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

Key takeaways

Marketing analytics uses data to track different marketing initiatives to more clearly understand what's effective and what's not. 

• Marketing analytics typically includes various data points, such as page views, conversion rates, clickthrough rates, engagement, and generated leads. 

• To make use of marketing data, you’ll typically use analytics models such as descriptive, predictive, or prescriptive to understand the data and use it to refine your decisions and marketing strategies. 

• You can use marketing tools like Google Analytics, HubSpot, or Sprout Social to help with various marketing analytics tasks. 

Learn more about 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. To build your skills, consider enrolling in the Meta Marketing Analytics Professional Certificate. This beginner-friendly program can help you become job-ready, with opportunities to learn more about how to collect and use marketing data, using AI as part of your process, and build skills in data analysis, data storytelling, and data-driven marketing.

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: 

• Page views and bounce rate

• Conversion rate

• Email open rates and clickthrough rate (CTR)

• Social media engagement 

• Mobile app use

• Generated leads 

How to use analytics in marketing

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. 

Read more: 5 Predictive Analytics Tools to Help You Unlock Insights from Data

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.

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 better meet and serve their needs.

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, , 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 begin to develop crucial skills to work with marketing data and produce actionable insights to help your team, or your company, improve its 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 working with AI, which are among the top skills when it comes to marketing analytics, according to North Carolina State University [1]. 

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

• GenAI

Learn how to leverage AI for competitor analysis, social media optimization, and generating innovative marketing ideas with the Microsoft Copilot for Marketing Specialization.

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.

Your go-to guide for marketing and analytics information 

Keep up with the latest trends and technologies shaping your industry by subscribing to our LinkedIn newsletter, Career Chat. Also, explore our other marketing resources for career guidance and insights into popular tools: 

• Bookmark for later: How to Use Funnel Exploration in Google Analytics

• Hear from an expert: 7 Questions with a Data Analytics Professor

• Watch on YouTube: 3 Ways AI Is Changing Marketing

You can also build your skills and foundational knowledge in marketing analytics and more with Coursera Plus, while learning and earning credentials at your own pace from over 350 leading companies and universities. With a monthly or annual subscription, you’ll gain access to over 10,000 programs.

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