Organizations are looking to AI to help bridge the gap as demand for a better and more personalized consumer experience develops.
AI advancements are paving the way for enhanced efficiency across the enterprise, especially in customer service. Chatbots are still at the forefront of this shift. Still, other technologies like machine learning and interactive voice response systems are ushering in a new era for customers — and customer care employees. Although not every piece of technology is appropriate for every business, AI will play a critical role in the future of customer support.
The Use of Chatbots
You are not alone if you have seen an uptick in chatbot usage. Enterprise organizations are increasingly using them to automate portions of the customer experience. Organizations see considerable cost savings and becoming more efficient as they rely less on service agents and live agents. Artificial intelligence is commonly used in customer service through chatbots.
Businesses already employ chatbots of various levels of complexity to answer basic questions about delivery dates, balances owed, order status, and other information gathered from internal systems. By transferring these commonly asked questions to a chatbot, the customer support team will be able to assist more individuals and provide a better overall experience while lowering operational expenses.
US companies spend close to 1.3 trillion dollars annually on customer Support. If you were able to offload 1% of those calls, it would save 13 billion USD per year.
Assistance from an agent
Agent assist technology is used in many modern omnichannel contact centres to automatically translate what the customer is asking, search for knowledge articles, and display them on the customer care agent’s screen while they are on the phone. The method can save both the agent and the customer time and minimize average handle time, saving money.
Self-serve options
Customer self-service refers to customers’ ability to discover and obtain the assistance they require without the aid of a customer service representative. When given the opportunity, most consumers would prefer to handle problems independently if provided the necessary tools and information.
Self-service functions will become more common as AI advances, allowing customers to resolve issues on their own time.
Automation of robotic processes
Many simple operations that used to be performed by an agent can now be automated using robotic process automation (RPA). For example, automating bots to focus on updating information, resolving incidents, or offering proactive outreach to consumers can substantially cut expenses while improving efficiency and processing time.
Asking customer service workers is one of the best methods to determine where RPA can help with customer service. They can probably decide which processes take the longest or have the most system clicks.
Alternatively, they may recommend basic, recurring transactions that do not require the intervention of a human. When prioritized and implemented appropriately, this business process optimization may save customer service firms millions of dollars each year.
“Automation is cost-cutting by tightening the corners and not cutting them. – Haresh Sippy”
Sentiment and advanced analytics
Sentiment analysis and advanced analytics are two of the most important aspects of advanced analytics. In today’s customer care teams, sentiment analysis assesses and detects how a customer feels. Some solutions can even see client dissatisfaction and alert a team leader or representative to intervene and de-escalate the issue.
When combined with a voice of the customer tool, Sentiment analysis can provide a more accurate and complete picture of client happiness. Sentiment analysis tools from companies like Brandwatch, Hootsuite, Lexalytics, NetBase, Sprout Social, Sysomos, and Zoho proactively evaluate client feedback.
AI Training
Many training teams began utilizing AI to create simulations to measure employee aptitude for managing various situations as the COVID-19 epidemic forced employees into distant positions. Previously, training consisted of classroom instruction, self-paced learning, and a final exam, which is considerably more challenging to implement in remote or hybrid workplaces.
New agents can practice their responses with their natural counterparts. At the same time, AI plays the role of the consumer, allowing them to test out dozens of conceivable scenarios and guarantee that they’re ready to address any issue a user or client may have.
Knowledge Management
Knowledge management is an essential tool for any firm in today’s knowledge-driven economy. Knowledge management may help firms become more efficient and productive by strengthening information-sharing procedures. However, implementing this best practice can be inefficient and lower productivity levels if you don’t have the right tools. The three key knowledge management components are sharing knowledge, producing new knowledge, and successfully utilizing current knowledge.
Knowledge management can be challenging for many firms due to rapidly changing digital and client landscapes. Optimizing your knowledge management processes will help your team communicate and collaborate better, make faster decisions, and stay ahead of the competition.
Conclusion
To improve customer experience in enterprises, various technical solutions can be deployed. Each tool or technology has its own set of features that can be used to speed up, simplify, and improve knowledge acquisition.
Consumers are more demanding than ever, and technology is crucial to bridging this gap. They demand experiences as fluid and effortless as the greatest they’ve ever had. On the other hand, Artificial intelligence may play a critical role in this equation by increasing the efficiency of your operations and services.
