How to Read Data Analytics

So you collected all that data, now what? How do you read data analytics? How do you make sense of the data? How do you find trends and answer questions about that data? Data analytics can help plot a course for a business to follow. Data analytics is a lot like reading tea leaves. It can be difficult to know what the data means, but there are many techniques that can help you understand it better. Data analytics is a useful technique in analyzing your company's data and using it to make business decisions. This article will break the concept down and show just how important it is for the future of your company.

How to Read Data Analytics

What is Data Analytics?

Data analytics is the process of examining data to learn new business insights.

Data can be collected through surveys, social media posts, funded studies, and it helps companies make sense of their own data and find trends.

It also helps them answer questions about their customers such as:

  • What are our most popular products?

  • What pages on our website do people visit the most?

  • How much money do we spend on marketing campaigns?

There are two main types of data used in analytics: first-party and third-party data.

First and Third-Party Data

First-party data is your own data. Data a company has on themselves and obtained from their own research and studies, but can be limited to what the company collected directly at home or within its audience.

Third-Party data is rich in behavioral and demographic information and comes from outside different sources like call centers, online surveys, or interviews with people outside of the organization

Third-party data can help fill holes you have in your first-party data as well as paint a clearer picture.

The analyses help identify trends that will drive decisions you take going forward with respect to marketing strategies or new product development ideas.

How to Read and Understand Customer Data

The first step to understanding analytics is figuring what data set you're working with.

There are two kinds of data segments: qualitative and quantitative.

Qualitative data include things like people's opinions or reactions that can't be measured numerically; while quantitative data involves numerical measurements which don't always have a one-to-one relationship like speed limits on California highways relative to other states' highways in the U.S.

Once you've categorized your analytical data into qualitative or quantitative sections, work on finding patterns within each segmentation. If there isn't enough evidence from just one category alone for an accurate interpretation, then it may help get more clarity by looking at how the data in one category relates to that of another.

If you have a lot of qualitative data segments but not much quantitative information, try looking for correlations between these two sets and see if any correlation is found with other parts of your analysis.

Reporting Tools

Data analysis software, like Microsoft Excel, can give you different options for data visualization. Business intelligence tools can create dashboards that combine the data with charts and graphs that reveal patterns, outliers, and changes over time.

Many organizations find it helpful to visualize findings in a way that makes them easy to understand and recall. These types of tools will help with a deeper dive into your data and can provide insight as it relates to a demographic.

The final step is translating your findings into something actionable. The key in this stage is knowing when you've found a pattern that can be acted on.

Analyzing data can be done across many different industries with varying levels of complexity. To avoid getting overwhelmed, use the right tools at the appropriate time.

Dashboard Analytics for Quick Review

Dashboard analytics is a great way to keep tabs on the data as it comes in. With dashboard analytics, you can monitor progress and measure success at any given time - where one's website ranks across search engine results pages (SERPs) or how well they're doing from goal perspectives for Google Analytics.

Social media analytics will help understand engagement levels on company pages like Facebook or Twitter.

There are many different analytic tools and techniques to choose from. A business may use one or a combination of these analytic methods depending on its needs.

Why You Need it

Oftentimes, businesses are trying to answer one question: where is my company going wrong? Analytics can help identify what that problem may be.

Understanding real-time data can help a company optimize its performance, lower costs and increase revenue. This data is the foundation for an analytic strategy that will have long-term benefits. The information ensures companies know where their money is going while also being able to develop more informed decisions.

With the help of analytics, companies can better market their products to consumers by finding out which ads resonate best with them and what works or doesn't. Data analysts use everything from interpreting statistics to predicting the future in order to find connections within a company's data that would otherwise go unnoticed

A lot of people think data analysis means simply interpreting statistics, but it's much more than that. It includes everything from making predictions to uncovering connections in your data to predicting the future of a company!

Seeing the Big Picture

Reading results can help a business get a broader picture of how they're doing. Analytics can provide insights on questions like:

  • What's happening with our website?

  • Who are we selling to and what kind of products/services do they buy from us?  

  • Do these customers have any similarities?

  • What are our strengths? Weaknesses?

  • How good is our customer service?

Using analytics to study customer behavior will lead you down the right path in deciding where marketing efforts should go next and what types of campaigns are most effective. With algorithms, it'll be clear as day which types of messages to churn out best reach your customer base.

You want to find out where the business is headed and how you can make it better. Analytics can helps plot a path for businesses to follow or steer them into different directions if needed.

The more real-time data you have, the better your chances for getting an accurate representation of reality. If there was no data analytic use, then these all questions will remain unanswered or answered poorly, based on assumptions rather than facts.

What is Right for your Company? 

There is no one-size-fits-all strategy for analyzing data. The right approach depends on what you're looking to accomplish. Descriptive analysis can help explain patterns, predictive analysis predicts future behavior based on past information and prescriptive analyses provides actionable advice

Descriptive Analysis

Descriptive analytics is a focus on describing what happened, not why or how. This technique doesn't answer any questions related to business decisions. Descriptive analyses can provide valuable feedback about consumer behavior for marketing purposes such as understanding buying trends from previous years.

Predictive Analysis

Predictive analysis looks into the future and predicts what a customer might want. It's an analytic tool that uses statistical formulas to determine how likely something will happen in the next few weeks or months. It looks at past behavior for clues about future actions and events, such as how likely someone will click on an ad, buy a product, or call customer service.

Prescriptive Analytics

Prescriptive Analytics is data analytics that looks at the past and predicts what the likelihood will be. It can predict concepts like which marketing campaign would work best or how long with it take to implement a new program.

An example of an organization that utilizes prescriptive analytics is Amazon. That company uses this technique when determining where they are going to deliver products within a certain time frame.

Tips on Using Data Analytics Effectively

Data analytics helps companies make sense of the data they have. It's important to find trends and answer questions about that data and plot a course for a business to follow. Here are some useful tips.

Keep your hypotheses simple and testable and break down complex problems into smaller problems with a clear set of observable implications that can be analyzed quantitatively.

Test against multiple datasets or an alternative explanation for the observed behavior by using different methods, such as qualitative research.

Monitor changes over time to see if your prediction comes true or not/create a new hypothesis based on what has been learned.

Analytics software is only as good as the person using it so make sure you have someone who knows what they're doing, has time for this type of project, and will be able to follow through with it if need be.


Data analytics is more than just a buzzword. It’s the future of your business and it will only become increasingly important as time goes on. I hope this article made the concept more approachable and gave you a good understanding of what it entails and why it matters!! If you want help implementing data analytics into your digital marketing strategy, contact us today because we’ll be glad to get started with helping you reach success.