Business Intelligence

Tips for Using Descriptive, Predictive, and Prescriptive Analytics to Grow Your Business

Mar 27, 2022

Descriptive, predictive, and prescriptive analytics can work like magic when used to grow your small business. Learn how in this article.

Andrew ConradSr Content Writer
Tips for Using Descriptive, Predictive, and Prescriptive Analytics to Grow Your Business

Data analytics have the power to transform businesses and build empires. But not all business analytics are built the same. Some data analytics help business leaders determine what is happening with their business, some analytics help business leaders discover what moves they should make next, and some analytics even help businesses predict the future.

To make the most of data analytics, small business leaders like you should know the different data science tools that you have at your disposal, and how to use them effectively.

Maybe you’ve heard about data science and business analytics tools or even thought about using them to grow your business, but aren’t quite sure where to start. You may have loads of raw data but you’re just not sure what you can do with it. After all, you’re a business leader, not a data scientist.

In this article, we’ll look at three fundamental types of data analytics—descriptive, predictive, and prescriptive analytics—and show you how to start using them to improve your business decisions.

Let’s get into it.


Descriptive analytics: What happened?

Descriptive analytics is the most fundamental form of data analysis, which is great because it’s the easiest entry point into business intelligence and it also builds the foundation for the more advanced analytics that we’ll get into below.

For example, a data analyst working for a professional baseball team might use descriptive analytics to dig into why their team has been a losing franchise for the past several seasons. You don’t need data analytics to reveal something obvious like mounting losses (or dwindling profits for a small business).

But descriptive analytics can reveal the important details behind those losses, like a lack of runs scored compared to the league average or an error-prone defense. Or, in the case of a struggling small business, descriptive analytics can help reveal that a specific product or location is bringing your overall numbers down during a specific time of year, for example.

How to grow your business with descriptive analytics:

Pro baseball decision-makers work in a much more controlled environment than business leaders, but the analytics process starts the same way: by asking questions that you want to investigate.

Get more specific than “Why are we struggling?” or “Why are we losing money?” Think more along the lines of “Why are we losing customers in X region?” or “Why did our sales drop sharply between 2020 and 2021?” Then you can start uncovering data to illuminate those questions. You can start off with nothing more than raw data and a spreadsheet before moving onto more powerful tools. Here are some useful metrics to help you start painting a picture.

Examples of descriptive analytics metrics to track:

These metrics will also inform the models used in predictive and prescriptive analytics.

  • Month-over-month revenue

  • Average revenue per sale

  • Total customers

Descriptive analytics won’t give you a magical solution to your business problems, but it can help you hone in on a specific area to further investigate. For example, if you want to find out why your sales dropped suddenly, descriptive analytics might reveal the exact week that there was a sharp decline. Then you can look closer at the factors that might have caused it, such as a personnel change or even the weather.

Predictive analytics: What will happen?

You might think of predictive analytics as the fun and exciting phase of data analytics, but when harnessed properly, it can also be transformational for growing businesses. Predictive analytics uses tools like big data, machine learning, regression analysis, data modeling and simulation to work its magic and peek into the future.

Let’s use our baseball example from earlier. Think about the team’s data analyst who might use predictive analytics to determine that—based on regression analysis along with average age, injury history, and impending rule changes—their team is projected to have one of the worst offenses in the league over the next half decade unless drastic roster changes are made.

Or in the case of a small business leader, predictive analytics might reveal that your payroll will likely exceed revenue in the next five years if significant changes aren’t made.

How to grow your business with predictive analytics:

While you can start running basic descriptive analytics with a spreadsheet, you’ll be wasting time and resources if you attempt to perform advanced analytics (like predictive analytics) without business intelligence software. Once you have a dashboard set up in your BI system, you can start plugging in the historical data you’ve been tracking and let the software do the heavy lifting of processing all this data with artificial intelligence to produce a predictive model.

Here’s a video showing predictive analytics in action:

What is predictive analytics? (Source)

Prescriptive analytics: What should we do?

Another form of advanced analytics, prescriptive analytics may not be quite as glamorous or exciting as predictive analytics, but it’s arguably even more useful. Why? While predictive analytics may help businesses forecast what’s going to happen months and years in advance, prescriptive analytics helps them determine what to do in response to those predictions.

For example, our hypothetical pro baseball data analyst might use prescriptive analytics to address management’s goal of increasing runs scored over the next several seasons without completely blowing their budget. Prescriptive analytics might guide them to go after undervalued players who are adept at getting on base. Similarly, a small business leader could use prescriptive analytics to aid the decision to outsource recruiting and add sales staff in order to boost revenue in the coming years.

How to grow your business with prescriptive analytics:

Now that you have details on what has been happening with your business (descriptive analytics) and what might happen in the near future (predictive analytics), it’s time to use prescriptive analytics to devise a plan that will help your business reach its goals. For example, if predictive analysis revealed that your business will continue losing customers at a rate of about 20% per year, prescriptive analytics can help uncover strategies to stem that tide, like adding salespeople and customer service reps.

Here are a few examples of prescriptive analytics applications from Harvard Business School, based on descriptive metrics like website clicks, email engagement, and prior purchases:

  • Sales team lead scoring

  • Content recommendations

  • Fraud detection

  • Email marketing automation

But what about diagnostic analytics?

You may have heard about a fourth type of analytics called diagnostic analytics. While the other three types of data analytics aim to answer the question, “What?” (what happened, what will happen, what should we do?) diagnostic analytics aim to answer the question, “Why?”

So, how does diagnostic analytics fit into the bigger picture of business intelligence?

Diagnostic analytics fits somewhere between the, “What happened?” of descriptive analytics and the, “What will happen and what should we do?” of advanced analytics. In our example of a baseball data analyst, diagnostic analytics might help uncover why the team’s offense is struggling. For example, diagnostic analytics might reveal that an overly aggressive approach at the plate along with an overreliance on right-handed batters are to blame for the offensive struggles.

Or a small business leader might use diagnostic analytics to reveal that inadequate marketing for a specific new product line led to its failure and a significant dip in sales. This information can then be used for more effective prescriptive analytics.

More tips to grow your business with data analytics

As we’ve seen in this article, descriptive analytics, predictive analytics, and prescriptive analytics can each offer valuable insights for your business, but they work best when used together.

  1. Start by picking some basic descriptive metrics to track based on your business goals.

  2. Next, select a business intelligence tool to take your data analytics to the next level.

  3. Once you have some descriptive data and you’re familiar with your new business intelligence tool, you can start using it to perform advanced analytics like predictive and prescriptive models.

Ready to gain some new insight into your business using business intelligence and data analytics? GetApp has you covered. Our Business Intelligence Buyers Guide has all the information you need before starting your BI software buying journey, and our Category Leaders in Business Intelligence highlights 15 top options in BI software based on verified user reviews so that you can effectively use descriptive, predictive, and prescriptive analytics effectively to grow your small business.


GetApp’s Category Leaders in Business Intelligence (Source)

About the author

Andrew Conrad

Sr Content Writer
Hey there, I’m Andrew. I’m a Senior Content Writer at GetApp. I bring you insights about retail, eCommerce, and marketing. I studied at Loyola University Maryland and have more than a decade of professional writing experience. Home base: Austin. 2 things about me: I am a lifetime Baltimore Orioles fan, and I love walks in the woods. The tech trend I think you should keep an eye on: Mixed reality in retail. Trying on clothes will never be the same.
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