Analytics – Feliciano School of Business

Your Guide to Digital Marketing Analytics

mattiap — Mon, 04 Dec 2023 14:11:17 +0000

In the dynamic landscape of business today, marketing with data-driven strategies stands as a pillar of success. Brands, irrespective of their magnitude, are constantly vying to broaden their horizons and ensure their offerings reach potential customers. Digital marketing analytics plays an instrumental role in this pursuit. So, what exactly is this now indispensable component of marketing?

What is Digital Marketing Analytics?

Digital marketing analytics encompasses the gathering, measurement, and interpretation of data to understand user interactions and their engagement with digital marketing materials. Interactions with digital marketing materials might be more frequent than most realize. Customer touchpoints include emails, social media posts, online ads, website content, affiliate marketing content, etc..

The process involved in digital marketing analytics may vary by platform, but a simplified way to explain it is:

First, the customer touchpoint is set up with relevant marketing materials, and tracking mechanisms are attached to the materials/touchpoints that will be connected to a dashboard.
Whenever a customer interacts with the material or touchpoint, the tracking mechanism is triggered, and data is collected by the back-end systems and displayed on the dashboard.
The digital marketer or analyst can now view the data and interpret whether their strategies work or need further improvement. This data can also be used to measure the growth of the business’s customer base or sales.

While this may seem fairly straightforward, digital marketing analytics can get complex as different touchpoints use different tracking and data collection systems, and digital marketers/analysts have to stay on top of all the different dashboards that hold the data.

Sources of Digital Marketing Analytics Data

Some popular digital touchpoints that analytics is carried out on include:

Social Media: Platforms like Facebook, Instagram, Twitter, and LinkedIn provide a treasure trove of insights about your audience’s engagement and the potency of your content.
SEM (Search Engine Marketing): Tools such as Google Analytics are quintessential for gauging the efficacy of your display and search advertisements.
SEO: Ensuring your content dominates search engine rankings necessitates delving into keyword analysis, competitor insights, and user behavior.
Email Marketing: Metrics like open rates and click-through ratios can spell the difference between email campaigns that soar and those that plummet.
Affiliate Platforms: Knowing the origins of your online clientele and their motivation can helps magnify desired outcomes.
Consumer Purchase and Loyalty Data: Today, the spotlight is on cultivating lasting relationships with customers rather than one-off transactions. Using purchase and loyalty data to craft compelling campaigns is often a must.

This is by no means an exhaustive list – there are many other touchpoints that a business may have that a digital marketing analyst may need to measure the data of. Once the data is collected, strategies can be built, maintained, refined, or changed depending on what the information says. From shaping buyer personas to website revamps, digital marketing analytics is the compass directing the trajectory.

Embarking on a Digital Marketing Analytics Career Path

If everything we just told you has only made you excited, you may thrive as a digital marketing analyst. Mastering digital marketing analytics needs the amalgamation of the right attitudes and educational foundation. Let’s start with attitudes or traits. Below are the highly sought traits in digital marketing analysts:

Detail-orientedness: The devil, as they say, is in the details. Gleaning insights from digital marketing data often hinges on one’s meticulous nature when setting up tracking systems and digging into dashboard data.
Analytical acumen: Deciphering what the data articulates and connecting disparate dots is crucial — especially since a lot of the material has creative components, which may be difficult to connect to data unless testing has been done.
Data-centricity: While intuition has its merits, a steadfast reliance on data can help to precisely identify low-hanging fruit that can be tackled for better outcomes in campaigns.
Patience: Though it may seem counter-intuitive, in the digital realm, outcomes might not always be instantaneous. Perseverance is key.

Next, consider the right educational foundations. Though it may be possible to learn digital marketing analytics on your own (granted you have some type of marketing degree or have experience in non-analytical aspects of digital marketing), a more solid way to learn is to get a master’s degree related to marketing analytics, either online or in person.

Even better, consider delving into an ��ǰ�� to gain a more holistic understanding and to serve as an ideal precursor to specialize further in the nuances of digital marketing analytics. Alternatively, a more niche focus can be attained through an or an .

Job Prospects in Digital Marketing Analytics

The versatility of digital marketing analytics is mirrored in the diversity of career paths it offers. Some examples of potential roles include the likes of SEO Specialist, Marketing Manager, Market Research Analyst, Brand Manager, and Business Analyst.

As businesses amplify their digital endeavors, the domain is only poised to burgeon. Reflective of this trend, the Bureau of Labor Statistics indicates an optimistic outlook for professions entrenched in digital marketing analytics — examples include the median annual wage of $68,430 for Marketing Specialists and $141,000 for Marketing Managers (as of May 2022). So, if you are looking to increase your income potential, being a master of this area is certainly worth a try.

Data Analytics vs. Business Analytics

mattiap — Mon, 04 Dec 2023 14:10:08 +0000

In today’s data-centric world, the terms “data analytics” and “business analytics” are often used interchangeably, creating a cloud of confusion around their unique roles and applications. Although a great deal of overlap exists between the two fields, they also differ from one another in important ways. Read on to learn how each field is distinct and which key aspects of data analytics apply to business analytics.

What Is Business Analytics?

Business analytics uses quantitative methods and various tools to turn data into meaningful insights that enable businesses to make informed decisions. In a data-driven world, they are essential for businesses to improve efficiency, productivity, decision-making, and financial performance, and they empower professionals to influence their organizations by supporting arguments and recommendations with data-backed evidence.

There are four primary methods of business analytics: descriptive analytics, which interprets historical data to learn what happened; diagnostic analytics, which determines why it happened; predictive analytics, which forecasts what will happen based on past and/or current data; and prescriptive analytics, which recommends what to do to optimize results in specific scenarios. Depending on the method used, the field encompasses elements such as data management, data visualization, predictive modeling, data mining, forecasting, simulation, and optimization.

Data Analytics Defined

Data analytics is the multidisciplinary science of deriving actionable insights from raw data. It generally follows a process involving data collection and storage, data processing and organization, and data analysis and visualization. It employs spreadsheets, programming languages, and visualization software to identify and display useful information from datasets. Conducting accurate data analysis draws on the disciplines of statistics, mathematics, and, in many cases, computer programming.

While data analytics is a key component of business, it also applies outside the business world. For example, educational institutions apply data analytics to student performance data, attendance records, and learning outcomes. This information can be used to identify areas for improving academics, allocating resources effectively, and enhancing the learning experience.

How to Mix Business Analytics and Data Analytics

A subset of data analytics, business analytics employs key steps from that analytical process within a business context. Whereas data analytics entails the full lifecycle of data collection and storage, data processing and organization, and data analysis and visualization, business analytics tends to focus on data processing and organization and data analysis and visualization to interpret data, obtain insights, and communicate those insights to motivate business decisions.

Since data collection and storage generally fall outside the scope of business analysts’ responsibilities, they do not use the specific programming skills required for these lifecycle stages.

�鶹��ý��’s MS in Business Analytics

Delivering a strong foundation in using data to solve business problems, �鶹��ý��’s prepares students to succeed in this exciting field.

Through their coursework, students acquire deep knowledge of data analytics and methods such as statistical and predictive modeling, analyzing structured and unstructured data, and analytical reporting. They then finish the program with an applied industry-based practicum that puts their new skills to work in real-world situations.

Master’s in HR Analytics Program Launches at Feliciano School of Business

piercema — Thu, 06 Oct 2022 15:46:45 +0000

�ճ�� at �鶹��ý�� has launched a new program, with the first cohort scheduled to begin coursework in the fall 2022 semester.

The program is the first of its kind at a New Jersey college or university. The 30-credit, STEM-designated offering is designed for both current HR professionals and those looking to enter the field, and provides an intensive grounding in business analytics and its application in HR settings, alongside courses in HR Management. The capstone practicum course is also designed to deliver experiential learning via real-world projects, and pairs student teams with organizations seeking assistance with HR challenges.

Students may complete the program through either a fully online or a hybrid format, providing accessible, affordable pathways to earning a graduate degree.

“This program was created because the changing world has compelled organizations to recognize employees as their most valuable resource,” says graduate program coordinator and Assistant Professor of Management Michele Rigolizzo. “Human Resources professionals can make a profound impact on creating equitable and inspiring places to work. Any rising – or established – HR professional can benefit from our program’s balanced curriculum that teaches how to analyze data and communicate insights to all levels of an organization.”

As the industry evolves, the infusion of “people analytics” skills – the ability to collect and interpret data to improve return on investment for processes including talent acquisition, retention and compensation – are creating expertise that is increasingly essential to both organizational and career success.

�鶹��ý��’s new program has been designed to directly address this need in the marketplace, with jobs in HR Analytics set to grow significantly for the rest of the decade. With the program set to begin in late August, seats are still available in its first cohort.

“Human Resources has been fundamentally changed and supercharged by the use of data analytics to inform every aspect of the employee experience,” says Rigolizzo. “Data is the new gold – and our program provides the means to mine that data and transform it into engaging, and thereby profitable, workplaces.”

For more information about applying to the program or information about graduate programs at the Feliciano School of Business, visit .