Cameron Weeks reports in Venture Beat:
The benefits of machine-learning chatbots multiply tenfold when that chatbot operates on an open contact center platform. There is no limit to what the chatbot can do or learn. It can traverse APIs and gain access to an infinite knowledge base stored within integrated software — if the chatbot can access it, the chatbot can learn from it.
Due to Apple’s success with a closed-platform solution, many software companies have opted to forgo an open-platform to provide a more consistent user experience, and of course, for the benefit of increased profits. But, when it comes to chatbots, a closed-platform completely defeats the purpose of a chatbot solution. Closed platforms are walled gardens that isolate the chatbot from a world of possibility.
A chatbot on a closed platform can never become the ultimate solution because it can’t be customized to address the specific problems a company faces. For example, integrating with internally developed software would likely be a lengthy process and at the discretion of the software developer. Any changes or added functionality to the platform have to be reviewed, approved, and implemented by the vendor.
On the flip side, open platforms encourage technological advancement. By giving a multitude of developers access, the potential functionality of the software is endless. An open platform provides companies the freedom to build a customized solution specific to their problems. When chatbots have access to data from various sources, the platform becomes the canvas, and the chatbot’s intelligence the brush.
Chatbots in real-world applications
The most interesting use of chatbots is found in the contact center industry. Contact center software vendors are developing machine-learning chatbots that work within their platform. The premise of these chatbots is to increase agent efficiency by handling menial customer service requests, and as a result, improve both agent and customer satisfaction.
No doubt, for a contact center, the benefits of machine-learning chatbots are numerous. Those benefits multiply tenfold when that chatbot operates on an open contact center platform. There is no limit to what the chatbot can do or learn. It can traverse APIs and gain access to an infinite knowledge base stored within integrated software — if the chatbot can access it, the chatbot can learn from it. With over 159 million interactions happening everyday, the human mind can’t even scratch the surface of making sense of data that could provide us with advantageous insight.
To “learn,” the internal chatbots create a database by observing human agents’ conversations and the data that is stored within the contact center platform across all types of media. Their knowledge base is dynamic and updated in real time as agents work. They eventually become virtual assistants, handling requests without ever involving an agent. With the help of a chatbot, agents can spend less time on boring tasks and more time on complex customer service issues.
Closed vs. open for problem solving
For example, let’s say a company is experiencing an influx of customer service messages on social media. The social media team is overwhelmed, and there is no efficient process to transfer these messages to customer support agents. With an open platform, any developer can create a unique, holistic solution to this problem.
The chatbot can be coded to crawl social platforms for brand mentions and determine which posts were customer support related. Those social posts would be transferred to a customer service queue, where they would be responded to by a support agent.
Comments unrelated to customer service would be queued up for the social media team for a response. Frequently asked questions, like “Do you have a store near my city,” would be automatically answered by the chatbot using its database of knowledge.
With an open platform, not only can solutions be tailored to specific business problems, but the customization can be developed quickly without interference from the software vendor. Free from obstacles, the relationship between chatbot and developer becomes a catalyst of innovation.
However, if we take this same example and apply it to a closed-platform solution, the process is much different. Because the contact center and chatbot platform aren’t customizable, new features can’t be added without involving the software vendor, and the chatbot can’t gather data from another platform. The inability to truly solve business problems is the main reason many contact centers find themselves using several different unconnected systems.
Endless possibilities
A chatbot within a closed platform is deprived of mindshare and innovation. It lives within a consistent environment, a neighborhood where all the houses look the same and all the roads are dead ends. It can’t explore, learn, or realize its potential. It’s just a small town bot, living in a lonely world.
A chatbot within an open platform knows no limits. It lives in an infinite city of towering skyscrapers — what’s built is at the discretion of the creator. The roads go on forever, connecting cities near and far. An open platform is a new frontier. Chatbots can explore, learn, and come back to tell us what they’ve found. There’s nothing a chatbot can’t do. It can take a train going anywhere.


















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Great insights in this post! The effectiveness of a chatbot truly depends on whether it's built on an open or closed platform — especially when it comes to real-world applications in the travel industry. I recently had an experience with the Delta Airlines Office Minneapolis , and while the in-person staff were helpful, the digital support via chatbot felt limited. It’s clear that the platform powering the bot affects how well it can access flight details, booking info, or even office-specific services. If Delta integrated a more open, responsive platform for their chatbot, it could better serve passengers trying to reach local offices like the one in Minneapolis. Thanks for sparking this important discussion!
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