A New Approach to Conversational AI: Transforming Consumer Engagement in the Healthcare Field – Info Lopare

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The recent research conducted by Gartner revealed that only 8% of the participants in the study have ever used chatbots, and only a quarter of those participants would use chatbots again. This finding has prompted me to discuss the dissatisfaction that has been accumulating for over a decade. To begin this story, I must dismiss the popular belief that consumers simply prefer talking to humans: NO! NO! NO! What consumers want is a solution.


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It is easy to blame consumers for all the poorly executed chatbots flooding the digital space. But the truth is, for decades, we have consistently reinforced the consumer belief that the only way to solve a problem is by conversing with a human, by providing them with mostly subpar digital experiences between humans and consumers.

Why is this a problem? Because these chatbots were mainly built to enhance the efficiency of call centers, while technology has long enabled a focus on providing better consumer experiences. Of course, there are a few chatbots that have been intelligently utilized with natural language understanding and CRM integration to demonstrate their ability to improve user satisfaction, increase revenue, and enhance contact center efficiency. Unfortunately, such chatbots are too few.

The problem lies in the fact that all the bad chatbots and decision trees have poisoned the well, and thirsty consumers are reluctant to take the risk and try out good chatbots. Today, many companies are content with the success of launching a chatbot but remain trapped at the bottom of Gartner’s “Trough of Disillusionment.” Yes, I said it, and now that I’ve gotten that off my chest, I will focus on the great opportunity we have, after ChatGPT, to transform the way we engage and activate consumers, with a special emphasis on healthcare.

In short, the main problem with the current generation of chatbots is that they are limited in communication and context, providing an overly rigid and transactional experience. As if that wasn’t enough, since they do not retain information about the user and usually cannot access or adapt to CRM context in real-time, every time a chatbot is used, one has to start from scratch.

Dave Belcher, the co-founder and COO of Tuzag, compares chatbots to the capabilities offered by conversational AI. “Chatbots are essentially versions of self-service flow charts that a customer service representative would use to help a patient find information,” he said. “Though they are helpful in answering frequently asked questions, they fall short of effectively engaging consumers and providing the quick personalized solution they need for activation.”

Consumers mostly view chatbots as obstacles on their way to talking to a human, hoping to at least get some level of resolution if they can overcome the automated voice recognition hell. How many times have we all pressed ‘0’ or shouted “agent” repeatedly to reach a human.

And then, of course, alongside us, a human restarts the triage process. Unfortunately, often even humans lack the sufficient ability or authority to deviate much from the solution offered by the decision system, thus leading us to even greater disappointment.

“It’s not enough to just provide the right information or a suggestion to someone, you have to tailor the solution to the unique needs, desires, environment, and relationships of the consumer. It’s less about delivering information and more about tailoring responses and next best actions to the consumer’s unique intent or needs,” said Belcher. “On the other hand, a conversational AI assistant or coach acts more like an educated advocate, capable of utilizing your context and natural language processing to understand what the consumer is trying to achieve (their intent) and then providing the best unique solution or action.”

In the realm of healthcare, this presents an opportunity to move far beyond patient engagement towards the holy grail of activation and build human-like relationships with consumers, accelerating our progress towards the “quadruple aim,” particularly when it comes to improving patient experience. Imagine having a digital assistant that can help consumers set and achieve personal and clinical goals tied to their unique wellness motivators.

We are not rational beings, so simply providing information to everyone in random transactions, without establishing trust in the digital connection/relationship, is and will never be successful. We must transition from informational engagement to activation. To achieve this, we need a knowledge base with much greater precision and capabilities than what simple chatbots can manage.


– What research showed that only 8% of participants have ever used chatbots?

The research was conducted by Gartner.

– What are the major pitfalls in chatbot development?

Insufficient adaptability to context and conversation, often resulting in rigid experiences.

– How can conversational AI improve consumer activation in the healthcare field?

Through an adaptable and personalized approach to providing solutions based on unique consumer needs and intentions.

– Why is it important to view AI as a supplement to human resources in healthcare?

This allows us to effectively complement and enhance human resources instead of replacing them, aiding in real-time consumer needs and achieving transformation.

– How can technology help in achieving personal health goals?

By building trust and providing personalized information and actions based on each consumer’s unique motivators for well-being.


Gartner – www.gartner.com

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