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How the Conversational AI Analytics will transform the business

Conversational AI
Conversational AI Analytics 

Chapter #1 Conversational AI

Conversational AI is a voice assistant that can engage in human-like dialogue, capture context and provide intelligent responses. Examples include Apple Siri, Amazon Alexa and Google Virtual Assistant. There are other conversational platforms with a strong focus on enterprises. According to Gartner, typical applications exist in HR, IT help desk and self-service but customer service is where chatbots are already having the higher impact, notably changing the way customer service is conducted. One of the areas where they are not included yet ,in the Gartner typical applications for the Conversational AI Platforms, is in Conversational Analytics.

Chapter #2 What is the conversational analytics

Banner of Conversational AI Analytics
Banner of Conversational AI Analytics

To understand conversational analytics, at first we need to talk about the data. Organizations produce and have a lot of data, both structured and unstructured. The volume of data is growing each second, receiving new and new updates from different sources every time. With Conversational Analytics and AI technologies, you can get a better opportunity to navigate through all this data, extract the right data sets from multiple sources and make it available via voice or type queries.

Use case — Financial report

Example conversational BI
Conversational analytics. Example - Financial report

Chapter #3 Opportunity

One of the reasons why conversational analytics will transform the business is the lack of data access and personalization. The lack of data itself is not an issue today, it is the opposite. Today the companies have a lot of data and they spend significant efforts to put in place the reports, charts and any other data visualization tool.

Here is the question — how data can bring maximum value to the business, to managers and decision makers. Data should never be a dead asset for the organization; data should be relevant, transparent, up to date, personalized and accessible. We truly believe that conversational analytics help the data be more accessible and personalized.

Use case — Sales report

Example conversational analytics
Conversational analytics. Example - Sales report

Chapter #4 What to improve?

Conversational analytics help employees talk and interact with the data. Today employees can use graphical user interfaces (GUI) to access reports, charts and any other data visualization graphic, for them to gather information that helps them to take confident decisions. When talk about the top management, in many cases, they do not have time to use GUI for getting reports, other people are preparing reports for them.

Sometimes there is no possibility to get analytics when you are not in the office. In this case, you can use the e-mail and ask someone to give the information to you. Of course, there are mobile solutions that can provide you the opportunity to access faster to the data from wherever and whenever.

We need to take into consideration that people across the organizations are working in different departments, they have their responsibilities and sometimes existing analytics does not fit their agenda or align with desired outcomes. All these aspects are generating barriers between employees and data, often it is time-consuming to search for the right data at the right time, which can lead to inaccurate conclusions.

Chapter #5 Benefits of conversational AI

Current AI technologies can understand us and understand the context of the query. What if we can train machines to understand the query and visualize the data? Just imagine the person standing behind the big screen and talking to the machine, which visualizes the data based on the person’s input. What are the benefits of this?

Time — with conversational analytics, you don't need to think about how to get the data or where to get the data. You only need to think about what you want and later type it or say it.

Accuracy — there is no human touch point in preparing data and visualizing it, machines are programmed to select needed data, aggregate and prepare the data for you. We can avoid human mistakes while making the reports.

Mobility — conversational AI interface are in your devices, this is not a stand-alone application, this is a simple chat, with this chat you can get analytics, book a business trip or create a sales order, all in one.

Use case - Marketing report

Conversational analytics. Marketing.
Conversational analytics. Example - Marketing report
With AI technologies you can talk to the data.

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