Harnessing the Power of Data Analytics in Investor Relations

In today's world, we have access to more data than ever before. In fact, there's so much available data that the bigger challenge is often how to use the data we have and apply it to specific needs. However, tech-savvy investor-relations professionals are up to date on all the latest tools and best practices for using them — not just for gathering data but also for analyzing it.

Of course, with technology changing all the time and as artificial intelligence continues to improve, changes in data analytics are coming fast and furiously, so here's the latest on what investor relations officers (IROs) should know about using data.

How data analytics can inform IR strategies

Having the right data and analyzing it correctly can help IROs spot emerging trends, anticipate investor concerns, and tailor communications to address those trends and issues before they become huge problems. Data analytics can help IROs gain a better understanding of the company's investors, including their sentiments, behaviors, preferences and more.

Additionally, tapping data could enable IROs to automate some of their communications with investors, leaving more time for critical decision-making and strategic planning. In some cases, data analytics could even help IROs decide which institutional investors might be the most interested in their company and strategize the best ways to connect with them

Of course, before implementing data analytics into their strategies, IROs need to have a plan. Here are some essential considerations before diving in:

• Defining objectives – Before you even begin gathering data, it's important to clearly state what you intend to do with all that information. Some common objectives for IROs in data analytics include better understanding investors, predicting trends in the market, automating your communications, and informing your strategies.
• Gathering the right data – As mentioned already, a key issue with data is that there is so much of it, and a related problem is that it's become so easy to gather data that you might accidentally gather the wrong data. However, once you have clearly defined your objectives, you can then look at ways to start gathering the specific data you need.
• Appropriately analyzing the data – Next, you need to ensure that you choose the right form of analytics to ensure that your findings inform your chosen objectives. The most common forms of analytics include predictive, descriptive, prescriptive, and diagnostic. Of course, some of these analytics types will be more useful than others for the type of processing you need, and IROs will find a variety of different tools that offer one or more of these options for data analytics, including a growing number that incorporates artificial intelligence.
• Interpreting the findings and putting them into action – If you've done the first three steps correctly, you should have a useful analysis you can glean for the insights you need to do your job better and more efficiently.

With that overview, let's discuss the specifics of using data analytics for some of the most important tasks IROs do every day.

Targeting the right investors

For example, one of the most important jobs of an IRO is identifying investors who might be the best fit for their company. In the days before data analytics, IR professionals relied heavily on their relationships and networking skills at industry events, and they didn't have nearly the information available to them now.

Of course, some strategies to identify the ideal investors will never change, like corporate roadshows, in-person meetings with key institutions, conferences and other similar events. However, by applying data analytics, IR professionals can get a better feel for the investors they've spoken to and what types of companies they want to invest in. This strategy can save IROs lots of time they might otherwise spend with institutions that have no interest in their company.

For example, applying the appropriate analytics tool to an institution's most recent 13F or other public filings should reveal not only what's in the investor's portfolio but also whether they may be likely to consider investing in your company.

Identifying trends and using them

Another key piece of the IR puzzle is tracking the many trends affecting not only your company but also the market as a whole. Performing analytics on a wide variety of different data sets can help identify many different types of trends, depending on what data you're using, how you're analyzing it, and what types of queries you're using.

For example, IROs may want to identify trends in their company's financial reports or in the industry their company operates in. They might want to look for market trends that impact what stocks investors are currently favoring or even economic trends that could inform what next year's market might look like.

All of these options can play different roles in the world of IR, from looking into the past to making projections for the future. By asking the right questions from the right set of information, IROs can spot key trends, work out some strategies for benefiting from them, and even anticipate potential investor concerns so that they can address those issues before they get blown out of proportion.

Data analytics tools commonly used in IR

With technology improving all the time, more and more data analytics tools are being launched, but here are some of the most popular tools IROs might find to be useful:

• Presspage – used to analyze media reports and company-issued press releases in real time for insights on investor sentiment, audience engagement and content performance
• SQL – used to query databases
• AlphaSense – search engine powered by artificial intelligence that scans call transcripts, news and financial documents and provides sentiment analysis and market insights
• Tableau – used for visualizing data and business intelligence
• Apache Spark – for large-scale data processing
• Excel – more than just spreadsheets; used for business intelligence
• RapidMiner – for predictive analysis, data mining, text analytics, machine learning and visual analytics using any type of data source, from Access and Excel to Oracle, IBM DB2, MySQL, Sybase and more
• Qlik – to help with decision-making and problem-solving
• Google Analytics – helps IROs understand how people interact with their websites or apps
• Spotfire – useful for transforming real-time or historical data into actionable insights, predicting trends, and visualizing the results

Of course, many other tools are available, and some IR professionals find certain ones to be better than others. It may take a bit of time to determine which ones work best for your needs.

Why data analytics is essential for today's IR professionals

The concept of data analytics has been around for decades, and modern technologies have brought critical advances we never could've dreamed of back when the concept was first proposed. Data analytics is a game-changing technology that no IR professional can afford to ignore, and now with the advent of generative AI, it seems there will be no end to what we can do.

Of course, with great power comes great responsibility, and IROs would do well to work by this last bit of advice. Some potential pitfalls of data analytics include privacy issues if the data is not handled carefully, ethical usage, and interpreting the data without unfair biases.

At the end of the day, there is no substitute for the human touch, so it's critical that IR teams don't just leave everything to the AIs. Integrating human use with the latest technology is the best way to avoid these potential pitfalls while benefiting from everything data analytics has to offer.

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.