Tools of a Digital Marketing Analyst
Tools of a Digital Marketing Analyst

Tools of a Digital Marketing Analyst

There is exponentially more data available than ever before. Thanks to the torrent of information on the Internet, plus the fact that it is incredibly cheap to store information, an Everest-sized mountain of data is available. A digital marketing and data analytics degree prepares digital marketing analysts to transform this data into usable information.

Every time a customer buys an item online, there’s a new data point. Every time a customer starts to buy an item online but abandons the shopping cart, there’s a new data point. Every time a user visits a web page, or leaves a web page, there’s a new data point.

Every time a user likes a seller’s social media post, or searches for a product, that’s a data point. Every time a user clicks the sponsored search result instead of the organic search result—that’s a data point too.

But this data is of no use to the marketer without some means of analyzing and organizing it into something useful. That’s where data analytics comes in.

A data analyst tells stories with numbers. Data analytics is the discipline of taking piles of raw data and analyzing it in order to understand trends, make predictions, figure out how best to use resources, and more. Data analytics is especially important for marketers, who are constantly on the lookout for new and better ways to find the right customers and present them with the products and services that they need.

There are dozens of tools for online marketers available on the Internet. You might say there’s a mountain of software applications for going after that mountain of data. How do you know which tools you need? Which ones would you be using if you pursued a degree, such as a digital marketing and data analytics degree?

Below you will find an overview of tools for online marketers.

Tools for Descriptive Analytics

Tools for Descriptive Analytics

Descriptive analytics looks backwards at data that has been collected in the past. As the name suggests, you are describing historical realities. How have customers behaved in the past? What have they bought? What have they clicked? How long have they stayed on Web page A? Web page B? Which have been more effective—email campaigns or social media campaigns?

Descriptive analytics is a set of tools for compiling a record of what has been true in a business environment. Descriptive analytics doesn’t attempt to forecast anything about the future. However, all good forecasting depends on data that is accurate and clearly understandable. [source]

If you pursue a digital marketing and data analytics degree, becoming fluent in descriptive analytics is a vital step, whatever else you intend to do in the online marketing space. As the old saying goes, “If you want to know the future, look at the past.”

Web Analytics - Masters in Digital Marketing & Data Analytics

Web Analytics

Web analytics is the detailed study of customers’ online behavior. Google Analytics is by far the most important of all web analytics tools for online marketers. Web analytics provides detailed insights about how people experience your website [source]:

  • Which pages get the most views?
  • How long do users stay on your pages?
  • What do they click?
  • What search terms brought them to your site?
  • Where and when do potential buyers abandon their shopping cart?
  • What devices are your website visitors using?
  • Which channels are effective in driving valuable traffic to your website?

If you pursue a digital marketing and data analytics degree, you will become adept at Google Analytics.

Customer Segmentation - Masters in Digital Marketing

Customer Segmentation

There are billions of buyers out there. Most of them aren’t in the market for whatever you’re selling. But some of them are. If you can find those buyers, you can sell to them. Also, you won’t waste your marketing dollars trying to sell to the billions of customers who won’t buy anyway.

That’s why a customer segmentation program is one of the most important tools for online marketers.

Customer segmentation simply means dividing customers into groups according to their past buying patterns and/or their geographic, psychographic, demographic, and technographic characteristics. People who live in Minnesota buy more snow boots than people who live in Florida. Parents of schoolchildren buy notebook paper. People who subscribe to Netflix don’t buy a lot of DVDs.

These are obvious examples that don’t require a lot of data insight. But a marketer with an online master’s in digital marketing and data analytics will use tools that provide much less obvious insights. By layering variables, these tools discover the customers who have proven most likely to buy certain products and services.

A good data analytics degree program should include instructions in SAS Enterprise Miner or a similar program. This robust data-mining application is a great tool for customer segmentation, among other data analytics tasks. Familiarity with this industry-standard program prepares college graduates for jobs anywhere in the data-analytics industry.

Market-Basket Analysis

Market-basket analysis shares a lot in common with customer segmentation, but instead of finding connections between buyers and the products they buy, it finds connections between products. To use a couple of obvious examples, diapers are often bought with baby formula, and spaghetti is often bought with spaghetti sauce.

Market-basket analysis is the basis of the “Customers who bought X also bought Y” recommendations (and other, more subtle sales pitches) on online retail sites.

You don’t need elaborate analysis to recognize that spaghetti and spaghetti sauce go together. The magic of market-basket analysis comes in finding surprising correlations.

Using market-basket analysis, Wal-Mart noticed that before a hurricane, sales of Pop-Tarts surged in affected areas. So when a hurricane is in the forecast, Wal-Mart has started shipping huge numbers of Pop-Tarts to stores in affected areas. [source]

In retrospect, it makes sense that people would stock up on Pop-Tarts before a hurricane. They have a long shelf-life, they are edible even if the power goes out, and lots of people like them. But it’s the kind of correlation one could easily miss without market-basket analysis tools for online marketers.

The SAS Enterprise Miner includes algorithms for performing market-basket analysis. Students earning an online master’s in digital marketing and data analytics use this and other tools in this vital field of data analytics.

Social Media and Voice of the Consumer Analytics

Social Media and “Voice of the Consumer” Analytics

“Listening to the customer” has always been a vital part of business and marketing. With the growth of social media, listening to the “voice of the consumer” is more important than ever. Yet the sheer volume of consumers’ voices can be overwhelming.

Brandwatch is a “social listening” platform that allows marketers to capture and analyze data from social media. More importantly, it empowers marketers to transform that data into real marketing insight.

Brandwatch is foundational to the social media and voice-of-the-consumer aspect in a data analytics degree program. If you earn an online master’s in digital marketing and data analytics, Brandwatch is one of the tools you will have hands on experience with.

Data Visualization - Masters in Data Analytics

Data Visualization

In one sense, data is just numbers. Most of us, however, find it much easier to make meaning from pictures and stories than from rows and columns of numbers. Data visualization is the process of converting data into pictures and stories that human beings can more easily comprehend.

Data visualization goes beyond pie charts and bar charts (though they are a good starting point for data visualization!). Data scientists and designers are constantly finding new, better, more dynamic ways to present data and make it comprehensible. When you work toward a data analytics degree, you will become familiar with a wide array of visualization techniques that will transform your ability both to interpret information and to communicate it.

One of the most important data visualization tools for online marketers is the SAS Studio. This “dashboard” serves as an interface for many of the data tools offered by SAS. It enables marketers to access the data they need and see and share it in ways that make sense.

Ideally, an online master’s in digital marketing and data analytics will include instruction in SAS Studio. Again, familiarity with this industry standard application gives graduates a leg up in the job market.

Exploratory Data Analysis

Exploratory Data Analysis

Exploratory data analysis is one of the most exciting aspects of descriptive analytics because it is one of the most open-ended. In customer segmentation or market-basket analysis, you know what you’re looking for, even if you’re not sure what you’ll find. [source]

In exploratory data analysis, on the other hand, you don’t even know what you’re looking for. Like a jungle explorer, you just wade into the data to see what surprises lurk there. Who knows what you’re going to find in that jungle of data?

Good data visualization and analysis methods make it possible for the perceptive digital marketing analyst to identify connections, patterns, and relationships. That’s exploratory data analysis. It’s a preliminary look at data that identifies the areas that deserve a closer look.

At the most basic level, a spreadsheet like Excel or Numbers is a key exploratory data analysis tool for online marketers. There are much more robust tools out there, including the SAS tools mentioned above. But spreadsheet skills will be an important part of your education if you pursue an online master’s in data analytics.

Tools for Predictive Analytics

Tools for Predictive Analytics

By giving a clear picture of what has been true in the past, descriptive analytics provides a basis for everything else that happens in data analytics. But prediction—forecasting—is where the real action is when it comes to marketing analysis.

In predictive analytics, the marketer takes the insights gleaned from descriptive analytics and uses them to forecast the future. Some examples of predictive analytics are:

  • Identifying whether a customer is likely to respond to a marketing solicitation
  • How likely they are to redeem a coupon
  • The likelihood of them opening an email

To get a data analytics degree is to learn how to see into the future. Forecasting the future can never be an exact science, but data analysts constantly get better and better at it. [source]

Predictive analytics:

  • enables the marketer to identify the best targets for campaigns
  • helps identify the customers who are most likely to “churn” (that is, to go away or stop buying)
  • equips the marketer’s decision on how best to use limited marketing resources

Again, for data analytics degree candidates, SAS Studio and SAS Enterprise Miner are crucial tools. These applications allow for very complex predictive modeling that give a glimpse into the future.

Optimization and Automation

Optimization and Automation

Predictive analytics leads to the optimization of business and marketing practices. Optimization is the best use of the resources that are available.

Lead-scoring tells you which potential customers to target. That means you don’t waste time and effort going after the wrong customers. Content-scoring tells you what kind of content will resonate with your customers. That means you don’t waste time and effort creating the wrong kind of content.

One very important aspect of optimization is marketing spend. The available channels for marketing seem to grow every day. There are new apps, new websites, new methods for reaching consumers. Within the “old” channels—like email—there are new methods and strategies.

How do you begin to know which of these channels and strategies to use? Predictive analytics gives the marketer a clear picture of what marketing strategies are most likely to work.

Automation “closes the loop” on the data analytics by turning insights into daily practice. Repetition is a huge part of effective online marketing: you figure out which things work, and then you do those things—a lot!

Automation takes the boring, repetitive parts of online marketing out of human hands and gives them to a computer. That means more speed, more precision, less human error.

Automation also makes it easier to keep testing one message against another, one strategy against another, to continuously improve.

Hootsuite is among the most important automation tools for online marketers. Hootsuite certification is often baked into an online master’s in data analytics.

Online Master’s in Digital Marketing and Data Analytics

Are You Ready to Pursue an Online Master’s in Digital Marketing and Data Analytics?

Emerson College is preparing students for careers in this exciting field. Upon completion of the online master’s in digital marketing and data analytics, you will be certified in some of the most important tools for online marketers. Data analytics skills will position you to succeed, whether you own your own company or work for a marketing department or agency.

Learn more about the online Digital Marketing and Data Analytics program at Emerson College.