From engagement statistics to content analytics to conversion metrics, data is a big part of most social media managers’ responsibilities. But that doesn’t necessarily mean you enjoy processing marketing data or drawing conclusions from it.

If data isn’t exactly your favorite part of the job, these marketing analytics case studies may change your mind.

Find out how marketing analytics helped three major brands grow their businesses—and you might develop a whole new appreciation for marketing data in the process.

What Is Marketing Analytics?

Marketing analytics is the process of collecting and evaluating metrics to understand how much value marketing efforts generate. With analytics, you can assess the return on investment (ROI) of anything from social media posts and ad campaigns to landing pages and native platform features.

For many organizations and their marketing team, marketing analytics are essential for improving offerings and driving growth.

Here are common goals you can achieve with marketing analytics.

Improving marketing campaigns

Some social media marketing campaigns are more successful than others. Analytics can help your organization pinpoint exactly what works. By analyzing metrics like engagement, click-through rate (CTR), conversions, and ROI, you can determine what resonates best with its audience. By using data science, you can craft a marketing strategy that gets you better results from your campaigns.

Decreasing expenses

Ineffective marketing campaigns, usability issues, and poorly optimized algorithms can all lead to dissatisfied customers and unnecessarily high retention costs.

By investing in marketing analytics, your organization can take steps to identify points of friction and reduce expenses.

Forecasting results

Reviewing past outcomes is useful, but forecasting the results your campaigns are likely to generate is even more valuable. With marketing analytics, you can model results and get a better sense of how marketing initiatives can impact growth over time.

Marketing Analytics Case Studies: Progressive Insurance

In the early 2000s, Progressive’s website was routinely considered one of the best in the insurance industry. When the insurance provider’s customers began switching to mobile devices a decade later, the organization aimed to develop a mobile app as effective as its desktop site.

But what did that mean exactly? And what was the insurance provider’s mobile app missing?

To determine what would make the mobile app more successful, Progressive pursued an in-depth analysis of the organization’s marketing data.


As Progressive Data & Analytics Business Leader Pawan Divakarla explains, the insurance provider’s analytics team has always sought insight into how customers are using the company’s tools.

In his words, “At Progressive, we sell insurance. But if you think about it, our product is actually data.”

After launching the mobile app, Progressive began looking for ways to optimize the user experience. As this Progressive case study explains, the organization aimed to streamline the login process and improve user satisfaction to meet its ultimate goals of increasing customer loyalty and new customer acquisition.


Because Progressive’s mobile app generated so much information, the organization needed data visualization tools for collection and processing. To analyze customers’ experiences and actions, the company opted to use a combination of Google Analytics 360 and Google Tag Manager 360.

This choice was a relatively simple one for Progressive because the company already used these tools to run A/B tests and optimize its website.

Using Google’s analytical tools to review the company’s mobile app would allow Progressive to understand what features to test and how to optimize the user experience across countless mobile devices and operating systems.

Progressive used the two Google tools for separate yet complementary functions:

  • With Google Analytics 360, Progressive could track user sessions and demographics. The company integrated BigQuery for more insight into user behaviors.
  • With Google Tag Manager 360, Progressive could easily implement tracking tags to measure various actions, conversions, and navigation patterns.

To get the insights the company needed to improve its mobile app, Progressive took a three-pronged approach:

User device data

First, Progressive aimed to identify which devices and operating systems were most common among the app’s user base. With this information, the company would be able to develop more effective tests for its mobile app.

App crash data

Next, Progressive wanted to analyze app crash data. The company planned to use Google Analytics 360 and BigQuery data to understand the cause for the crash and how users reacted when the app stopped working abruptly.

Login and security data

Finally, Progressive aimed to learn how users responded when failed login attempts locked them out of the app. The company planned to use Google Analytics 360 and BigQuery to see what actions users took. It planned to then test new prompts that would guide users more effectively.

Outcome of this marketing analytics case study

Using marketing analytics tools, Progressive was able to process customer behavior, identify appropriate tests, and implement successful solutions.

Here’s how each of the three approaches generated useful results that helped Progressive reach its ultimate acquisition and loyalty goals.

User device data

First, Progressive developed session-based reports that reflected the most common mobile devices and operating systems for the app’s user base. With those insights, the company identified which device and operating system combinations to prioritize for its mobile app tests.

As a result, the company reduced testing time by 20% for its mobile app—allowing the organization to find solutions much more quickly than its typical timeline would have allowed.

App crash data

Next, Progressive reviewed the actions customers took right before the app crashed. The company pinpointed a server issue as the cause of a major crash that disrupted countless mobile app sessions.

Using this data, Progressive could address the server issue and prevent it from happening again.

Login and security data

Finally, Progressive created a custom funnel in Google Analytics 360 to evaluate users’ typical login path. After learning that many users who became locked out of their accounts never attempted to log in again, the company developed a workflow that provided better guidance.

The new workflow sends users to a Forgot Password page, which has increased logins by 30%.

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Marketing Analytics Case Studies: Netflix

When companies take a digital-first approach to customer loyalty, they can collect an incredible amount of user data. With these marketing analytics, companies can improve their products, build better marketing campaigns, and drive more revenue.

As this Netflix case study shows, the online content streaming platform has leveraged its user data in a variety of helpful ways.

By using data to improve its content recommendation engine, develop original content, and increase its customer retention rate, Netflix has positioned itself far ahead of the competition.


With so much data to leverage, Netflix had wide-ranging goals for the company’s marketing analytics. However, all of the organization’s goals contributed to the company’s larger business objectives—which focus on customer retention.

Netflix aimed to go beyond basic user demographics and understand what customers want from a streaming platform—and what was likely to convince them to stay. With this knowledge, Netflix could create better products and services for happier customers.

Access issues, service outages, and platform flaws can all lead to unhappy customers and negative sentiment—which can cause customers to seek out an alternative solution.

By identifying problems early through marketing analytics, Netflix could improve its products and continue to innovate.


To work toward its customer retention objective, Netflix collected data from virtually every interaction with its 150+ million subscribers. The company then used marketing analytics tools to process this native data and evaluate everything from how customers navigate the platform to what they watch.

By creating such detailed customer profiles, Netflix could make much more personalized recommendations for each user. The more data the company collected, the more it could tailor its algorithm to suggest the ideal content to each individual viewer.

To better understand the platform’s users, Netflix collected such data as:

  • The devices viewers used to stream content
  • Day of week and time of day when users viewed content
  • Number of serial episodes viewers watched in a row
  • Whether viewers paused and resumed content
  • Number and type of searches users performed

Netflix also welcomed user feedback on content. The company incorporated these content ratings into their analysis to better understand viewer preferences.

Outcome of this marketing analytics case study

According to the streaming platform, the Netflix algorithm is responsible for about 80% of viewer activity. The company has successfully collected relevant data and used marketing analytics to generate recommendations that encourage viewers to continue watching and subscribing.

The revenue metrics suggest that Netflix’s focus on marketing analytics has been hugely beneficial to the company. The company estimates that its algorithm generates $1 billion in value every year, largely due to customer retention.

In recent years, Netflix’s customer retention rate has far surpassed competitors like Hulu and Amazon Prime. Netflix has an impressive 90% retention rate, meaning the vast majority of viewers continue to subscribe to the service month after month. (In contrast, Amazon Prime’s retention rate is 75%, and Hulu’s is 64%.)

For Netflix, customer retention means more than happy viewers. It also means more data, a continually improving algorithm, and substantial business growth.

Netflix has emerged as the world’s most highly valued company, with a total valuation of over $160 billion. Netflix can continue to increase this valuation. It leverages its data by producing original media and recommending the ideal content to viewers every time they access the streaming platform.

Marketing Analytics Case Studies: Allrecipes

As the world’s biggest digital food brand, Allrecipes has 18 websites and more than 85 million users. But the brand also has plenty of competition from other food-focused apps and websites.

To stay ahead of other recipe sites and ensure that it continues to provide all the solutions that users want, Allrecipes relies on marketing analytics.

With marketing analytics, the digital brand can better understand the customer journey and analyze trends as they emerge. As this Allrecipes case study explains, the brand can expand its audience and attract even more lucrative demographics using these insights.


To continue to gain ground as the world’s top digital food brand, Allrecipes established several wide-ranging goals.

Some of the brand’s primary objectives included the following.

Improve user experience

With more than a billion and a half visitors across the brand’s sites every year, Allrecipes generates a ton of traffic. But the company needed a way to understand how visitors were using the site, so it could improve the user experience and gauge the health of the sites.

Increase video engagement

To take advantage of a demand for video content, Allrecipes had decided to invest heavily in video. However, the video production team needed strategic guidance. The brand needed to know what types of content would drive the most engagement.

Drive mobile engagement

To continue to meet the needs of its user base, Allrecipes had to look beyond its websites. As more and more people began using mobile devices to access the brand’s content, Allrecipes realized that the company needed to optimize its mobile app.

Inform product strategy

To promote new features and integrations or pursue partner programs, Allrecipes needed to know what its community wanted. Had they adopted the new integrations yet? Did they need new features to use the site or app more effectively?

Expand user base

Cooking and dining trends come and go, and Allrecipes needed a simple yet effective way to identify these developments.

By responding quickly to trends, the brand would be able to capture a larger user base, including elusive millennials.

Grow advertising revenue

Like many digital brands, Allrecipes has a native advertising program that allows the company to monetize its website. The company aimed to increase its advertising revenue, yet the organization didn’t want to compromise the user experience. To find the right partners to grow this program, Allrecipes needed deeper insights into its audience.


Although the brand’s goals were varied, the approach was relatively straightforward. To process marketing analytics from a wide range of channels, the brand opted to use Tableau, a business intelligence platform.

With Tableau, Allrecipes could establish a single platform for visualizing data from Adobe Marketing Cloud, Hitwise, and comScore. By linking Adobe Marketing Cloud to Tableau, the brand could pull in all of its website and marketing analytics. By linking Hitwise and comScore, the brand could source demographic data.

Using Tableau allowed Allrecipes to build custom dashboards and develop tailored reports to answer all of the brand’s questions. This tool also allowed the brand to pursue collaboration options across the organization.

In fact, departments ranging from marketing and design to product and finance contributed to the tool. Teams used Tableau Server to publish dashboards, creating a single space where stakeholders could visualize or analyze data.


With Tableau, Allrecipes was able to visualize the brand’s data successfully, enabling smarter decisions and making progress toward key goals. Here’s what the brand accomplished using marketing analytics:

Improve user experience

Using insights from Tableau, Allrecipes was able to see how visitors typically used the site—including how they submit recipes, share content, and post links on social media channels. The organization then used this data to devise a plan for improving the site.

Knowing how visitors were already engaging with the site allowed the brand to make data-driven, goal-focused decisions.

Increase video engagement

With Tableau’s marketing analytics, Allrecipes found that out of all types of recipes, dessert typically generated more views and attracted more comments and photos. As a result, the brand opted to focus on this highly engaging niche, creating a separate video hub for dessert recipes.

Drive mobile engagement

To increase engagement on mobile devices, Allrecipes devised an A/B test that displayed the brand’s mobile site on all devices. Then the organization used the analytics to identify what drove interactions on mobile. The brand then used insights to improve the mobile site, including optimizing content and encouraging photo uploads.

Inform product strategy

Tableau’s data visualizations helped Allrecipes understand trends in its user community and respond to preferences more efficiently. Using these insights, the brand was able to promote integrations and features while gathering data for future product enhancements.

Expand user base

By using Tableau’s insights to process trends, Allrecipes was able to segment audiences for various recipe types, ultimately identifying millennial users’ interests and preferences. The brand was then able to create more content geared toward this growing user base—likely responding much more quickly than competitors could.

Grow advertising revenue

By tapping into real-time marketing analytics, Allrecipes was able to share popular recipe searches and trending content with its advertising partners during a recent holiday season. Advertisers could then create ads tailored to these interests, generating a better ROI and creating a more appealing experience for users.

What We Learned From These Marketing Analytics Case Studies

As these marketing analytics case studies show, data can tell you a lot about what your customers want—and where your organization succeeds or has room for improvement. Using insights from marketing analytics, a digital marketer can make data-driven decisions to cultivate customer loyalty, generate more revenue, and ultimately grow your business.

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