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How Q4 Desktop Answers the #1 Question in IR Before You Ask It

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I’m very excited that we’ve launched Q4 Desktop at NIRI. Q4 Desktop is a brand new application that we’ve been working on for the last 8 months. Its purpose is to deliver all of the services, data, insight and tools required to manage successful investor relations program. The product provides institutional grade data, on all US and Canadian equities and the entire universe of Factset ownership data, along with global firm, fund and over 210,000 investor contact profiles.

However, the underlying data is just the beginning of what Q4 Desktop provides. When we set out to design the product, we wanted to deliver an app that was easy to use, but that was also proactive in delivering information to our clients before they asked the question. Rather than being another information portal, which requires the user to do all of the heavy lifting, we wanted the software to have the ability to do the work for the user.

To achieve this, we used artificial intelligence (AI) methods known as machine learning and natural language processing to deliver 15mins delayed market commentary throughout the day on what is driving your stock. If you work in IR your #1 question is “what’s going on with the stock” this provides that answer right away, each time you log in.

Here is an example of an AI statement related to LinkedIn’s stock.

AI statement related to LinkedIn’s stock

 

To deliver this, we have an algorithm that is reading various data sets and our quantitative indicators is making a judgement as to what is relevant to communicate. In addition to data sets and indicators, the algorithm is evolving to incorporate all of our datasets, including events, research, estimates, etc. Moving forward, AI offers great potential to help answer questions in real time from IROs and other market participants and help drive better decision making.

Think of it as having the worlds best and fastest Analyst available to you 24/7, answering any question you may have. It’s an exciting time.


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