Marketing Analytics: What It Is, Why It's Important and More

Written by Coursera Staff • Updated on

Marketing analytics is a crucial way to develop stronger, more data-informed marketing strategies. Learn more about the tools and skills you'll need to know to work with marketing analytics.

[Featured image] A marketer in a denim shirt reviews marketing analytics from a digital campaign on a desktop computer covered in colored sticky notes.

The vast majority of businesses use data to make more informed decisions across a wide array of functions. Marketing analytics is part of that trend. It's the use of data to track different marketing initiatives to more clearly understand what's effective and what's not.

In this article, we'll dive deeper into marketing analytics, including the marketing analytics tools you'll likely need to work with and the various data-driven skills you can begin developing or strengthening to grow as a marketer.

What is marketing analytics?

Marketers who want to understand what works and why often employ marketing analytics, which refers to the collection and analysis of marketing-specific data.

Gathering data about marketing is an excellent way to understand the return on investment (ROI) of different campaigns, initiatives, and efforts, such as publishing a new blog post or monitoring the success of a revised email campaign. The data you gather from either scenario can help you determine whether it was successful enough to repeat—or should be adjusted in some way.

Marketing analytics often starts with collecting data such as: 

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Using marketing analytics to develop marketing strategies

After collecting data, it's important to identify any patterns the set may contain and use them to make data-driven decisions and refine your marketing strategy. Oftentimes, this requires being able to understand and interpret the data you've gathered, like knowing what an optimal bounce rate or clickthrough rate is.

There are three main marketing analytics models you can use to optimize your marketing efforts: 

  • Descriptive models: Use data from prior campaigns to guide marketing decisions going forward. 

  • Predictive models: Use data from prior campaigns to predict customer behavior. 

  • Prescriptive models: Use data from all touchpoints and interactions to create better customer experiences. 

Marketing analytics examples

Here are three real-world examples of marketing analytics models in action: 

  • Descriptive: When you have limited marketing dollars in your budget, you can use marketing analytics to determine which campaigns have historically been the most successful and focus your remaining budget on top-performing efforts with a high ROI.

  • Predictive: When you want to make sure your email marketing is on-message, you can send two versions of a subject line to two subscriber groups, using the A/B testing feature in your marketing analytics software to discover the most open-worthy one. 

  • Prescriptive: If you notice you have a low bounce rate across a series of blog posts on your company's website, that might suggest the content isn't meeting users' needs. You can use marketing analytics software to examine keyword trends, top SERP, and other content marketing analytics to plan a way to revise each post to better serve your users.  

Read more: Understanding Different Types of Data 

Marketing analytics vs. market analysis

Marketing analytics is different from market analysis, which is a detailed overview of a business' target market and potential customer base to better meet and serve their needs.

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Important marketing analytics tools and skills 

Because marketing analytics relies on the use of software to compile and organize data, you’ll need to become familiar with different marketing analytics tools and how they can improve marketing efforts.

Popular marketing analytics software includes:  

  • Google Analytics: tracks and reports website traffic 

  • Hubspot: measures the performance of all marketing campaigns 

  • Sprout Social: manages, listens, and tracks social media engagement

  • SEMRush: tracks and measures content marketing efforts 

  • Brandwatch: finds trends, gathers consumer insights, and tracks marketing campaign performance 

  • Salesforce: marketing campaign performance across all channels

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Marketing analytics skills

Becoming familiar with the marketing analytics tools above will help you begin to develop crucial skills to work with marketing data and produce actionable insights to help your team—or your company—improve their impact.

You can also develop or strengthen technical skills in data analytics and SQL (a programming language used to manage relational databases), as well as workplace skills like communication and innovation, which are all top skills employers look for when it comes to marketing analytics, according to ZipRecruiter’s Career Keyword Mapper [1]. 

You may also want to hone the following skills, which can benefit your work in marketing analytics:

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4 benefits of marketing analytics 

Using data to bolster marketing decisions allows businesses to eliminate the guesswork or over-reliance on anecdotal evidence, and helps marketing teams make informed business decisions and improve customer relationship management. Here are four other benefits:  

1. Get a complete view of all marketing activities. 

Sometimes it can be hard to see the full picture across all marketing channels, such as paid digital ads, email, social media, and web. Data helps you track these components, understanding how they work independently and collectively.

2. Gain a better understanding of your customers. 

Data can provide actionable answers about your customer base, including who they are, what actions they commonly take, what their pain points tend to be, and more. Data can help you understand what improvements your team can make to improve their experience. 

3. Refine your marketing strategy. 

Data tells you what works and why, so you can refine your marketing strategy in real time, replicating certain efforts because they're performing well and eliminating those that are under-delivering.

4. Predict the success of future marketing campaigns. 

With predictive scoring based on past marketing campaigns, data can often predict how customers will respond to future campaigns and overall advertising and marketing efforts.

Learn more: B2B Marketing: Definition + Strategies

Build marketing analytics skills on Coursera

Enhance your skill set in marketing analytics by enrolling in a course or a professional certificate on Coursera.

In Meta's Marketing Analytics Professional Certificate, you'll learn how to collect, sort, evaluate, and visualize marketing data, design data experiments, and use Meta Ads Manager to optimize ad performance. Build in-demand skills and get job-ready in seven months or less.

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78,779 already enrolled

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Average time: 7 month(s)

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Skills you'll build:

Statistics for Marketing, Performance marketing, Data Analysis, Advertising Effectiveness Evaluation, Marketing Mix Optimization, Generative AI in Marketing Analytics, Marketing Plan, Linear Regression, Marketing, Marketing Mix Modeling, Python Programming, Pandas, Data Visualization, Spreadsheet, SQL, Tableau Software, Data Management, Marketing Science, Social Media Marketing, Ads Manager, Facebook Advertising, Statistical Analysis, Statistical Hypothesis Testing, Digital Marketing, Marketing Analytics, Meta advertising, A/B Testing

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Article sources

1. ZipRecruiter. “Marketing Analyst Must-Have Skills List &; Keywords for Your Resume,   https://www.ziprecruiter.com/Career/Marketing-Analyst/Resume-Keywords-and-Skills." Accessed December 20, 2023.

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