The Definitive Guide to Keeping Users Engaged With Chatbots

Communication is a key tool that determines the success of every business. For this reason, using chatbots as a replacement for human customer service representatives should be done correctly. One of the common mistakes most businesses make in that area is using chatbot scripts and strategies that don’t keep users engaged. Hence, making the business lose its potential customers.

In this guide, we will show you the best approaches to keeping your target audience engaged and leaving them happy. You will also get to see practical case studies of other brands and their chatbot strategy for success.

Tactics for Keeping Users Actively Engaged with Chatbots

Here are some strategies to help keep your audience engaged and satisfied when using chatbots:

Easy Access to the Chatbot Feature

An easily accessible chatbot is the start of a great user experience for your target audience. Businesses should start by creating a visually appealing landing page/homepage. A cluttered or disorganized homepage could make it difficult to find the chatbot. The clutter could also make potential customers leave your website.

Ensuring your chatbot suits all users, including visually impaired individuals, is crucial. Consider prioritizing your chatbots to always understand user input for these special individuals and respond appropriately.

A significant factor that influences the accessibility of the chatbot feature is its accessible language, color contrast, and fonts. Even though no official fonts are specified in most accessibility standards, chatbot developers may consider using friendly fonts like Sans Serif at a large enough size for easy readability.

Ensuring Conversation Tone Matches the Company’s Branding

“Tone” has a significant impact on user experience in chatbot conversations. Most users prefer a more conversational tone when interacting with chatbots. However, it’s also imperative that this tone matches the company’s branding. The brand’s tone of voice is from the organization's overall personality, applied everywhere that deals with the brand.

Up to 81% of people claim they buy from a brand they share equal values with. Hence, ensuring your brand voice through the chatbot is the golden ticket to creating a unique connection with your audience. If you're still trying to define your brand's voice, here are some tips to help:

1. Look for examples: Take note of other brand voice and tone examples from top brands or companies in the same niche. Learn what makes the brand voice unique and attractive to its audience.

2. Take note of what you want your brand voice to be: To define your brand voice, you also need to understand the characteristics you want from your brand voice. Do you want a fun, inspirational, hopeful, young, serious, inspirational, hopeful, young, or direct tone?

3. Create guidelines for your brand voice and share them with the developer: Your developer and other employees need to be familiar with your brand voice to stay in tune with it. Once you determine what exactly your brand voice is, create a step-by-step guide for the chatbot developer.

High Quality and Frequently Updated Data Training

Without good and updated data training, your business’s chatbot may behave wrongly. Hence, it’s imperative to effectively train the chatbot to understand the customer’s needs and what the customer wants.

To train your chatbot, the developer will need to use many datasets for the machine learning algorithm. Your chatbot learns from the available data set to answer questions prospective customers ask.

Datasets are typically utilized with natural language processing (NLP) to give the most precise and relevant responses. Common techniques that make data useful for chatbots may include text annotation, named entity recognition, audio annotation, and NLP annotation.

Consistent Delivery of Problem-Solving Results

For your chatbot to consistently deliver the best results, it has to be accurate. Unfortunately, most businesses don't have chatbots that easily comprehend a customer's intent. Many times, the reason for that is natural language understanding (NLU). Please note that NLU depends on AI-driven software that doesn't always get everything correct.

Due to the inaccuracy of AI, businesses may not always successfully satisfy prospective customers. However, there are four major KPIs that could help in improving this accuracy to give a problem-solving result. These KPIs include mapping the confusion rate (CR) of the virtual assistant and leveraging NLP to improve the understanding of the business's chatbot in colloquial terms. 

Other helpful KPIs include knowing your business audience and hyper-personalizing and framing empathetic responses using advanced sentiment analysis. Once you are aware of the most important KPIs to track and utilize, you may observe an improvement in the chatbot's ability to solve prospective customers' problems.

Successful Case Studies to Consider for Your Marketing Model

Some of the case studies from successful brands to learn from include:

Ask Julie by Amtrak

Amtrak is a corporation that delivers rail passenger service that exceeds the expectation of customers. With close to 20,000 employees, they are able to serve close to 30 million passengers every year. The company's chatbot feature, "Ask Julie," has a 50% growth every year. Why? Amtrak's business model is to primarily ensure customers are quickly satisfied with logistical travel solutions. 

Julie's designers wanted a chatbot that could function as Amtrak's best customer service representative, with close to 5 million answered questions yearly. The bookings made through the chatbot also resulted in an average of 30% more revenue than other means.

Drift for MongoDB

Before MongoDB started utilizing chatbots, they had a significant success rate with the typical live chat. However, it began to seem less efficient due to factors like space and time. 

Drift is a lead generation chatbot that efficiently handles prospective customers' inquiries and redirects them to sales reps if they are most likely to buy. With Drift, MongoDB could effectively automate lead-qualifying conversations, making them have more conversations. It could also automate the scheduling process, which helped in generating leads from conversations. 

Next IT for Charter Communications

Charter Communications is one of the fastest-growing cable providers in the United States. The firm has approximately 16,000 employees and 25 million customers. With this number of employees and customers, it's no surprise why "Next IT" will need a well-functioning chatbot. 

Charter Communications incorporated its chatbot, Next IT, in 2012. However, the company had 200,000 live chats monthly before switching to chatbots.

Thirty-eight percent of the monthly live chats were conversations about forgotten usernames and passwords. Switching to Next IT made 83% of all chat communications handled by the bot.

Conclusion

User engagement is important for boosting brand experience. For many businesses, it also helps increase customer loyalty and trust. Unfortunately, keeping up with every prospective customer can be difficult and, many times, expensive. For this reason, utilizing chatbots the right way is imperative. When using these chatbots, ensure they are accessible and constantly updated to give users helpful responses when needed.