The Key to Successful Chatbots and AI
Chatbots can be a powerful tool for improving user experiences. They are commonly used for customer support, website help, and more. However, if chatbots are not implemented correctly - with a structured content strategy - they'll produce little more than a headache for companies that use them. In this blog, learn how to successfully prepare your user experience for chatbots and AI.
Another Content Silo
Here’s the biggest concern about chatbots – they are quickly becoming another silo of content in the organization. Organizations want them for different reasons. A chatbot can help a customer or prospect get an answer to a question quickly, any time of the day. It can gather basic information for a support call before connecting in a live agent. It can also provide personalized information if it leverages AI and machine learning.
But to build the best chatbot, you need to consider its implementation as part of your wider digital experience strategy – including your content strategy and content model.
Leveraging Intelligent Content for Chatbots
Not all chatbots use AI, some basic chatbots work from a set of content that follows a decision-tree, but to deliver personalized experiences with a chatbot, you will need one that leverages AI and machine learning. In both instances, structured content is critical for the chatbot to work properly.
Chatbot Content and Your CMS
You could store your chatbot content directly in your chatbot software, but it makes more sense to manage it within your CMS, as part of your existing content. To do that, you need a CMS that provides an open API the chatbot can connect with to pull content. It also requires your CMS to support a structured content model.
Saunders talks about the process of building a content model that includes the elements required for AI and chatbots. These elements include entities, intents, and responses. When you build your content model in this way, you can leverage all the content in your CMS in a chatbot.
To build this out further, content that a chatbot may need may be located in a number of different repositories. But a chatbot cannot connect to each repository; it requires a central location with a definedcontent set to work properly. A CMS that can import or integrate content from multiple content repositories, like a component content management system used for help documentation, or a series of Word documents used for training, can build out the content model for that additional content and use it to support chatbots.
The Bottom Line: Chatbots Need the Right Content and Content Structure
You could copy and paste the content you want for your chatbot into the chatbot application. But consider the nightmare of keeping it up to date and synchronized with similar content on other digital properties. Sounds painful.
By defining a complete structuredcontent model, used across the organization, that incorporates the elements a chatbot requires, you make it easier to feed the best content to your chatbot, and in turn, to your customers and website visitors.
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