In our last post, we discussed how business are deploying and benefiting from chatbots. Now that you have a basic understanding of what chatbots are and how they work, the next step is implementing them into your business model.
For life sciences companies that are unsure of where to begin, we’ve outlined six factors to ponder before you begin the implementation process:
Chatbots are great for streamlining business. However, to be truly successful, you must clearly define your goals for the chatbot. Is it improving customer service? Helping patients refill prescriptions? Setting up automated billing reminders?
Strategizing how your chatbot will improve your business and developing clear goals with defined metrics is crucial for a successful application.
When implementing a chatbot, it’s important to identify which one would be best suited for your business goals. For example, if your end goal is to improve customer service, a simple menu or button-based chatbot would be the best choice. More complex interactions or tasks would be better suited for contextual-based chatbots.
This is a big one; ensure there is a solid knowledge base to support the chatbot’s “brain.” This is the repository of knowledge and data that your chatbot uses to formulate interactions and give answers.
For example, say you’re deploying a chatbot to help answer questions regarding a new medical product launch. A good place to start is using the frequently asked questions to build content for the chatbot’s “brain” from there.
Additionally, it’s important to regularly update and manage the knowledge base so it is up-to-date with the latest information.
In the life sciences industry, data security is paramount. When designing a chatbot that interacts directly with consumers, it’s important to maintain complete transparency.
Users must understand what data is collected and how the chatbot (and business) will utilize it. Users should also have a clear way to review and download their data, with the ability to erase data as needed.
For life sciences companies operating overseas to effectively reach patients of all backgrounds, translating products and service offerings is crucial. This also applies to chatbots and conversational AI technologies.
In fact, many chatbot deployments fail user acceptance because of language and cultural issues. For chatbots to be effective in global markets, they must be adapted to fit the local culture and language. This is a process known as localization.
When chatbots are not properly localized for users, deployments usually fail. Without high-quality adaption, life sciences businesses could face myriad challenges ranging from loss in sales and revenue to compliance issues.
Last, but certainly not least, don’t overcomplicate it. A common mistake for companies implementing chatbots is assuming that chatbots are an end-all-fix-all for their business needs and will solve every problem under the sun.
While chatbots are fantastic tools, they should be implemented with a clear goal in mind. When chatbots are designed this way, it is much easier to track the value they provide.
This is especially true for customer service chatbots—when the questions become too complex, it is best to let a human counterpart take it from there.
There is no doubt that chatbots, when implemented correctly, can have a meaningful impact on business models, particularly for the life sciences. However, it’s important to carefully think through the process. What sort of problems are you trying to solve with the chatbot? Additionally, think strategically about implementation.
By following the above tips, as well as researching the right approach for your business model, you can successfully implement a chatbot that enhances the user experience and increases your ROI across diverse markets.
Looking for more information on implementing multilingual chatbots for your business? Contact us to learn more!