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Sabine Ocker, Comtech Services
January 15, 2020
Since at least the end of 2017, we have been hearing that the chatbot revolution is coming. But there have been only rumors and hints of upcoming implementations. We hear of some chatbots being implemented, but almost exclusively in the marketing content domains with limited applicability to customer support or technical product documentation. Apologies to T.S. Eliot, but the chatbot bang has not happened.
Last month at the CIDM Round Table, we asked members to talk to us about their chatbot implementations. We had an excellent turnout and an interesting discussion, but as it turns out, no member organization in the conversation has a chatbot; they all came to learn about someone else’s. As one member said, “…in DITA you have the semantic structure and the intelligence already,” so if you have metadata and the ability to scope to the right granularity of content, such as just a procedure, then your chatbot will be in a better position to deliver a precise answer. The operative part of this statement seems to be the word “if.”
I started thinking about why this is the case. Given the leg up which DITA gives organizations to provide an environment to mine their semantic-task-based-action-oriented content for answers to help their users, why aren’t we in the chatbot revolution?
There may be many reasons, but I identified at least two.
The first is because of content silos. There is no such thing as a product documentation chatbot, a marketing chatbot, or a support chatbot. There is just a corporate chatbot. So, if there is only a company chatbot, then the effort to develop it, implement it, populate it with content, and ultimately fine-tune it must be an Enterprise-wide effort. Furthermore, any chatbot must engage with users before, during, and after they have made a purchase of a product.
Similar to other enterprise endeavors such as taxonomy, creating a chatbot requires involvement, input, and ownership from key stakeholders from all content domains which represent any stage of the user journey. Of course, user journeys vary from company to company and can encompass many more stages than those listed below, but most have a variation of at least these four:
- Evaluation and selection
- Ongoing Usage
The content which users may need to answer their questions in each stage:
- Product briefs, customer reviews, or product documentation
- Product specifications, sales brochures, product catalog, product documentation
- Product Documentation, Training courses, and content
- Knowledge Base articles, product release notes, support, and troubleshooting content
This means the enterprise chatbot will need content inputs from the Marketing, Technical Product Documentation, Customer Support, Sales, and Learning and Training content domains at the very least to be effective across the entire customer journey.
A complex enterprise chatbot ecosystem of content sourced by, owned by, and updated by these different organizations is challenging to implement and maintain, especially if that ecosystem has a built-in requirement of constant tweaking and fine-tuning based on feedback on how users are engaging with […]