What Is Data Analytics? (Definition, Process, Types & More!)

Data analytics is the process of gathering, organizing, and assessing key metrics related to various parts of your business in order to find trends and gain insights into your processes and strategies.


On this page, we’ll be diving into the ins and outs of data analytics, including its:

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What is data analytics?

Data analytics is the process of gathering, organizing, and assessing key metrics related to various parts of your business in order to find trends and gain insights into your processes and strategies. The goal is to see how your business is performing and determine what you can do to improve it going forward.

Types of data analytics

You can analyze metrics related to sales, marketing, manufacturing, and more.  You can use data analytics in different ways.

There are four main types of data analytics you can conduct, each serving a different function. Here’s a brief overview of each type:

  1. Descriptive analytics
  2. Diagnostic analytics
  3. Predictive analytics
  4. Prescriptive analytics

1. Descriptive analytics

Descriptive analytics is the most basic level of analytics. It simply looks at what happened during the time you’re looking at. Did your sales go up? Did your revenue go down? Did you gain more leads than usual?

This level of analytics doesn’t involve looking to the future or trying to work out why things happen. It simply measures what happened and takes it at face value.

2. Diagnostic analytics

The second level of analytics is diagnostic analytics. This is the why of your data. It goes beyond simply seeing what happened and tries to determine the reason it happened. If your sales went up, what caused that? If you had less site traffic than usual, why?

If the data you’re looking at is from the previous month, you should figure out what you did that month that could have caused the results you’re seeing.

3. Predictive analytics

As the name suggests, predictive analytics is a type of analytics focused on figuring out what will happen in the future. The idea is that by looking at past trends, you can determine what will happen down the road.

So, let’s say you notice that in the past two years, your sales have dropped steeply in winter, only to rise again in spring. Based on that data, you might predict that the same thing will happen this year.

4. Prescriptive analytics

The fourth and final level of analytics is prescriptive analytics, which is all about using your data to plan for the future and drive the results you want.

This is where all the other types of data analytics come together. Using what you’ve learned about past trends and the probable causes of those trends, you can reoptimize your business processes to make things turn out the way you want down the road.

So, if you like the number of leads you’ve driven in the past, you can optimize your marketing to lean even harder into the cause of those leads. And if you haven’t generated many leads previously, you can reoptimize your marketing to perform better.

Data analytics techniques and applications

There are several different techniques and methods data analysts can use to gather insights and extract information, including:

  • Factor analysis: Factor analysis involves taking a larger dataset and shrinking it down to a smaller data set to more easily discover hidden trends that would be hard to spot in large amounts of data.
  • Regression analysis: Regression analysis is the process of analyzing the relationship between dependent variables to assess how a change in one may affect a change in another.
  • Time series analysis: This method of analysis involves tracking data over time, usually to track cyclical trends or to forecast future sales or revenue.
  • Cohort analysis: Cohort analysis entails breaking a data set down into groups of similar data, often by customer demographics.

Top data analytics tools

Analyzing data is no easy feat. Luckily, there are plenty of tools available that can help make this process infinitely easier for you and your team, such as:

  • MarketingCloudFX: MarketingCloudFX is our in-house revenue acceleration platform that enables you to track essential audience and marketing campaign data, so you can launch data-backed strategies that drive revenue.
  • Nutshell: If you want to collect data from your current leads and customers, Nutshell is the perfect tool for you. Nutshell allows you to track customer demographics, sales, lead sources, and much more.
  • Google Analytics: Google Analytics is one of the most popular data analytics tools. You can use it to track data from your website visitors, current customers, marketing strategies, and more.
  • Tableau: Tableau is a handy data visualization tool that creates beautiful graphs and charts from imported data to help you visualize your data and easily spot trends.

Understanding the data analytics process and steps

If you’re new to the world of analytics, you might be wondering how it works. What does analytics look like in action? How should you go about it?

Just keep reading for a four-step breakdown of the data analytics process:

  1. Choose your metrics
  2. Gather your data
  3. Organize your data
  4. Analyze your data

1. Choose your metrics

The very first thing you should do when you conduct business analytics is to figure out which metrics you want to track. That’s where your analytics data comes from — specific metrics from different areas of your business.

Which metrics you choose depends entirely upon what area of your business you’re analyzing. If you’re looking at the results driven by your email marketing, for example, you could look at metrics like:

Whereas if you’re looking at your website, you could look at metrics such as:

It all depends on what you’re trying to learn. But once you’ve chosen what you feel are the most useful metrics for you, you can move forward to the next step of the process.

2. Gather your data

The next step in the data analytics process is to gather your information. To do that, you’ll need to establish ways of tracking your chosen metrics. While you can do it manually, that would be a huge pain, so it’s better to use tools that will collect the data automatically.

You’ll want to use different tools depending on the data you’re collecting. Google Analytics is a fantastic starter tool for tracking website traffic, while SocialBakers is ideal for monitoring social media

You can also use data pipelines if you have data stored in multiple locations. But, what is a data pipeline, exactly? A data pipeline is a sequence of data processing actions that automatically moves data from one or more sources to a target destination. It can make analytics much easier by having all your information in one place.

Whatever tools you use, it will take you time to gather enough data to start analyzing. Once you have something to work with, though, you’ll be one step closer to getting your results.

3. Organize your data

After you’ve gathered a substantial amount of data, you need to do one more thing before the actual analysis can begin: You need to organize it.

Organization is so vital because it allows you to identify trends and patterns that you might not see otherwise.  Jumbled, disorganized data isn’t of any use to anyone, so you should take the time to sort it in a meaningful way.

Just like with gathering data, you can do this manually, but you probably don’t want to. It’s better to use data management platforms (DMPs) to help you. Tableau is a great example of such a platform.

Whatever you use, try to organize your data into patterns and graphs that you can assess and learn from.

4. Analyze your data

Finally, with all your metrics gathered and organized, you can begin analyzing them.

Sometimes, analytics is very simple. If all you want to know is whether your revenue went up or down last month, it’s simply a matter of comparing the numbers from the past two months, and you have your answer.

On the other hand, if you’re trying to outline a detailed plan for improving your lead generation efforts based on the leads you’ve driven in the past quarter, you might need to look deeper. If you’re struggling to uncover insights on your own, you can use an analytics tool or partner with an agency.

Whatever the case, you can use your analytics to learn about the performance of your marketing and sales. From there, you can reoptimize your business practices going forward, based on what you learned!

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The benefits of data analytics

Now that we’ve covered what data analytics is, why do you need it? How does it benefit your company? The simple answer is that without it, you’ll have a very hard time improving your business processes.

Imagine if you run a marketing campaign, but that campaign is poorly optimized and doesn’t do a good job of attracting users. Without business analytics, you’ll have no idea that it’s performing badly. You’ll simply continue to lose out on revenue.

But when you actually take advantage of your analytics data, you can find out what you need to do to improve your marketing. That means you can reoptimize and drive far more revenue down the line.

Measuring the metrics that affect your bottom line.

Are you interested in custom reporting that is specific to your unique business needs? Powered by MarketingCloudFX, WebFX creates custom reports based on the metrics that matter most to your company.

  • Leads
  • Transactions
  • Calls
  • Revenue
Learn More

How do different industries use data analytics?

Wondering how your business can use analytics to outshine competitors and drive more revenue? Learn how different industries use data analytics below:

  • Manufacturing: Manufacturing companies can use analytics to understand which products are the most popular, understand how customers discover their business, and more.
  • Healthcare: Doctor’s offices, hospitals, and practices can use analytics to understand the success of local marketing strategies to attract more patients, forecast future revenue, and more
  • Retail: Ecommerce and retail companies can use analytics to track and forecast sales, analyze the success of marketing strategies, view their most popular products, and more.
  • Financial services: Financial services companies can use analytics to better understand the customer journey, view which messages encourage leads to become customers, analyze popular services, and more.

WebFX can help you get more from your analytics data

Want some help uncovering valuable insights in your analytics data? WebFX can help! We’re the experts on marketing and sales analytics, as our more than 1020 client testimonials will attest. When you partner with us, you’ll get help learning all about your business data.

With our analytics services, we’ll assist you with each of the steps listed above and then help you put your new insights into action. We’ll also be sure to keep you informed throughout the whole process so you’re never left in the dark.

To get started with us, just call 888-601-5359 or contact us online today!