We know that the customer always comes first. They are why businesses exist and why they continue to be more customer-centric.
However, with the ever-changing customer expectations, the need has gone beyond just serving them. Today, the expectation is to predict customer preferences and influence them suitably.
Successful businesses strive to know the tastes, lifestyles, behaviors, and changing preferences of their customers in almost real-time. With this knowledge, they constantly realign their offerings to stay relevant and to deliver superior value to their customers.
In a nutshell, they ‘know’ their customers and this is the ‘extra’ that differentiates them from ‘ordinary’.
This is for good reasons. Prolific uses of smartphones and friendly applications, including social media, have dramatically altered customer expectations. At the same time, the unprecedented growth of cloud services and machine learning applications have provided remarkable Artificial Intelligence tools and potential. The adoption of AI is helping companies build differentiating capabilities at an unprecedented scale by providing real-time inputs on customer responses, predictive analytics, and deep analysis of data.
Towards these business objectives, call centers—the gates to Customer Relationship Management—continue to constantly refine their stake.
Over a very short period of time, they have leapfrogged from using evolving technologies for slashing costs to serve to deliver differentiating experiences to customers. This is where technology meets the human capital and its intelligence—or say, where the rubber meets the road.
In today’s world, neither AI nor human intelligence is individually sufficient to cater to the ever-changing business challenges and objectives. The key lies in the ability to get humans and machines to work in unison. Successful customer interactions now rely on a smooth blend of both human judgment and artificial intelligence.
Opportunities to leverage AI in customer interface
AI has evolved as a tool to bring forth tremendous potential to dramatically enhance the customer experience. When adopted and deployed correctly, it helps companies solve customer queries faster and more accurately, thereby improving the CX and freeing up the call center agents to add further value to customer interactions.
The efficiencies also help companies scale their customer relationship and support operations significantly.
Here are the top use cases for AI in contact centers.
1. Intelligent bots
Bots, or chatbots as they are commonly referred to, are the most frequently used communication tools that are based on AI technology. They gather basic information and enable self-service for customers with simpler queries. The most measurable result is the reduction in the manual workload of call center agents which is replaced by automated virtual text and voice-based conversations with customers in the real world.
2. Intelligent automation of workflow
With the information gathered from customers, along with historical data, relevant case attributes get populated automatically. This improves the accuracy of the information collected. Based on the automated attributes, the call is intelligently routed to agents with the proper skill and expertise to handle and deliver a first call resolution.
3. Intelligent recommendations for actions
Based on the real-time information profile created through AI, it also makes suggestions on next actions and steps to agents. Such recommendations tend to give the agent more robust inputs to drive a higher level of customer satisfaction.
4. Intelligent predictive analytics
Predictive analytics delivered by AI tend to present relevant data from past interactions with the agents. This enables them to make intelligent decisions and take proactive steps to resolve customer queries.
Accelerated adoption in current times
The pandemic has challenged businesses in new ways. Abilities to address them proactively using fewer resources has only accelerated the adoption of technologies like AI and ML. The need to track and monitor performance and continue to maintain a strong customer relationship in these challenging times has made the integration of these technologies into business and call center operations imperative.
Pillars to smart success
Success is in making the call center operations run smoother while offering a friendlier customer experience. This can be done through leveraging technology that is available. Tools like machine learning, natural language processing, and other forms of voice intelligence give the call center agents the inputs that help them make the interactions with customers more effective.
Following are some of the ways in which AI enables the efficiency of a call center agent.
1. Smart use of resources
Human agents are uniquely equipped to address different complexities in real-time based on their skills and exposures. AI and analytics use self-learning algorithms to match the customer’s personality based on previous interactions.
Thereafter, these AI software can assess the requirement of resources to solve the query—from a simple chatbot to more complex ones where human assistance may be needed. The bottom line is efficiency in the operations and improved customer experience.
2. Smart analytics
The words and the tone that a customer uses provide a wealth of information—from whether the customer is happy and satisfied, to whether he is disgruntled and unhappy. While in the works, analysis of tone through voice recognition and natural language processing can give actionable insights into both an individual customer as well as trends over large amounts of data. Both enable the human agent to use his intelligence to adjust and address concerns through appropriate tactics and strategies. All this culminates in offering a superior customer experience.
3. Smart understanding of customer behavior
Insights into trends in customer behavior allow a business and the call center to predict emerging customer needs. Intelligent use of this information enables the business to develop efficient and effective practices. AI also provides detailed information on customer profiles to a human agent who then quickly adjusts his approach based on individual customer data. It also potentially enables the agent to make additional sales through addressing upsell or cross-sell opportunities.
4. Smart suggestions
Real Time Speech Analysis (RTSA) adds to the listening capabilities of agents and provides insights into conversation flow and recommendations for responses to customers. Such recommendations enable the agent to respond and address the customer proactively and more appropriately, thereby positively impacting customer experience.
The technology also enables the supervisors to ensure compliance to defined standards of business conduct and take corrective actions quickly when needed. In the end, equipped with smart suggestions, the call center is able to deliver a standard, yet successful, customer experience across the board.
5. Smart judgments
Smart predictions on their own are only one side to the coin. AI provides actionable insights and models that create even more opportunities for increasing the value of human intelligence in judgment. With faster and superior predictive insights and models, empowered humans to make smarter judgments to combat customer queries.
Artificial Intelligence is unlikely to replace humans in call center operations any time soon. On the contrary, these technologies allow the agents to use the information in a more efficient manner to deliver a superior experience for the customer.
Sifting through the recommendations of AI still needs human intelligence in leading customer relationships. Together, they deliver a framework that is suitably termed Augmented Intelligence. The industry is at the inflection point, and enabled agents are key to bringing the ‘extra’ to the ‘ordinary’.
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