It’s the era of the Experience Economy. The relationship your customers have with your company is as essential as the value and cost of your products and services. This makes customer experience a competitive landscape. To thrive in such a situation, SMB leaders like you can use AI-powered chatbots to offer high-quality customer interactions.
Chatbotsenable SMBs to quickly address and resolve customer issues, even with a small service team. Chatbots canprovide answers to frequently asked questions, run surveys, collect contact information, provide promotional offers, clarify basic regulations, anddirect customers to the right teams for further interaction. With3.2 billion messaging app users projected by 2022, the potential for user engagement through chatbots is enormous. Especially since many younger, digitally-savvy customers prefer interacting with a brand via a chatbot over a human agent.
However, even as the capabilities of chatbots continue to improve and evolve, challenges remain. Here are some key aspects to keep in mind when you deploy chatbots in your customer service.
1. Chatbots can miss the context
Currently, a big concern with AI is that it cannot detect and grasp the tone and context of a conversation. Bots lack emotion and human logic, which are the driving forces of customer service. One way to overcome this is by informing your customers that they are speaking with a chatbot. In cases where human advice is needed, the customer should have the option to seamlessly continue the live chat with a human agent.
2. They can provide irrelevant responses
Too often, users conversing with chatbots may get less than satisfactory answers. For eg, thissurveyfound that more than half of the respondents believed chatbots did not understand their questions. According to 47 per cent, chatbots do not deliver exact answers, and take longer to process and react to queries (44 per cent). To prevent such a situation, businesses must regularly upgrade their chatbot programs by leveraging conversation logs and live chat information. The more data it has to evaluate and process, the more efficient the chatbot will become. Automatically collecting volumes of data over time lets it intelligently respond to all types of queries.This can help improve the natural language processing technology used and thus enhance your chatbot’s features and performance.
3. Chatbots may not be able to provide personalised responses
Chatbots can provide templatised or bland answers to your customers. This can make your customer feel frustrated. To avoid this, enable your bot access to the user history, their existing requests, and preferences – these can be provided by a robust CRM. The bot can use this information to engage customers and provide appropriate responses. Another way to infuse some life into the conversation is by giving your chatbot a unique identity. Decide on a persona, use warm greetings and enthusiastic language, or some visual elements to make your customer forget that they are interacting with a conversational AI tool.
Also, avoid using chatbots as an overt marketing channel. For SMBs, with limited marketing budgets, it may be tempting to send frequent push notifications to all users through this tool. However, such messages can seem intrusive and annoying to customers looking to just get a resolution to a query. Thus, timing is crucial. Identify opportunities to start a fresh conversation or motivate people to take action. Ensure that the message is relevant and helpful so that your customer gives their full attention to it.
Deliver faster customer service using smarter chatbots
Clearly, the key to ensuring great customer service is striking the right balance between digital and human elements.So while chatbots can respond to your customers’ questions and issues in a timely and effective manner, your service agents can focus on more complex customer service challenges.
With the help of Salesforce’s Service Cloud Einstein, you can create CRM-connected chatbots to check the status of claims, make changes to orders, and more, using natural language processing on real-time channels. Einstein bots pay attention to the context of the consumer and connect all data from the back-end systems to develop appropriate responses. When the demands become more complex, the bot is smart enough to transfer the case to a human agent effortlessly. They also collect and qualify customer information before connecting them with the appropriate representative.
Creating such CRM-connected chatbots is also easier now. With Einstein Bot Builder, you can get a visible, guided, and declarative approach to create your bot and connect it to business processes and back-end systems. Thus, you can easily build your own customer service data scientist to speed up self-service and provide your customers with the superior support they need.
