The rise of digital technology, social media and SaaS applications has fundamentally reshaped how companies perform marketing and has given businesses access to an increasingly large amount of customer data from various sources. However, it's not enough to just have this data; companies need to leverage it to understand customers’ habits and change how they measure, plan and carry out their marketing activities. Doing this requires a synergy between data analytics and digital marketing; this is where digital marketing analytics is a game-changer.

Digital marketing analytics helps companies leverage data to uncover actionable insights and improve their marketing returns. Understanding and implementing digital marketing analytics is essential for companies that want to attract and retain customers and remain innovative. 

What is digital marketing analytics?

Digital marketing analytics consists of processes and technologies that enable marketers to effectively evaluate the success and value of their digital marketing initiatives, identify trends and patterns over time and make data-driven decisions. Data analytics in digital marketing helps you know what's working, who your customers should be and what digital channels to focus your marketing resources on. 

Here's one example: Nando's, a multinational food chain with over 1,200 outlets in 30 countries, turned to data analytics to optimize its digital marketing campaigns, particularly for its customer rewards and loyalty program.

 "[Our marketers] need[ed] fast access to reports and dashboards to help them run successful campaigns and action the data and we just didn't have that flexibility," Miguel Puig Garcia, technical lead at Nando's, explains. 

By incorporating digital marketing analytics, they can integrate data across the marketing stack to create a holistic view of all marketing channels. The marketing team can then use that data to build a 360 view of the customer, activate marketing campaigns quicker and provide customers with more personalized email and social media marketing. Digital marketing analytics also helps them analyze the effectiveness of their marketing programs by cross-referencing customer purchase data from sources like Stripe with data from CRMs like Zendesk, so they can make fast decisions and tweak marketing campaigns as needed. 

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Why is digital marketing analytics useful?

Digital marketing analytics' goal is to boost the effectiveness of marketing campaigns by ensuring that the correct audiences are targeted with relevant advertisements through the most relevant channels. As a result, customers gain access to more tailored promotions, and companies get an increased return on their marketing investments with higher brand awareness and sales conversions.

In general, digital marketing analytics tools can help companies achieve three main goals:

Provide personalized user experiences: According to Google trends data, search interest for "ads settings," where users can view or adjust how their ads are personalized, increased more than 1,000 percent worldwide in the past year. Clearly, customers crave personalization, but the only way to create customized advertisements is by analyzing customer data. For example, in an ecommerce application, this can be data like a customer's purchase history, purchase channels, geo-location, favorite items and product images clicked. This customer data can then be combined with advanced statistical machine learning (ML) models to develop personalized ad offerings.

Measure campaign performance: With strong digital marketing analytics, marketers can close the gap and better understand the effectiveness of marketing campaigns based on actionable metrics, such as return on investment (ROI), revenue and cost per acquisition (CPA). Companies can see how marketing campaigns stack up against each other in revenue, click rate and other standard metrics and make better decisions to eliminate waste and maximize profits.

Find insights from marketing campaigns: Digital marketing analytics also helps identify trends in marketing campaigns. Analytics can show you where customers engage, click and buy as well as where they lose interest. For example, an ad that performs well on Facebook might not do the same on Instagram or Twitter, and several factors could cause this, such as user experience and ad placement within the app. A solid digital marketing analytics pipeline aggregates these different data points to find insights that aid data-driven decision-making when crafting marketing campaigns.

Five ways to leverage digital marketing analytics to increase marketing ROI

Here are some methods you need to consider to utilize digital marketing analytics to boost your marketing campaigns effectively.

1. Build a solid data pipeline for data consolidation and insight generation

The key to using digital marketing analytics is to quickly access customer data from multiple sources in a unified view. 

Whether it's first-party data collected from your users through your websites or other sources, such as social media, surveys and SaaS applications, invest in a reliable and scalable data pipeline provider to aggregate these data sources and utilize them to create marketing value. For example, Imperfect Foods, an online grocer, saw a 53 percent increase in customer reactivation rate and a 15 percent reduction in customer acquisition costs after consolidating all of its customer data across its data stack and using it for marketing activation.

That said, collect data responsibly. Ask for consent directly from your users to collect and use their data, and avoid any solutions that aren't compatible with people's expectations for privacy or aren’t compliant with privacy regulations.

2. Create meaningful marketing metrics for your use cases

Although it's tempting to track as many metrics and KPIs as possible, start with a few use cases and related dashboards. Then you can purposefully expand what you track and ensure the insights provide the most business value.

Define your goals and measure the results for the most valuable use cases. Then try out different data combinations to see which insights inform the best decisions. Iterating your dashboards helps you determine the right metrics and KPIs. 

It’s also important to segment your customers so that you can market to them more effectively and increase customer lifetime value. Customers can be segmented on a variety of factors, ranging from demographic to behavioral. Leverage the data you obtain from marketing campaigns to continue to iterate and improve on your customer segmentation. 

3. Track the customer journey appropriately 

Organizations can leverage digital marketing analytics to optimize marketing campaigns and metrics at each customer journey stage.

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At the product awareness stage, where you entice and educate customers about your product, the metrics here should include reach, frequency and engagement as the goal is to grow your organic audience and keep them engaged. Analytics here answers questions such as percentage increase in website, search engine and blog traffic and social media engagements and mentions. Using these data points, you can fine-tune your marketing to grow awareness. For example, you can know what type of social media posts work best for different groups and for what channel.

At the consideration/conversion stage, where buyers are more actively appraising the product choices to take action, the marketing metrics here should include sales, sign-up or other action goals, as your goal here is to convince customers to drive conversion. At this stage, marketing analytics answers questions such as average time on site, new and return visitors conversion rate, cost per conversion and bounce rate. These metrics can help optimize conversions. For example, if your site has a high bounce rate for users from a specific location, it could mean it takes too long to load, or users in that location are not getting the products they want from your site. As a result, you may need to redesign your website to deliver a better experience and improve conversions. 

At the retention stage, after a customer has been converted, analytics like click-through rate, customer churn rate, loyal customer rate and customer lifetime value can play a big role in personalizing and optimizing retention campaigns. For example, you can use data here to determine if it's the right time to kick off a customer loyalty program or offer exclusive discounts to certain high-usage customers to improve customer retention. 

4. Invest in appropriate analytics tools to gain insight faster

When building charts and dashboards, choosing the most appropriate data visualizations is essential. The right view and reports allow for accurate data interpretation and insights into action and are vital for communicating marketing's value to the business.

Choose a data analytics tool that enables you to customize your visualizations instead of relying only on default charts for displaying data.

Today, analytics technologies are ubiquitous, and with them come a plethora of visualizations—such as bar and pie charts, tables and line graphs—that can be used in reports and articles.

5. Develop models that measure and predict

Take a lesson from the Agile methodology of continuous improvement. The approach is grounded in rapid test-and-learn cycles. For example, you’re likely using more than one digital advertising marketing platform. It’s critical that you understand the performance of your ad campaigns on different channels so that you know what is working, why it’s working, and best allocate your budget. 

Try out different data combinations to see what helps you make the best decisions. Every measurement in marketing provides a new opportunity to improve, whether by optimizing campaigns to enhance the customer experience or increase revenue.

Analyzing the past, however, is not enough in marketing. In addition to reporting campaign performance, it's important to build analytical marketing models to make predictions based on customer segments.

From personal preferences and regional differences to what time of day an email should be sent or an ad served, digital marketing analytics improves a company's ability to forecast. And this is where the rubber meets the road in marketing — through a combination of analytics and prediction.

Data integration is the key to effective digital marketing analytics

"One of the biggest challenges for marketing teams is integrating data from all their global partners," Guli Zhu, head of marketing analytics at Square, says. 

Companies must invest in an automated and reliable data integration solution that consolidates data from different sources to truly unlock the power of their data to implement effective digital marketing analytics. Modern data integration tools like Fivetran can help integrate data from its library of 200+ pre-built connectors for all major marketing sources to power advanced marketing analytics. Sign up for a 14-day free trial to learn more.

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