicing tools leverage their ability to process natural language to understand customer queries and provide appropriate solutions. Using resources like knowledge bases and FAQs, AI in customer service can quickly find answers to customer queries – without having to wait for human intervention.

To assist customers, self-service portals can help them find their solutions, thus saving both time and effort.

  1. Predictive analytics

AI-enabled predictive analytics tools can drive more “precise and scalable” personalization. Using predictive analytics, companies can utilize customer data to anticipate their needs and behavior patterns. These insights allow them to:

By integrating predictive analytics into customer service, companies can continuously improve prediction models and stay “tuned” to customer preferences. To improve their prediction efficiencies, AI-powered models analyze various data sources including:

  1. Sentiment analysis

With its natural language processing or NLP capability, AI tools in customer service can easily understand and interpret human language. This can help this tool understand human sentiment and take appropriate actions. Besides this, AI-powered sentiment analysis tools can gauge the customer’s brand perception from:

How does sentiment analysis improve customer service? Companies can use these AI-driven insights to personalize their customer experience and respond appropriately to their concerns. Besides, by using machine learning algorithms, sentiment analysis tools can detect “fake” reviews with 85% accuracy.

  1. Chatbots

According to the Zendesk CX Trends report, companies using AI in customer service could resolve issues 30% faster. AI-powered chatbots are crucial for providing faster responses and answers. Beyond simply answering customer queries, chatbots are delivering a personalized experience by:

Effectively, an AI-enabled chatbot acts as a “virtual buddy” that understands individual customer’s needs and preferences.

  1. Hyper-personalization

By combining AI technology with data and analytics, companies can now “hyper-personalize” their customer service. According to this Deloitte report, companies can hyper-personalize the entire customer journey including:

Through hyper-personalization, companies can customize their products and customer services based on their data, preferences, and behaviors. Their real challenge lies in how to scale personalization without “overwhelming” the customer. Using AI technology, they can deliver personalized content that is in tune with changing customer behaviors and preferences.

Conclusion

Customer engagement is a focus point for companies of all sizes worldwide. As customers expect more personalized experiences, AI-powered customer service is the answer to keeping them engaged and loyal.

At InovarTech, we help you leverage AI technology for your business benefits. Our AI-enabled data analytics can scale your business to the next level. Get in touch with us to know more!