A Beginner’s Guide to Data Sources of Digital Marketing Analytics

Digital marketing analytics is an essential aspect of any marketing strategy in the digital age. It involves collecting, measuring, analyzing, and interpreting data from various digital marketing channels to understand market trends, customer behaviour, and the performance of marketing efforts.

Navigating the world of digital marketing analytics can be daunting for beginners, but understanding the basics is crucial for leveraging the power of data in marketing decisions.

Understanding Digital Marketing Analytics

At its core, digital marketing analytics is about turning data into actionable insights.

First, digital data insights enable marketers to assess the business opportunities and risks in the business environment. Second, it is a process that allows marketers to evaluate the effectiveness of their campaigns, understand customer preferences, and optimize their strategies for better results. By analysing data from different sources, marketers can gain a comprehensive view of their marketing performance across various channels, including social media, email, search engines, and more.

The Importance of Data Sources in Digital Marketing Analytics

Data sources are the foundation of digital marketing analytics. They provide the raw material that, when properly analysed, can offer invaluable insights into customer behaviour and campaign performance. Identifying and accessing the right data sources is critical for any marketer looking to make informed decisions based on analytics.

Among various data sources, Clicademy offers the most unique access to its internal traffic data for the registered members. This is especially beneficial for analytists and data readers who do not have their own websites.

How to Find Data Sources for Digital Marketing Analytics

To get started with digital marketing analytics, here’s a list of common data sources and how to find them:

  1. Website Analytics Tools: Platforms like Google Analytics are fundamental for tracking website traffic, user behaviour, and conversion rates. They offer a wealth of information about how visitors interact with your site.
  2. Social Media Analytics: Social media platforms such as Facebook, X, and TikTok provide built-in analytics tools that allow you to measure engagement, reach, and the effectiveness of your content.
  3. Customer Relationship Management (CRM) Systems: CRMs are valuable for tracking customer interactions, sales data, and other customer-related metrics that are vital for personalized marketing. Examples of such platforms include Salesforce, HubSpot, Zoho Analytics, etc.
  4. Email Marketing Platforms: Services like Mailchimp offer analytics on email campaigns, including open rates, click-through rates, and conversions.
  5. Pay-Per-Click (PPC) Platforms: Google Ads and other PPC platforms provided by Facebook, Microsoft Ads, YouTube, LinkedIn, Amazon, Etsy, Yelp, etc. provide detailed data on ad performance, including impressions, clicks, and conversions.
  6. Search Engine Optimization (SEO) Tools: Tools like Google Search Console and third-party platforms like Semrush or Ahrefs help track your search engine rankings and organic traffic.
  7. Market Research Tools: Platforms like Mintel and Statista can help you understand market trends and consumer behaviour.
  8. Competitive Intelligence Tools: Tools like Simiarweb give insights into your competitors’ online strategies and performance.
  9. Audience Research Tools: Platforms like One2Target, part of SEMrush, help you gather data on your target audience’s preferences and behaviours.
  10. Third-Party Data Providers: Companies that specialize in data collection can provide additional insights that may not be available through other sources.

By utilizing these data sources, marketers can collect a vast array of data points that, when analyzed, can reveal patterns, trends, and insights that inform strategic decisions.

It’s important to note that while collecting data is crucial, the real value lies in the analysis and interpretation of that data to drive marketing success. Your Clicademist has more about those topics.


Use Digital Analytics Data to Address User Pain Points

To be fair, customers can be a pain. They are hard to please, and according to the 20/80 rule, only a minority of them will sustain your business. However, marketers should step into online customers’ shoes and consider using digital analytics data to ease user pain points.

Digital analytics serves as a beacon, guiding businesses through the murky waters of user experience issues. With digital analytics, we can illuminate the pain points that users encounter, and more importantly, devise strategies to alleviate them.

Your Clicademist navigated the mud puddle and found a few of these, together with what analytics can help.

User Abandonment: The Sign-Up/Checkout Conundrum

One of the most critical challenges online platforms face is user abandonment during sign-up or checkout processes.

The problem solvers are:

  • Funnel analysis can reveal at which stages potential customers are dropping off, allowing businesses to streamline these processes.
  • Session recordings offer a window into user interactions, highlighting areas where users face confusion or frustration.
  • Examining exit pages can pinpoint the last touchpoints before users leave, providing valuable insights for retention strategies.

The Need for Speed: Addressing Slow Loading Times

In a world where speed is essential. Slow loading times can be a death knell for user retention.

  • Page load time metrics are crucial in identifying pages that lag behind, while geographic insights can uncover location-based discrepancies in loading times.
  • Device-specific data further refine our understanding, ensuring no user is left behind due to technical delays.

Content Relevance: Curating a Personalised Experience

The relevance of content is a cornerstone of user engagement.

  • Content engagement metrics can assess the effectiveness of the material presented to users.
  • Search queries provide a direct line to user intent, revealing what users seek.
  • Segmentation allows for the personalisation of content, catering to the unique preferences and behaviours of different user groups.

Mobile Usability: Smoothing Out the Rough Edges

As mobile traffic continues to grow, addressing mobile usability issues has become imperative.

  • Analyzing mobile traffic share and conversion rates sheds light on the mobile user experience compared to the desktop.
  • Heatmaps offer a visual representation of user interaction on mobile devices, identifying areas that require optimization.

Navigating the Maze: Error Messages and Broken Links

Nothing sours the user experience quite like encountering error messages or broken links.

  • Error tracking is essential in monitoring the frequency and types of errors users face.
  • The behaviour flow can illustrate the user journey, pinpointing where errors throw a wrench in the works. Understanding the impact of these errors on the conversion funnel is critical in maintaining a smooth user journey.

Beyond the Numbers of Digital Analytics Data for User Pain Points

Digital analytics transcends mere number-crunching. The goal is not just to solve problems, but to create an environment where users thrive, engage, and convert. It is about empathising with the user and enhancing their journey.

By leveraging the wealth of data at our disposal, we can transform pain points into touchpoints of improvement. It’s a continuous process of learning, adapting, and optimizing to ensure that the digital experience is not just satisfactory, but delightful.

Let go the pain points. Let’s make the digital world a better place for every user.


Digital Analytics for Audience Insights in 10 Steps

Digital analytics has become an increasingly approachable tool for marketers. With the vast amount of data available, digital analytics offers a treasure trove of audience insights that can significantly enhance marketing strategies. Using the tools should also be a professional habit that you do on a daily basis.

Habits have patterns. Here’s a detailed exploration of leveraging digital analytics to gain a profound understanding of your audience in 10 steps.

1. Defining Target Audience

The first step in audience analysis is to clearly define who your target audience is. This involves creating detailed buyer personas that represent your ideal customer. Marketers can identify key characteristics such as demographics, interests, and behaviours by analysing data from your digital channels.

2. Analysing Customer Behaviour

Digital analytics tools allow you to track how users interact with your content across various platforms. This includes website visits, social media engagement, and email activity meatrics. Understanding these interactions can help you tailor your content to match your audience’s preferences.

3. Utilising Segmentation

Segmentation is a powerful technique that divides your audience into groups based on shared characteristics. This enables you to create targeted marketing campaigns that resonate with specific segments, increasing the relevance and effectiveness of your communications.

4. Measuring Engagement

Engagement metrics such as click-through rates, time spent on pages, and social media interactions are vital indicators of how compelling your content is. High engagement rates often correlate with a deeper interest in your brand and a higher likelihood of conversion.

5. Leveraging Surveys and Feedback

Surveys and direct feedback are invaluable for understanding the needs and opinions of your audience. They provide qualitative data that can complement the quantitative data from analytics, giving you a more complete picture of your audience’s preferences.

6. Tracking Conversion Rates

“Conversion. Conversion. Conversion”. The conversion rates are the ultimate measure of marketing effectiveness. By analysing which channels and content types drive the most conversions, you can optimise your marketing efforts to focus on the most productive areas.

7. Understanding Motivations and Pain Points

Beyond behaviour, it’s crucial to understand your audience’s motivations and pain points. This insight can inform content creation, product development, and overall marketing strategy, ensuring that you address the real needs of your customers.

8. Predictive Analytics

With AI and machine learning advancements, predictive analytics can forecast future behaviours and preferences based on historical data. This forward-looking approach can help you stay ahead of trends and anticipate the needs of your audience.

9. Creating Actionable Reports

The data you collect is only as valuable as the insights you extract from it. Creating clear, actionable reports helps communicate findings to stakeholders and informs strategic decisions.

10. Continuous Adapting Digital Analytics for Audience Insights

Understanding your audience is an ongoing process. The digital landscape is ever-changing, and so are the behaviours and preferences of your audience. Continuous learning and adaptation are necessary to align your marketing strategies with your audience’s evolving needs.

By embracing the power of digital analytics for audience insights, you can transform data into actionable insights that drive your marketing strategies forward.

Analytics Web & SEM

Mastering PPC Analytics Without Running a Campaign: A Comprehensive Guide

Pay-per-click (PPC) is an essential building block of Search Engine Marketing on the Internet.

Pay-per-click (PPC) advertising is a crucial aspect of digital marketing that allows businesses to target potential customers through paid ads. However, for those new to the field with a tight budget yet looking to enhance their skills, the question arises: How can one learn PPC analytics without firstly investing in a campaign to work on? This comprehensive guide provides insights and resources to help you gain proficiency in PPC analytics, even without direct campaign management experience.

Understanding the Basics of PPC

Before diving into analytics, it’s essential to grasp the fundamentals of PPC. PPC is a model of Internet marketing in which advertisers pay a fee each time one of their ads is clicked. Essentially, it’s a way of buying visits to your site rather than attempting to earn those visits organically. Understanding the terminology, the structure of campaigns, ad groups, and the importance of keywords is foundational knowledge for PPC analytics.

Online Courses and Certifications

Numerous online courses and certifications are available that can provide structured learning paths for PPC analytics. For instance, the Google Ads Certification is a free program that offers comprehensive training on Google’s advertising platform. Similarly, platforms like Semrush offer PPC Fundamentals Courses, which cover the basics and gradually move to more advanced topics. These courses often include hands-on exercises that simulate campaign management, allowing learners to apply analytical concepts without running a live campaign.

Simulation Tools and Software

Some platforms offer simulation tools that mimic the experience of running a PPC campaign. These simulators allow you to practice setting up campaigns, choosing keywords, writing ad copy, and analyzing hypothetical campaign data. This hands-on approach can be invaluable for understanding the impact of different strategies on campaign performance.

Case Studies and Industry Reports

Analyzing case studies and industry reports can provide real-world examples of successful PPC campaigns. By studying these, you can learn from the successes and failures of others. Look for case studies that include detailed analytics and performance metrics to understand the decision-making process behind the campaigns better.

Blogs and Forums

Blogs and forums are excellent resources for learning from experienced PPC professionals. Many industry experts share their insights, tips, and tricks on blogs, while forums provide a platform for asking questions and engaging in discussions with peers. Reading blogs like the HubSpot Marketing Blog can inform you about the latest trends and best practices in PPC analytics.

Google Analytics for PPC

Google Analytics is a powerful tool for analyzing PPC campaigns. Even if you don’t have your own campaign, you can learn a lot by exploring the features and reports available in Google Analytics. Understanding how to interpret data such as conversion rates, click-through rates, and bounce rates will be beneficial when you eventually manage a campaign.

Clicademy: See the Data Real Time

Clicademy is a unique platform that provides aspiring marketing and data professionals with the opportunity to learn digital analytics using real online data. Users can leverage Clicademy to enhance their PPC analytics skills. Registered members can organise micro-marketing projects and see how the promotional efforts are reflected in the site data.

To Sum Up

Learning PPC analytics without a live campaign is challenging but entirely possible. This guide has provided an overview of the various ways to learn PPC analytics without having a campaign. For those eager to dive deeper into PPC, consider exploring the resources mentioned and actively participating in the digital marketing community. The journey to PPC expertise is ongoing, and every step taken is a valuable addition to your skill set. Join Clicademy. Happy learning!


Top secrets of digital marketing analytics

Marketing practitioners are in touch with digital analytics all the time. But there are a few secrets in digital marketing analytics that they need to know. Some of these may need the disclosure. Others may just be so common that they are left in blind spots.

Secret 1: Before marketers ask for it, analytics has already started

Analytics relies on data. Creation of data does not wait for marketers’ command to go ahead. Neither do processing and analysis of data. In the era of Big Data, data come from everywhere and all the time. They appear in both quantitative and qualitative forms, structured and unstructured, in big volume or in small batches. Analytics happens in real-time as data emerge, or more precisely when things happen.

For example, when one started to create a campaign plan the first question was always about what the situation was. The description of the situation was a result of some analytics that had taken place before the need to know arose. At this point, the marketer just opened the dashboard to look for some analytics to confirm the situation.

What markets need to do is to treat analytics as an on-going process and know where to hunt for the needed data. This requires them to be sensitive as well as informed. Remember, when Mike Bloomberg asks that everyone else bring data, he knows they should already have them.

Secret 2: The APIs are making all these to happen

When using digital analytics, not knowing about APIs is like opening a website without knowing the Internet. Whereas the analytics dashboards are like websites, the APIs are equivalent to the world-wide-web protocols to enable the exchanges of data and information.

API is the application programming interface, which is a group of computer codes to ask computers to exchange data with other computers. Clicademy has another reading to focus on this topic. Today all digital analytics tools use APIs. Scroll down their websites to read their documentation. Here is an example from Ahrefs about its API offerings.

Marketers do not need to deal with APIs directly, just like website users do not need to know what the www protocols are. However, marketers need to know how to discuss APIs and their capabilities with computer engineering teammates and those in partner companies. They need to have a say in what data are exchanged between the data owners and the fetchers.

Secret 3: What you see is mostly vanity

Pageviews, sessions durations, returning users, new users… how do these metrics matter? Sadly, among the several hundreds of measurements that marketing analytics tools show us, most of them are more for vanity than usefulness.

Not fearing to critically analyse our own data, your Clicademist acknowledges that we are in such a situation said above. We are yet to roll out our search engine marketing programmes, so the hits and views we get are the leaves without connections to the roots. What concerns our most is the sign-up rate, with very few site visitor’s journeys ending at the Goal Page.

Then what is not for vanity? The answer is to choose the correct KPI(s) which should correctly measure the current marketing performances of your organisation. Once set, the KPI metrics are the analytics that is useful. Others are just good to have but non-essential. For example, the current performance for Clicademy hinges on building site traffic and signing up members. The visitor-to-member conversion rate, measured by the visits to the Goal Page versus the total traffic is our focus.

Secret 4: Analytics are most useful when helping to create solutions to digital marketing problems

Good numbers and upgoing darts just tell a partial story. Digital analytics is more useful when it shows problems. Being able to see these problems and to make difficult choices to solve these problems make a good decision-maker.

Marketers constantly need to set objectives. After doing this many times enough, setting marketing objectives becomes the second nature. Digital analytics enables the so-called data-driven objectives. Marketing managers should build it into a habit to consider setting marketing objectives means to solve some problems. And they are able to see the problems because of analytics data.

It is a tough call when faced with the choice of to see problems or to see vanity from data analytics. So when next time your boss asked you to bring data, would you bring in problems or good news?


Functions of digital analytics: sighting & solving problems

Digital marketing analytics solves problems. Even if all things go well, there is still a problem – how to do better? It is a constant battle for decision-makers to compete either against some rivals or themselves. Therefore Davenport and his co-authors argued 15 years ago that high-performing enterprises built their competitive strategies around data-driven insights and the resulting decisions.

Four functions

Digital analytics provide the functions for marketers to see problems and make decisions upon them. Specifically, the functions are of four types which are to report, explain, predict, and recommend.

These four functions follow a data analytics progression from describing the problems to the final step of recommending optimal solutions. In their 2019 book chapter, Prachi S. Deshpande, Subhash C. Sharma, and Sateesh K. Peddoju illustrated the information-to-optimisation progression. The figure below is an adaptation of their discussions.

Digital marketing analytics functions and types
Caption: Digital analytics and types (adapted from Predictive and Prescriptive Analytics in Big-data Era)

Digital analytics, according to the figure above, provides the sighting of the marketing problems in a sequence of hindsight, insight, and foresight. The ultimate purpose of the four functions is to optimise marketing value creation.

Corresponding to the four functions to report, explain, predict, and recommend are the well-known four types of digital analytics.

Descriptive analytics for reporting “what”

Descriptive analytics analyses data to tell what happened. It is generally the initial stage of data sighting. Since the data are about what already happened, the analysis creates hindsight.

The descriptive analytics mainly concentrated on “what” with the help of classification, clustering and segmentation of the data to discover patterns such as the central tendencies.

For such an example, Clicademy provides a data dashboard.

Diagnostic analytics for explaining “why”

The function of explanations using diagnostic analytics starts to create insights about why something happened. More complex analysis, often aided by computing power and algorithm, look for relationships between variables. This is the stage for the machine to learn about the patterns. However, the insights are still hindsight as of now.

Users of the diagnostic analytics need to be careful when taking the “why” as the causal explanation. It often requires controlled experiments to find out what caused what. More often, relationships between tested variables are correlations. Most A/B testings suggest correlations and associations between dependent and independent variables.

Predictive analytics for “so what”

Predictive analytics answers what is going to happen. Based on data patterns, analytics forecasts what will result from the predicted relationships between variables using regressions, simulations, and scenarios. This is the moment of “so what”.

Perhaps one of the most commonly predicted is how the current Covid-19 crisis will develop to affect every marketer in the world. Now the job is becoming more complex with the addition of a new deadly variable — the variants of the virus. It is the worst of the times for marketing, but one of the best times to see how predictive analytics works.

Prescriptive analytics for recommending “how”

Prescriptive analytics answers how to make the predictions to happen. This is the stage of decision-making. There should be a clear division of labour between algorithm and marketers. Computers are responsible for recommendations. Marketers make so-called data-driven decisions.

So this is the stage where marketers make the call. Analytics can point out the opportunities and even recommend how to take them. It is not that easy, though, to just follow the recommendations. It requires human judgement.


The digital analytics provides marketers with the functions to report, explain, and predict the problems and then recommend solutions. The time-reliant and increasingly automated sequences involve the four types of descriptive, diagnostic, predictive, and prescriptive analytics to inform marketers to make optimisation decisions.


Why and how digital marketing analytics are useful?

From pie charts to today’s dashboards everywhere, marketers cannot work without analytics. Marketing analytics have been in stay for decades. Digital analytics, however, has been the mainstream in recent years as everything goes online and digitalised. It has almost become a stand-alone craft.

Digital analytics gains the prominence largely due to the multitudes of the data and formats. In the good old days, a spreadsheet was sufficient to carry a company’s analytics. But in the digital era, a company’s analytics profile is complex. Website analytics alone using Google would have more than 200 metrics. What makes the situation more interesting is the speed of data creation and collection. Everything happens in real-time and a blink of eyes.

Despite the Four Vs of Big Data, digital analytics for marketing still falls in the realm of marketing analytics. This blog discusses the roles of digital analytics play in marketing to be useful for organisations. The roles are pretty straightforward.

In their famous Key Marketing Metrics book, Farris, Bendle, Pfeifer & Reibstein (2017) wrote,

Today marketers must understand their addressable markets quantitatively. They must measure new opportunities and the investment needed to realise them. Marketers must quantify the value of products, customers and distribution channels— all under various pricing and promotional scenarios. Increasingly, marketers are held accountable for the financial ramifications of their decisions. (p.2)

They summarised marketing metrics’ roles in organisations are to assess opportunities, performances, and accountability. But do not forget about risks.

Opportunities and risks

Digital analytics measures data collected internally and externally of organisations. Externally, the focus is mainly on consumers and competitions.

Consumer data enables businesses to understand consumer attitude and behaviours. Marketing decisions follow to engage and convert consumers into customers. The analytics work does not stop at monetising the insights. It continues to advise the efforts of customer relationship management.

Marketing analytics also help businesses manage risks. Social media monitoring is a common practice for firms to detect consumer sentiment. All social monitoring dashboards nowadays attempt to measure consumer sentiments to brands. A negative sentiment score would alert marketers to find issues and prevent them from becoming problems.

The ultimate purpose of identifying and measuring opportunities and risks is to set consequent marketing objectives, which are decisions to either take the opportunities or to walk around the risks.


Analytics measure how much results marketers have delivered. It is perhaps the biggest role that marketing analytics plays. Therefore the term KPI (key performance indicator) appears everywhere.

Monitoring performances relies mostly on internal data, for example, sales, revenue, and profit margin. Organisations tend to guard such data tightly unless they have to disclose, for example, the regular investor reports. Competitors crave for rival’s performance data. Marketing researchers and analyst value such data with the same level of interest.

Therefore it is unique for Clicademy to disclose its website performance data to assist the member’s learning of marketing analytics.

Performance data are significant by themselves. But they are even more meaningful when examined against objectives. This leads to the next role that analytics played.


Effective marketers deliver performances that meet or exceed objectives. Marketing objectives must be aligned with businesses’ ultimate objective which is to be profitable. In the old days when marketing was a side-kick of the sales function, marketing constantly needed to justify its expenses.

The contemporary definition puts marketing management in the central and ubiquitous position of a firms’ value creation and exchange with customers and other stakeholders. This does not alleviate marketers’ accountability to the financial ramifications of their decisions. What has been changed is the scope of the marketing objectives. They are no longer only to the quantifiable contributions to the sales numbers. Meeting the qualitative value creation and exchanges objectives, for example, managing a firm’s social citizenship, can also justify marketers’ accountabilities.  

Down to the objectives

There is a common phrase which is “marketing objectives” to link up the three roles of digital analytics for marketing. A firm uses digital analytics to assess opportunities and risks, performances, and accountability of the marketing teams. They only make sense when there are meaningful and realistic objectives set and delivered.