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How to Use Marketing Data Analytics to Make Better Business Decisions

The use of data analytics in marketing is becoming more and more essential. As you run campaigns, there are always things that you can learn about your customers from the clicks they make, as well as likes, opens, and shares. 

Data is king. But true power lies in processing and analyzing the data to generate insights that ultimately lead to better decisions on future strategies.

This blog post explains what marketing data analytics is, its challenges, steps, and tools. We’ll also explore how it works and how to use it to improve your business results. Let’s get going!

What is marketing data analytics and why do you need it?

Marketing can be tough. It’s even more challenging if you’re just starting out with your new ad campaign or trying different strategies for reaching potential customers. 

Without analytics, you’re blind to the performance of your marketing efforts in terms of what works and what doesn’t, this can be inefficient and can lead to negative consequences. 

Some organizations may have impressive success without analytics. However, they’ll find it difficult to understand why their campaigns work and sometimes respond with “we were lucky.” Meanwhile, when marketing fails spectacularly, no one knows what went wrong.

Now, let’s take a look at the definition below.

Marketing and data analytics defined

Marketing data analytics is the process of analyzing marketing data to extract actionable insights. This includes identifying key marketing metrics, collecting reliable data, tracking the metrics over time, and using the results to improve future strategies. 

“Marketing analytics” sounds like just numbers, but it’s so much more than that. It’s a process that also involves people, tools, and technology to reach marketing goals.

Marketing data analytics gives you the power to understand what’s working and why. This process will help you take full advantage of what it can do.  

The importance of data analytics in marketing

Organizations use marketing data analysis in many ways. Let’s look at some common examples:

  • Product Intelligence

Analytics can help you track how customers interact with your products. This information can be used to improve the products, from pricing to features, to better align with customer needs.

  • Customer Trends and Preferences

By understanding customer trends and preferences, you can adjust your marketing mix to better appeal to your target audience. You can also use this information to segment customers and create targeted marketing campaigns.

  • Customer Support

Analytics can be used to improve customer support by identifying areas where customers are having difficulty or need assistance. This information can be used to develop training materials or improve self-service options.

  • Messaging and Media

Data analytics can help you understand which messages and media are most effective in reaching and converting customers. This information can be used to create more targeted and effective marketing campaigns.

  • Competition

You can use marketing data analytics to track your competition and also understand strengths and weaknesses. Businesses that use data analytics can gain a competitive edge over those that do not.

  • Predict Future Results

With predictive analytics, you can build a forecasting model to analyze current and past data to project future results. This type of analysis helps you understand which leads in the funnel will likely buy and when, as well as their level of interest in certain content or promotion. By understanding how your offers affect different segments—like age groups, for example—you can act accordingly and optimize your budgeting, increase revenue, and you’ll have much better chances of capturing new customers through targeted ad campaigns.

Benefits of data analytics in marketing

Data analytics is becoming increasingly important in today’s business world. Here are some reasons why:

  • Better marketing decision. Analytics help you understand your marketing campaigns in a more objective way. This way, you can make better decisions based on facts and data instead of just guessing. For an optimal process, use analytics before and after decision-making. This will help you achieve both tracking campaign success/failure as well as optimizing future plans.
  • More revenue. Marketing analytics is a powerful tool for understanding your customers and what they need from you. You can then use this information to reach out with the right message at the right time — increasing revenue streams significantly!
  • Save time and money. By analyzing data, you can identify which marketing strategies are most effective in producing results. This allows you to save time on future projects while also ensuring that money isn’t wasted on unproductive efforts.
  • Impacts in other areas. Marketing analytics has the potential to impact other areas. For example, it can significantly improve your brand recognition, content quality, channel optimization, and customer understanding.

The challenges of marketing data analytics

Creating an analytics process that measures and tracks meaningful things is sometimes complicated for most companies. The challenges to building an effective analytics process are broad in scope. Let’s take a look at some of the significant challenges below.

  • The volume and variety of marketing data

The modern marketing landscape is diverse and complex. Most channels are digital, and campaigns produce content people consume across many devices. While this sheer volume of data is good, marketers find themselves overwhelmed in a data overload situation. 

  • Lack of resources

Another common challenge is that businesses need more resources to utilize data analytics properly. Staffing up employees who are trained in analytics will take priority. In addition, marketing data analytics requires time and money, but many businesses do not have the budget or staff to dedicate to data analytics, which can limit its usefulness.

  • Lack of knowledge and skills

Many marketing organizations need more skills to use data analytics effectively. Marketing data analytics requires a specific set of skills, including statistical analysis, data visualization, and technical skills. Understanding the customers and products well is also important. These skills and knowledge are necessary to make sense of the data and glean actionable insights.

  • Difficult to identify and track meaningful analytics

This is one of the toughest challenges for marketers. The metric identification process must begin with something other than looking at whatever metrics are available or just following existing marketing processes. Instead, this process has to start with understanding the strategic objectives marketing is pursuing. There is often no easy, direct path to getting the best metrics for an analytics process. Marketers might find themselves juggling different sets of data, blending and calculating numbers to arrive at something that truly indicates how a process is performing. 

Despite these challenges, marketing data analytics is a powerful tool that can help you improve your marketing strategy. If you’re looking for help with marketing analytics, then is the perfect company to call! They offer a data analytics consulting service, data visualization, and more. 

Figure 1. Mailtrap s dashboard

Data analytics in marketing — examples

The main goal of marketing data analytics is to track the marketing channels’ performance. This should provide you with insights on the channels that bring more leads, convert better into paid customers, etc. Other successful cases of using data analytics in marketing include expanding the understanding of customers’ behavior, optimizing customer engagement and retention, building a personalized customer journey, and so on.

As a real-life example of data analytics in marketing, we’re sharing Tradezella’s case on how proper marketing communication can improve product adoption and lead to increased revenue. 

Tradezella is a trading journal designed to help traders make data-driven decisions and build healthy trading habits. At the early stage of the product, they monitored basic business metrics such as ARR, churn, retention rate, etc. However, these did not provide a full picture of product performance from a marketing perspective, in particular,  users’ activity. As a result, there was no clear understanding of which users were active and which were likely to churn. The attempts to reengage the latter were not efficient due to the lack of proper analysis of users’ activity data. All users got identical marketing content that did not get them back. data automation and analytics experts helped fix this issue by defining different stages of the funnel. It was determined when a user was recognized as churned and what desired activity level would likely keep them coming back. Marketing analysts at set up several dataflow automations for the marketing team so that they received a fresh list of users entering a particular funnel stage. This allowed them to tailor relevant marketing communication to users and different stages. As a result, this significantly increased the activation rate from 28% to around 65%. Read more about the case.

How can data analytics improve marketing strategy?

Businesses can still do marketing without a clearly shaped marketing strategy and analytics process. Startups and small businesses might have no allocation for analytics in their marketing budgets. Can they succeed without this? Unlikely, since marketing analytics adds consistency to your marketing strategy. Having no analytics process is like flying blind, like a vehicle without a dashboard. 

The proper implementation of the data analytics process helps you understand the current performance of your marketing effort and what needs to be done to produce better results. 

Another role of analytics is to constantly monitor the efficiency of your strategy and change it if necessary. This will help you maintain a steady focus on producing better results.

How to use data analytics in marketing

The marketing analytics process is a continuous cycle of measuring, analyzing, and improving. The following are the marketing analytics steps to help you work efficiently and effectively.

Step 1: Identify metrics

The first step is determining which metrics to use. This will depend on your marketing strategy. It’s no surprise that each marketing organization will have different metrics to support its process. 

There are some metrics that marketers usually use in the marketing analytics process. When you’re just starting the process, it’s best to pick only a few metrics. You will want to use more metrics as you get better at it. 

Common metrics used in marketing data analytics:

  • Website performance metrics 

Some examples are traffic, most visited pages, search ranking, unique visits, bounce rate, and conversions.

  • Digital ads metrics

Some metrics are impressions, click-throughs, conversion rate, LTV, ROI, and engagement rate.

  • Social media metrics 

The key metrics in this category may include total reach, likes, views, comments, shares, followers, and subscribers.

  • Email marketing metrics 

This can include measures such as open rate, click-through rate, and bounce rate.

Optionally, you can benefit from the following metrics:

  • Marketing team performance metrics 

These metrics measure how productive the marketing team is. The right metrics in this category are those that help the CMO and the marketing team know how well it is getting its work done. Example metrics in this category may include impressions generated, net profit, and ROI.

  • Lead generation metrics 

How are you doing with your marketing lead generation? Well, metrics in this category will tell you how effectively your campaigns and channels capture leads. Some example metrics: new leads by channel, new leads by campaign, new opportunities created, qualified leads created, conversion rates, and cost per lead.

  • Customer metrics 

Some metrics in this category include customer lifetime value (CLV), customer satisfaction, customer retention rates, Net Promoter Score (NPS), and customer churn rates.

Step 2: Collect marketing data for analytics

In this step, you will need to collect data from various sources. The type of data may vary depending on where it comes from.

Your websites are likely your primary data source. Why? Because they are the first stop for your customers to get detailed info about your product or service. 

You may also need to get data from other sources, such as your CRM and marketing automation tools. 

With the right systems in place to capture metrics, understanding your business’s current state is not difficult. For websites, you can capture and monitor their performance by enabling analytics through Google Analytics or another provider. This will also help you to optimize your web presence.

Collecting data from different sources can be a huge and time-consuming task for many businesses. And this is only the beginning since then you need to consolidate your data, compare it and perform other transformations. The most efficient approach you can go with is to automate this process with

This platform helps you seamlessly export and merge your marketing data from different sources, including Google Analytics, Mailchimp, ad apps, and others, to one destination file (Google Sheets, Excel, or BigQuery). You can also make the process automated on a recurring basis. This way, you’ll have fresh and reliable data at your fingertips!

Figure 3. is a solution to automatically export data from multiple sources

Our team of experts can help you with finding the right approach to your marketing data management, analytics, and visualization, or solve your specific case. 

Step 3: Analyze

Now you have collected the data. The next step is to analyze and visualize the metrics to gain correlation and insight. 

Dashboards are the type of visualizations you need to display metrics in summary. For more detailed info, you can use reports.

The dashboard that visualizes your marketing metrics provides a bird’s eye view into the health and performance of your marketing team. With the right charts and graphs, you can effectively communicate what is going well and the areas that need improvement.

If you are looking for an effective way to design dashboards, can help! With their team’s technical skills and creativity, they will ensure your desired dashboards are met efficiently. 

These example marketing dashboards were built by data experts at using different visualization tools. They show metrics in summary, which gives you all the important info available at a glance.

Figure 4.1 Dashboards by ad-groups-performance ad-campaigns-dashboard countries-performance-overview

Step 4: Take improvement actions

Marketing metrics are an excellent way to see what’s going on and why. What you need to do in this step is determine what actions and changes are most likely to yield improvement. No matter how thorough the analysis, it is of no value if it doesn’t lead to some sort of improvement action.

Are improvements always necessary? 

Well, absolutely! 

In theory, any process always has room for improvement. Sometimes, the improvement actions are obvious, but in some cases, it can be difficult to know what exactly needs changing.

More importantly, this step is not only to address low performance but also to replicate what works well. This way, you can continue achieving better results in future efforts.

Tools used in data analytics for marketing

Marketing analytics is a complex process. However, it can be made easier with the right tools and technology. 

The right tools can make your life easier and more efficient. Tools can help:

  • Better understand your data
  • Automate tasks
  • Segment and target your audience
  • Provide real-time and more accurate insights
  • Enhance collaboration

Now, let’s take a look at a few of the most popular (and useful) marketing analytics tools. We have broken them down into categories for you:

  • Website analytics tools
    • You can use web analytics tools to capture and track a variety of website metrics, such as total page views, unique visitors, and time on site.
    • Some popular web analytics tools: Google Analytics, Adobe Analytics, and Mixpanel.
  • Business Intelligence (BI) and data visualization tools
    • BI tools help you extract raw data from multiple data sources, transform, and load it to a destination. The destination is often in the form of a dashboard or other data visualizations.
    • Visual data representations (charts and graphs) are used to gain insights.
    • BI tools typically include data visualization tools. Some of the popular ones are Tableau, Microsoft Power BI, Looker Studio, Oracle Business Intelligence, and SAP Business Objects.
  • Cohort analysis tools
    • The goal of Cohort analysis is to see how metrics change over time. The result can be used for better customer retention and precise lifetime value estimates.
    • Tools used for Cohort analysis include BI tools mentioned above, KISSmetrics, Heap, and others.
  • Social media analytics tools
    • Tools that fall into this category can be used to track a variety of social media metrics, including engagement, reach, and impressions.
    • Some of the most popular social media analytics tools include Sprout Social and Hootsuite.
  • Marketing automation tools
    • Marketing automation software helps companies automate and measure marketing tasks and workflows. 
    • Their common features include lead management, email marketing, campaign management, and analytics. 
    • Marketing automation tool examples: HubSpot, Marketo, Pardot, AWeber, and MailChimp.
  • Search Engine Optimization (SEO) tools
    • There are a variety of SEO tools that help marketers improve their website’s ranking in search engine results pages (SERPs). 
    • Some common ones include keyword research tools and link-building tools.
    • Popular SEO tool examples: Ahrefs, SEMRush, Google Search Console, and Moz.

The list above is just the iceberg when it comes to marketing analytics tools. How can you choose the right tools? Well, you should start by first knowing what you want from the tools. Then, do some research on the potential options and compare their features, at the same time prioritizing ease of use. Lastly, review them against price points as well, and then you should be in a position to make the right decision for you.

Data analytics for better marketing decisions – final words

Marketing data analytics is vital to making informed business decisions. By understanding what marketing data analytics is and how to use it, you can make better decisions that lead to increased revenue.  

While there are challenges to collecting and analyzing marketing data, can help you overcome them with ease. They offer a data analytics consulting service that can help you get started or take your current efforts to the next level.
Check our article on 12 best marketing reporting templates to learn what else you can do to streamline your marketing analytics.

  • Fitrianingrum Seto

    Technical content writer with a strong interest in data. My background is in software engineering. I've developed software, worked with data, and been involved in SaaS product development. I love producing content that adds value to businesses and helps readers.

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