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

Written by Coursera Staff • Updated on

Marketing analytics is crucial to developing 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 female small business owner sits at her desk with her laptop and looks at her marketing analytics.

Most businesses use data to make more informed decisions across various functions. Marketing analytics is part of that trend. It's using data to track different marketing initiatives to more clearly understand what's effective.

In the UK, the value of the research insights and analytics industry is around £9 billion and growing [1]. Analysts at the Market Research Society (MRS) expect the industry to continue expanding, eventually employing more than 70,000 people [1]. Read on to explore the field of marketing analytics, including the marketing analytics tools you'll 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 collecting and analysing 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 somehow.

Marketing analytics often starts with collecting data such as: 

  • Page views and bounce rate

  • Conversion rate

  • Email open rates and clickthrough rate (CTR)

  • Social media engagement 

  • Mobile app use

  • Generated leads 

Using marketing analytics to develop marketing strategies

After collecting data, it's important to identify patterns, use them to make data-driven decisions and refine your marketing strategy. Often, this requires understanding and interpreting the data you've gathered, like knowing what an optimal bounce rate or clickthrough rate is.

You can use three main marketing analytics models to optimise 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 behaviour. 

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

Marketing analytics examples

Consider the following real-world examples of marketing analytics models in action: 

  • Descriptive: When you have limited marketing pounds 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 how to revise each post to serve your users better. 

Marketing analytics vs. market analysis

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

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Important marketing analytics tools and skills 

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

Popular marketing analytics software includes:  

  • 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

Marketing analytics skills

Becoming familiar with the marketing analytics tools above will help you develop crucial skills for working with marketing data and producing actionable insights to help your team—or your company—improve its impact.

You can also develop or strengthen technical skills in data analytics and workplace skills like teamwork and attention to detail. 

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

  • Building dashboards using marketing analytics software to track and display data

  • Sales forecasting

  • Branding 

  • Conducting marketing research

  • Project management  

  • Cleaning data 

  • A/B testing

4 benefits of marketing analytics 

Using data to bolster marketing decisions allows businesses to eliminate the guesswork or over-reliance on anecdotal evidence. It 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 the web. Data helps you track these components and understand 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 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.

Build marketing analytics on Coursera.

Marketing analytics involves collecting and analysing data from marketing efforts to measure their effectiveness and improve customer relationships. To enhance your skill set in marketing analytics, enroll in a course or a professional certificate on Coursera.

In Meta's Marketing Analytics Professional Certificate, you'll learn to collect, sort, evaluate, and visualise marketing data, design data experiments, and use Meta Ads Manager to optimise ad performance. Build in-demand skills and earn a credential you can feature on your CV.

Through Google's Digital Marketing & E-commerce Professional Certificate, you'll explore how to measure marketing performance through analytics, use digital marketing channels to attract and engage customers, and build e-commerce stores.

Article sources

  1. Market Research Society. "Industry size and growth rates, https://www.mrs.org.uk/resources/industry-size/". Accessed May 13, 2024. 

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