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Not All Conversational Platforms Are Created Equal; What Makes Virtual Advisors Unique

In this special guest feature, Michele Pini, SVP of Technology at iGenius – the company powering virtual advisor – crystal, examines how a virtual advisor can basically function like another co-worker. Michele first joined the company in 2014 as a back-end developer. His ultimate goal is to make the relationship between people and data as frictionless as possible. Michele is based in Italy.

Data is key for success in any business, and more data than ever is being generated every day. But how are companies leveraging that data? And more importantly, how are their employees able to make use of it?

Business intelligence tools have made a huge impact on how data drives decision making in the workplace, but the average employee often lacks the understanding of this complicated data infrastructure, and has to rely on IT and data teams to glean any insight from the raw data.

Building and maintaining this infrastructure is a huge lift on the part of data and IT teams, and is often a barrier for access to data due to the time constraints. Further, training all employees, regardless of their role, in data literacy is often not a key priority for companies. Why train every employee on a complicated data infrastructure if you can instead train a specialized team?

But employees of all skill levels need to be able to access the data essential to them to make quick decisions — whether that’s on the factory floor, in the warehouse or in the boardroom — without needing to rely on the IT team for every question. And the IT and data teams need to prioritize bigger picture tasks than pulling reports for every sales meeting.

So, what’s the solution?

Gartner is predicting that 70% of white-collar workers will interact with conversational platforms daily by 2022. But not all platforms are created equal, and companies need to evaluate what technologies will be most helpful to their employees. 

For example, what’s the difference between a chatbot and an advisor? And how do you know which will be most beneficial for employees?

Essentially, a chatbot is a part of the infrastructure — a cog in a greater machine — while an advisor is an extra layer that sits on top, and captures all of it. A chatbot can help users complete some tasks, but it’s relatively limited in its scope and isn’t connected to data directly. An advisor is completely integrated, absorbing and processing everything in real-time.

An advisor can basically function like another co-worker. By using technology like conversational AI and natural language processing (NLP), advisors have a conversational flow when employees have a question they need answered. The conversational flow generates automatically based on the user’s behavior, and data. Everything the employee sees throughout the exchange is driven by context, and they can explore business relevant data and get real-time advice as if they were asking questions of a real colleague, an experience that cannot be replicated by a chatbot.

Companies of any industry and size can benefit from employing business intelligence tools that will democratize data for all employees. When employees are empowered and better informed, they can make smarter and faster decisions from the office, the production floor, the road and even their home. Data will always be there, might as well put it to good use.

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