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No matter the industry, any business leader will tell you that delivering a fantastic customer experience (CX) is a top priority for a firm. According to studies, after obtaining excellent customer service, up to 42% of B2C clients said they were more interested in making a purchase. Additionally, a single negative customer service encounter caused 52% of them to discontinue their purchases.
In order to provide customers with consistent service and experience, businesses are adopting technology. By increasing client interaction and providing round-the-clock customer support, artificial intelligence (AI) is completely changing the e-commerce call center service industry. In addition to revolutionizing customer service, it increases brand exposure and customer loyalty.
We will cover every aspect of automated customer support and artificial intelligence’s contribution to better customer experience in this blog.
Here are a few applications of AI-driven customer support in e-commerce.
Chatbot-based customer support
One of the main functions of AI-powered customer support is intelligent chatbots, which are being used by both small and large enterprises to increase client services (while keeping pricing low).
Sixty percent of internet customers don’t like to wait more than sixty seconds to get a response to their question. By reducing customer wait times and answering their enquiries more quickly, chatbots are boosting customer loyalty.
In addition to providing prompt responses with lightning-fast real-time responses, chatbots can also alleviate the burden on human agents by accurately and human-like interacting with a huge number of customer enquiries.
Predicting consumer needs
You must have been amazed at how e-commerce applications and shopping websites can determine your preferences based on your social media sharing, basket item selection, and frequent page views. This is a machine learning model’s core component.
Processing and evaluating large data streams and determining what actionable insights are available depend heavily on machine learning. Predictive analytics and machine learning can help customer care representatives identify frequently asked questions and answers.
24×7 support availability
Consumers want brands to be available and responsive throughout the year. Automated customer support can help in this situation. It makes it possible for companies to promptly address issues and offer 24/7 customer support. Consumers may get answers to their issues at any time of day or night without having to wait a long time for a response. For businesses who wish to enhance customer service and have a worldwide presence, e-commerce BPO services can prove to be a game changer.
Assisting customers in decision making
Almost 80% of consumers believe chatbots with AI capabilities might assist them in making better selections about what to buy than people.
These days, consumers engage with companies on a variety of devices, therefore customized touch points are necessary to improve the customer’s decision-making process. Outsourcing e-commerce customer support can swiftly answer consumer enquiries, gather comprehensive product or service information, and offer guidance to help customers make the best choices. A human agent takes over the conversation if it gets too complex between the customer and the chatbot.
Furthermore, bots can use their machine learning skills to provide precise answers by learning from past encounters.
Natural language processing
In the past, analyzing customer interactions took a lot of time and included many teams and resources. These repeats are now overcome by natural language processing (NLP), which boosts productivity and customer satisfaction.
One method for training computers to understand human speech is natural language processing (NLP). NLP is extremely important in customer service. Voice intelligence technology can detect terms and their frequency in customer contacts, as well as properly transcribe conversations in real time. By looking for certain trends and themes in the data, an agent can meet the demands of the consumers more quickly.
Sentiment and advanced analytics
Sentiment analysis of customer feedback is a tried-and-true method of determining what consumers think about your brand. Artificial intelligence-powered text analytics tools may evaluate and classify information as neutral, negative, or positive. All words may be grouped and the most pertinent information extracted using NLP algorithms.
Additionally, metrics that assess the customer experience, such the Net Promoter Score (NPS) and the Consumer Effort Score (CES), can be helpful indicators of how customers feel about the business overall.
Robotic process automation
Robotic process automation (RPA) can automate a lot of basic tasks that an agent used to perform. For instance, automating bots to concentrate on information updating, problem resolution, or proactive customer engagement can significantly reduce costs while simultaneously increasing processing time and efficiency.
One of the best ways to find out where RPA may be useful is to ask customer support agents. They can most likely determine which processes have the most system clicks or take the longest. On the other hand, they can suggest routine, simple transactions that don’t need human assistance.
Bottom Line
Thus, an e-commerce industry can expand with AI-powered customer support technology. A business process outsourcing (BPO) company can help an e-commerce firm grow by providing industry experts, a strong workforce, and resources as per the needs of the consumer.