Good Bot, Bad Bot: The Three Key Factors for Effective Chatbot Customer Experiences

Customer expectations for service continue to increase at the same time that the volume of support interactions skyrocket. In response, companies rightly turn to automated experiences in order to meet demand.

Chatbots and virtual assistants have become an increasingly popular tool for businesses to interact with customers at scale, but not all are created equal.

At Verint, we know that a good chatbot should understand a customer’s intent, provide an accurate response, and most importantly, actually perform actionable service. Good bots don’t just say things, they actually do things.

On the other hand, a bad chatbot that only provides simple question-and-answer functionality and might even provide inaccurate information can lead to frustration, dissatisfaction, and a negative image for your business. It also hurts your budget.

In this blog post, we explore the key factors that make a good chatbot or virtual assistant and what to avoid when creating a chatbot for your business. By understanding these key elements, you can ensure that your chatbot provides a positive experience for your customers.

Understanding Customer Intent

Customers reach out to organizations for a whole host of different reasons. And, while effective chatbots are able to assist with a range of specific issues, they often struggle with ones that are more complex.

For a chatbot to resolve a query, it first needs to understand what the customer’s intent is and whether handling it falls within the chatbot’s capabilities.

Good Bot

Actionable Service: Again, good bots should be able to do things for your customers. This means that the virtual assistant can, for example, book a flight, change a medical appointment, or sell a product to the customer—right in the chat. Good bots don’t just deliver information—they deliver service.

Improved customer experience: Understanding a customer’s intent enables the chatbot to provide relevant and accurate responses to the customer’s queries. This leads to a more efficient and enjoyable interaction for the customer, which can improve overall satisfaction and customer loyalty. 

Increased efficiency: When the chatbot is able to accurately understand a customer’s intent, it can respond more quickly and effectively, reducing the time required for the customer to receive the information they need.

Verint Intelligent Virtual Assistants (IVAs) draw upon a huge natural language understanding (NLU) library to understand customer intents and extract key information from conversations, including:

• Any specific entities mentioned, e.g., place names or products
• The context of a request, e.g., a specific time or location
• The sentiment of the conversation, e.g., the customer is annoyed

Better handling of complex issues: A chatbot can leverage the power of machine learning to handle increasingly complex issues. If a customer makes a query that a chatbot isn’t trained to resolve—or is unsure about—this information can be fed back to a human expert, who can then create a new intent classification and generate a conversational flow that enables the chatbot to resolve the query in the future.

Bad Bot

Frustration and dissatisfaction: If a chatbot is unable to understand a customer’s intent, the customer may become frustrated and dissatisfied with the interaction. This can lead to a negative experience and lower customer satisfaction.

Increased workload for human agents: If the chatbot is unable to accurately respond to the customer’s queries, the customer may need to speak to a human agent for assistance. Now, handing over a conversation to an agent is actually the sign of a well-functioning customer journey, but if it’s done unnecessarily—the chatbot can’t understand the intents it is designed to service, for example—then the increased workload for human agents results in increased support costs.

Missed opportunities for business: If the chatbot is unable to understand a customer’s intent, it may miss opportunities to upsell products or services, or to provide relevant information that could improve the customer’s experience or decision-making process.

Tailoring Service and Promotions Based on Customer History

A chatbot has the potential to draw upon rich customer history, including customer service interactions and previous purchases, to provide a personalized experience.

Good Bot

Improved customer experience: By using customer history to personalize service and offer specific promotions, customers are more likely to engage with the chatbot and make a purchase as the conversation has been tailored to their specific needs and interests.

Increased customer loyalty: Personalized service can help develop a sense of customer loyalty, as customers feel valued and appreciated by the business. This can lead to repeat business and a higher lifetime value for the customer.

Increased sales and revenue: By understanding the customer’s history, the chatbot can recommend products or services that are more likely to be of interest to the customer, leading to increased conversion rates and therefore sales.

Bad Bot

Lack of relevance: If a chatbot is unable to personalize its service and offer specific promotions, the customer may have a negative experience and reduce the likelihood of the customer engaging with the chatbot in the future.

Decreased customer loyalty: Without personalized service, customers may feel that the business does not value their needs and interests. This can harm customer loyalty and reduce the likelihood of repeat business.

Decreased sales and revenue: Without personalized promotions and offers, the chatbot may not be able to effectively sell products or services to the customer—resulting in decreased sales and revenue for the business.

The Ability to Seamlessly Hand Off Conversations to a Human Agent

Even the most intelligent chatbots can’t solve 100% of customer queries. At times, particularly for more complex issues, they need to be able to hand the conversation over to a human agent.

Good Bot

Improved customer experience: If a chatbot understands when a customer wants to speak to a human agent and is able to pass the conversation over, it can greatly improve the overall customer experience. Customers are more likely to be satisfied with the outcome of their interaction if they are directed to their preferred method of resolution. 

Better handling of complex issues: While the ability for bots to handle complex issues is clearly a benefit to the organization, there remain times when human agents are better equipped to handle sensitive issues that require empathy and a human touch. By allowing the chatbot to pass these interactions on to a human agent, the customer is more likely to receive the help they need—and the issue is more likely to be resolved to their satisfaction. 

Increased efficiency: By allowing the chatbot to handle simple queries and pass more complex or sensitive issues to a human agent, the business can improve efficiency and ensure faster resolutions.

Bad Bot

Frustration and dissatisfaction: If customers cannot speak to a human agent when they want to, they may become frustrated and dissatisfied with the interaction. This can lead to a negative experience and poor customer satisfaction. 

Deflection to more costly support channels: If the chatbot is not able to pass complex issues on to a human agent, the customer is likely to use an alternative, potentially more expensive channel, in an attempt to reach a human agent. 

Missed opportunities to build customer relationships: If a customer is unable to speak to a human agent, the business misses out on the opportunity to build a relationship with the customer and demonstrate the value it places on customer service. This can harm the reputation of the business and reduce customer loyalty.

Now that you know the dos and don’ts of building an effective chatbot, all you need is a solution that makes it easy to build automated customer experiences across a range of engagement channels. Well, you’re in the right place.

Verint Conversational AI technology combines cutting-edge natural language processing (NLP), machine learning, and robust intent understanding to deliver effortless interactions with your customers at scale.

As part of our conversational AI, Verint Intelligent Virtual Assistant allows the quick and efficient deployment of automation across an organization’s channels to deliver consistent and personalized self-service experiences, while also improving contact center operations.

Equipped with pre-built NLU models and extensive analytical tools, Verint Conversational AI allows an organization to scale a hybrid workforce to provide excellent customer outcomes. Conversational AI also includes a low-code bot-building environment so companies can quickly launch, tune, and improve their bots for an immediate ROI from their virtual assistant.

Want to learn more? Here’s what analysts have to say about why Verint is a trusted conversational AI provider.