What is Data Intelligence and Why Is It So Important?

What is Data Intelligence and Why Is It So Important?

Data can be a powerful predictor of future performance, and many companies are missing out on these indicators by looking at data and data intelligence as a window to the past. Yet with more real-time data analytics options and the dynamic nature of digital marketing, data provides much more than insight into the past. Data, and the marketing intelligence you derive from it, can be a compass helping you move forward in the right direction.

Strategic data intelligence: Data as a compass

Data has been touted as a kind of marketing miracle cure, holding such promise as to draw monikers like “the new oil”. These assessments are not wrong. But collecting data is not the same as extracting intelligence from it and applying it to your data-driven marketing strategies. Data, as valuable as it is, has suffered from its elevation into a buzzword-laden, fix-all abyss, with many companies expressing doubt about:

It’s a common problem: data is collected haphazardly in the hope that one indeterminate day in the future, it can be mined for insights into the past. But this isn’t representative of what data intelligence offers, and most definitely does not reflect the promise of strategic data intelligence

The keyword here is “strategic”. To leverage fully the possibilities your data provides, you first need a cohesive data strategy that defines your business goals and questions you need to be answered. Then you should identify what type, amount, and quality of data you need to achieve these aims. The data strategy, and your approach to data intelligence, will be underpinned by an important point, which we’ve made before: think carefully about the data you need and the sources you’ll get it from. If you are clear and precise in your strategy and data source selection, you gain a more complete and thorough picture of past performance, but more importantly, you gain valuable insight into the future, and the path you should take to get there. 

What is data intelligence?

Before we think about data sources and how they feed into data intelligence, it’s high time we define what we mean by “data intelligence”. Amidst the now-familiar jargon of data and business intelligence and analytics, precise definitions can easily be lost, if there’s ever been a consensus about them in the first place. Data intelligence is a good example of a term with multiple, overlapping definitions. Some pigeonhole data intelligence as the outcome of applying artificial intelligence and machine learning solutions to massive datasets for analysis. Other, broader, definitions, propose that data intelligence is simply harnessing the ability to understand and use your data in real ways.

We see “data intelligence” as a combination of these. It’s not just technology-led, and it’s not just gaining an understanding of your data. In fact, it’s a middle ground between the two. 

Data intelligence comes from the process of extracting and interpreting meaning from data, and applying that meaning into actions that can answer business questions, help make business decisions, and ultimately contribute to business value. To get the maximum value and answers to your questions, it’s important that your approach to data intelligence acknowledges and includes the key factor we highlighted above: data strategy and determining what your data needs and sources. Data intelligence comes from the right mix of the right data and the right technology delivering actionable insights.

How does business intelligence and analytics fit in?

While business intelligence (BI) is often used interchangeably with terms like data analytics, they are not quite the same, but the lines are often blurred. Historically BI has been the domain of historical information, such as reporting or product analysis, and is used for trying to improve performance going forward. But business intelligence is also a part of the data intelligence family; BI should be harnessed as a part of the whole data intelligence picture. 

Business intelligence systems or software, by extension, play a role in the “technology” part of the data intelligence equation. Once you’ve decided what data you need, you have to think about how and from where you will collect this data, how you will store it, move it from one place to another, make it accessible, visualize it, etc. Different BI systems perform some or all of these functions, which can be confusing. In addition, referring back to companies’ doubts about tapping into the value of data, data silos and lack of transparency should be a consideration when selecting business intelligence systems, as the right tools can help overcome some data intelligence challenges. What system will deliver what you need? A professional BI or data consultant will be able to guide your BI system selection as a part of constructing your overall data management and data strategy.

Why is data intelligence so important?

Why is data intelligence so important? Without data intelligence, you are at worst making stabs in the dark with your assumptions about marketing performance, customer behaviors, or campaign results. At best, you’re only skimming the surface of what’s possible with data — you might be, as we described earlier, looking at a data-informed window to your past, which is not without value but is not the depth you’re looking for from data intelligence. No, instead, data intelligence should be like a compass, or better yet, a kind of GPS that gives you real-time information about the best route to get to your defined destination.

How’s your marketing and data intelligence savvy? Take our free assessment to find out. You can start making strategic decisions today to create experiences that produce valuable customer data for your business. Learn how to with our data course!

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