In today’s article, we willl take a closer look at chatbots. A chatbot is simply a virtual presence in support and help desk chat environments. Instead of speaking with a human being, users are directed towards a non-human who — presumably — has access to a wide array of support information. The greatest challenge, however, is communication. How can a chatbot understand what I need to know?
The Communication Gap with Chatbots
With a bevy of sci-fi movies in mind, the ultimate chatbot would be a virtual technician with a perfect understanding of human language. He/She/It would be able to fully understand our requests and conquer all the vagaries & nuances of human speech without a moment’s delay. Of course, the answers would always be direct, appropriate, and correct.
This may happen, but perhaps not in our lifetimes. For now, we are faced with the challenges of a slowly emerging technology that is trying to bridge the gap between Big Data and the ability to effectively communicate.
The first steps by Microsoft have taken the form of the following development platforms:
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- Microsoft Bot Framework: Development environment for the building, connection, deployment, and management of bots; and
- Microsoft Cognitive Services: A collection of algorithms that breathe life into the bots, enabling them to use visual, speech, and language recognition.
The Bot Framework and Cognitive Services are the brawns and brains, respectively, of the Microsoft chatbot world. At the moment, multiple companies, such as UPS and Progressive Insurance, are using their Microsoft-powered chatbots to interact and provide support to their customers.
The Main Benefit of Chatbots sch as the Microsoft Chatbot
Behind the marketing-friendly attestations of being “innovative” and “tech-driven,” most companies are drawn to the cost benefits of bots. Chatbbots don’t require a salary or benefits… and never complain. From a cost perspective, they are the perfect employees.
The rapidity at which organizations can build and customize chatbots is also a major draw. Companies no longer need to hire teams of data scientists to make sense of their Big Data, as all of the data is stored in the cloud (typically Azure) and the provided algorithms from Microsoft do all of the legwork. Companies simply need to hire developers to build and manage the chatbots and then use the appropriate API to plug them into the desired environment, such as Slack or Microsoft Teams.
The Main Drawback is Communication
The greatest hurdle to overcome is the communication barrier. At the moment, the technology doesn’t exist for AI to comprehensively understand the human language, whether it’s spoken or entered via text.
Customers requiring support will either enter a question using natural language or select from a pre-provided list of options. In the first instance, the effectiveness of the bot depends wholly on its ability to understand your question — this is determined by the robustness of the underlying algorithms as well as the connections to Big Data sources. In the second instance, selecting from a menu, the chance for error decreases but the relevance also decreases.
The issue is that service desk questions typically involve layers of data. These are human customers that, more than likely, have questions that don’t fit neatly into a pre-formatted Q&A session. This experience often results in customer frustration, as they are continually led down multiple solution paths, none of which may be relevant to their situation.
Conclusion
IT firms are chomping at the bit to find ways to increase customer service efficiency while saving money. At present, the need for AI to be the “magic pill” that solves all problems is greater than technology’s ability to actually deliver it.
Yet, the technology has to start somewhere. We’re at the beginning stages right now and, over time, the ability of the Microsoft chatbot and others to offer engaging and helpful experiences to customers will gradually increase.
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