Implementation considerations
There are other implementation factors you should consider. Ideally, you will have an implementation “roadmap” that ensures the chatbot is successful.
User need identification
The chatbot should be able to identify when users are experiencing confusion or friction. This requires careful mapping of user journeys, understanding pain points, and determining key moments when the chatbot should intervene.
Users should be able to exit or ignore the chatbot without consequences. Forcing users to interact with the bot when they don’t want to can negatively impact the experience.
Here is an example of a user journey map:
Seamless integration with existing systems
If the chatbot cannot resolve the issue, it should seamlessly hand off the conversation to a human agent. This transition should feel smooth, with all relevant information passed on, so users don’t need to repeat themselves.
Clear expectations about when and how human support is available will reduce frustration.
Error handling
When the chatbot can’t provide an answer, it should acknowledge this in a friendly, non-frustrating manner and guide the user toward a next step (e.g., connecting with support or suggesting Help topics).
Performance considerations
The implementation team are likely to consider performance issues such as the response times, the availability of the system, and its scalability to more users and more content.
Pre-implementation assessment
Before proceeding with chatbot implementation, it’s crucial to conduct a thorough assessment of your readiness and requirements.
See also
Part 4: How it might affect what you write
Using Generative AI in Technical Writing
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