Business intelligence and data analytics are two terms that are often used interchangeably, but there is a very subtle distinction between the two. We’ve encountered some misinformation floating around on blogs and opinion pieces online, even from generally reliable sources, that can add to the confusion.
As a result, people may be confused about whether they should be searching for BI tools or data analytics tools. In this blog, we aim to set the record straight and empower you to make the best decision for your business.
Business Intelligence Vs Data Analytics: In a Nutshell
Business intelligence is the application of data analytics to help make decisions about existing strategies and create new ones. Data analytics is the process of examining data in order to draw conclusions about it. So, business intelligence is essentially data analytics applied to real-world problems.
It’s really that simple. Many companies (Symanto included) describe their data analytics tools as business intelligence tools to make it clear that they can be used for business intelligence.
How data analytics is used for business intelligence
Business intelligence is all about taking the data you have and turning it into actionable insights. Data analytics is the first step in that process – it’s what you do with the data afterwards that determines whether it’s business intelligence or not. Here are some examples of how to apply data analytics to your business strategies:
Use review data to improve customer satisfaction
Customers leave reviews online all the time, but it can be hard to keep track of them all. Data analytics tools can help you collect and process this data so you can make changes to your products or services accordingly.
For example, an SaaS businesses can use data analytics software to collect review data from g2 and Gartner, and measure sentiment by topic to discover customer pain points and opportunities for improvement. Symanto’s text analytics software uses advanced natural language processing technology to get accurate customer sentiment data. It then clearly illustrates its findings through its interactive dashboard, allowing users to navigate the data easily and make informed decisions.
Use social media data to analyse the success of your marketing campaign
Social media data is a valuable source of information for businesses. Data analytics tools can help you track and measure social media metrics so you can see how successful your marketing campaigns are. Rudimentary social listening tools will give you stats such as the number of likes and interactions your posts have received or the number of mentions of your brand on Twitter, but now there are new and exciting ways to use social media data.
For example, Symanto technology can detect cues in comments and posts online that reveal key psychographic traits and tendencies. From just short a Tweet, Symanto psychographics can predict whether the author is a loyal customer with an emotional connection to your brand or an at-risk customer who is highly likely to churn.
This technology has many potential applications, but one example is measuring campaign success. After the release of a major campaign you can turn to social media data to see what impact it has had on your most loyal customers. While engagement is a useful metric for measuring brand awareness, it doesn’t tell you anything about who you’ve reached. With Symanto psychographics, you can measure the emotional response of your most loyal customers to gauge the true success of your marketing campaign.
Use employee data to improve retention
Employee data is another valuable source of information for businesses. Data analytics tools can help you track employee engagement and performance so you can identify issues early and prevent them from becoming bigger problems.
For example, data analytics software can use machine learning to predict which employees are at risk of leaving based on subtle changes in their communication. For example, are they sending fewer emails? In those emails, are they less engaged and less emotionally connected? Are they using more negative words?
This type of data is hard to process and make sense of without the help of data analytics tools. But with the right software, you can identify employees who are at risk of leaving and proactively address the issue and prevent it from escalating.
In conclusion
There are endless ways that you can use data analytics for business intelligence. The key is to take the data that you have and use it to make better decisions about your business. Whether you’re trying to improve customer satisfaction, marketing campaigns, or employee retention, data analytics is a powerful tool that can help you achieve your goals.
Misinformation About BI and Data Analytics
Here are a couple of examples of common misunderstandings about business intelligence and data analytics that we’ve seen online:
“Business Intelligence looks at the past, Data Analytics predicts the future”
A Forbes article from 2019 is probably the main perpetrator of spreading this false distinction. The article says:
This is wrong on two counts. Firstly, there are plenty of data analytics tools that look at current and past data and are used by people for business intelligence purposes to help them make decisions. Secondly, the purpose of business intelligence is to help you predict the outcome of your strategies and make changes as necessary.
“Data analytics requires a higher level of mathematical expertise”
A blog by Stitch is much closer to the mark in describing the distinction between data analytics and business intelligence, but they seem to make the bold claim that business intelligence is focused more on business users, while data analytics is geared more towards technical users.
This may have been true in the past, but it is no longer accurate. Data analytics tools such as the Symanto Insights Platform are very user friendly, with the goal of making complex AI accessible to everyone. Our intuitive dashboards make it easy for anyone to use our data analytics software, regardless of their technical expertise.
The Difference
So, what’s the difference between business intelligence and data analytics? The short answer is: not much. The distinction between business intelligence and data analytics is not as clear as it once was. Both terms are now used interchangeably to refer to the process of using data to make better decisions about your business. Business intelligence is a term that encompasses data analytics. Data analytics is a process that forms the basis of business intelligence.
Does Symanto Offer Business Intelligence Tools or Data Analytics Tools?
Symanto AI analyses unstructured data and turns that data into easy-to-understand visualisations to help you draw insights from virtually any dataset on any topic.
Primarily our tools are used for Business Intelligence, but they are also much more versatile. For example, our technology and research has also been used for hate-speech and misinformation detection, and to predict the success of crypto projects.
In short, Symanto offers tools for data analytics which assist in gathering and processing business intelligence.
Does the distinction matter?
Well, yes and no. If you want to know whether your business would benefit from a data analytics tool or a business intelligence tool, then it helps to know that both essentially serve the same purpose, and there’s little to no distinction between the two. You’ll need to look at the specific features of each tool to decide which will be most valuable to your business.
However, with the confusion online there will be some people who believe that there’s a significant difference and will continue to use the terms in this way. Ultimately, the meaning of words and terms is dictated by how people use them over time. For now, there is no significant difference but watch this space.
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Discover more about the potential of Symanto technology for business intelligence and more. Get in touch and start making better decisions for your business in no time.
