Conversational marketing: Are you using the right chatbot to optimize results?

If your patients and prospects are expressing chatbot frustrations, it may be time to consider whether you’re using the right type. 

All chatbots are not the same, and with the rapidly advancing capabilities available on today’s self-service landscape, there are plenty of opportunities to push beyond the basics and upgrade to a more effective approach. That’s especially important when it comes to building an effective conversational marketing strategy.  

But before we get into that, let’s cover a few basics.

What are chatbots?

Noting that AI chatbots are “programmed to provide human-like conversations to customers,” IBM says they’ve become essential to helping organizations provide 24/7 customer support: “Designed to do almost anything a customer service agent can, they help businesses automate tasks, qualify leads, and provide compelling customer experiences.”

However, all chatbots are not the same — nor do they possess the same capabilities to meet customers’ needs. 

IBM describes the primary types of chatbots as: 

• Rule-based chatbots — which are the most basic type. Also referred to as “decision-tree” chatbots, this type tries to map out user conversations to drill down on intent and are limited to the specific scenarios for which they’re designed. 
• Menu-based chatbots — which give users a list of options from which to choose that will hopefully lead to the needed answer. That may work well for simple queries, but not so much for users with more complicated questions. When that’s the case, you may end up with a frustrated customer in search of human help. 
• Hybrid chatbots — which provide a little of both worlds by combining automation with the human touch. The chatbot handles the easy stuff and punts to a live representative when things get complex. 
• Keyword-based chatbots — which look for keyword combinations within the text and generate a response based on the analysis. The result is “more flexible and natural conversations” during which users are able to ask more complicated questions. 
• Machine-learning chatbots — which are the most advanced. Also referred to as artificial intelligence (AI) chatbots, they learn from each conversation to help improve their responses as time goes on. As a result, users can ask complex questions and receive more natural responses. 

Chatbots and conversational marketing

According to Drift — a sales and marketing company credited with coining the term — conversational marketing is “a dialogue-driven approach to marketing that uses real-time conversations to engage site visitors and quickly move them through the buying journey. It creates an authentic experience that builds relationships with customers and buyers.”

Of the options available, IBM notes that machine-learning chatbots can best support conversational marketing needs. 

“A machine-learning chatbot is a form of personalized conversational marketing software that acts like a human by stimulating conversation through a mobile app or website,” IBM says. 

To do so, the firm notes that two types of advanced AI technologies are used — machine learning and natural language processing (NLP) — to perform data analysis and teach the chatbots to “interact as humans would.” 

IBM provides descriptions of both:

• Machine learning is “the use of complex algorithms and models to draw insights from patterns in data. These insights can be used to improve the chatbot’s abilities over time, making them seem more human and enabling them to better accommodate user needs.”
• NLP is “a form of linguistics powered by AI that allows computers and technology to understand text and spoken words similar to how a human can. This is the foundational technology that lets chatbots read and respond to text or vocal queries.”

Benefits for healthcare marketers 

IBM lists a variety of ways that machine-learning chatbots can benefit a conversational marketing strategy — which also applies to healthcare marketers adopting this approach. These include:  

• Improving audience engagement: “Chatbots don’t have the same time restrictions as humans, so they can answer questions from customers all around the world, at any time. …”
• Answering customers’ questions: “…Chatbots are a practical way to inform your customers about your products and services, providing them with the impetus to make a purchase decision. …”
• Delivering personalization at scale: “By using machine learning, your team can deliver personalized experiences at any time, anywhere. …”
• Creating “more memorable” ad experiences: “Since ads are catered to the individual’s preferences, they become more memorable for your target audience. …” 
• Reaching customers “across a variety of touchpoints”: “Conversational marketing can be deployed across a wide variety of platforms and tools. …”
• Gaining cookieless insights: “…Machine-learning chatbots can collect data and new insights about your target audience without the use of cookies. They can be used to gather customer email addresses and phone numbers, discover key customer interests and behaviors, and automatically qualify leads.”

To learn more, check out IBM’s resource, “The ultimate guide to machine-learning chatbots and conversational AI.”