Digital Analytics Fundamentals
Content
Analytics Academy
Digital Analytics Fundamentals The importance of digital analytics
Introduction In this lesson, we will talk about what the term “digital analytics” actually means. We’ll talk about how today’s changing customer behavior has dramatically altered the way businesses need to approach measurement.
The evolving customer journey But before we talk about measurement, let’s review a few major trends that are driving change for every business both big and small alike. ● First, the internet has made the world’s information and media available to nearly everyone at the click of a button. ● Second, mobile devices have helped connect nearly everyone around the world, 24 hours a day, 7 days a week. ● And finally, cloud computing has provided us with practically infinite computing power and for cheap.
Because of the first two trends, the consumer journey is forever changed. People are empowered with more information than ever: product reviews, recommendations from friends or experts, store inventory, and competitive pricing. All these things are now instantly available.
At the same time, cloud computing has empowered organizations to analyze more business data than ever before.
The importance of building your analytics infrastructure Unless you have a solid infrastructure to collect and distribute data, and the skills to analyze and interpret that data, making business decisions about what you should be doing online to understand and connect with your customers can be overwhelming.
1
You need the right people, processes and technology to uncover all the ways you engage with your customers, to measure the effectiveness of those engagements, and to make sure you’re taking actions based on your data to improve your business results.
This is where the field of digital analytics comes in!
Defining “digital analytics” So what do we mean when we say “digital analytics?” Let’s take a look at a definition from a wellrespected digital marketing evangelist, Avinash Kaushik. Here’s his definition:
Digital analytics is the analysis of qualitative and quantitative data from your business and the competition to drive a continual improvement of the online experience that your customers and potential customers have which translates to your desired outcomes (both online and offline).
Your customers’ purchase journey Let’s unpack this definition and talk about a few key elements of digital analytics, starting with the most important part first your customers.
For a long time, we’ve had the marketing concept of a purchase funnel with various stages of customer interaction. This funnel consists of the following stages: ● ● ● ● ● building awareness acquiring interest engaging with potential customers driving them towards a conversion online or offline retaining them as customers
With the consumer increasingly in control, the linear purchase funnel is no longer relevant. The customer is at the center of the universe.
With all of their choice and control, we now recognize that customers can start their purchase journey at any point along their decision path. A marketer’s job is to figure out how to tap into this new dynamic and anticipate where customers will appear and what messages they need to hear. This can only be achieved if you’re focused on analyzing the customer, not the individual channel your customer is coming from, or the device they’re using to find or engage with you. 2
With customers ever more in the driver’s seat and controlling the speed and timing of their engagement, businesses need accessible, reliable, holistic and near realtime customer analytics to understand how well they are performing.
Qualitative and quantitative data Next, let’s talk about the concepts of qualitative and quantitative data.
Traditional web analytics has given us access to massive amounts of quantitative data about your website. This data tells us many things, like the size of your online audience, where they’re located, the performance of your online marketing and what people do once they visit your website.
For many years, tools like Google Analytics were only capable of collecting quantitative data for websites. But now, with the development of new technology, Google Analytics can track mobile applications, cloudconnected pointofsale systems, CRM systems, video game consoles, and even home appliances, like your refrigerator. This allows you to remove the artificial data walls between your customer engagement points. You can have a more comprehensive view across all of the touchpoints consumers might have with your business, not just your website.
Qualitative data, on the other hand, explains the why. An example of qualitative data is data you collect through a survey. Asking users why they came to your site, if they were able to complete their intended task, and why they were or weren’t able to complete that task can give you valuable information about your user’s experience that you can’t get with quantitative measurement alone.
Measuring outcomes Next, let’s talk about measuring outcomes. One of the most important steps of digital analytics is determining what your ultimate business objectives or outcomes are and how you expect to measure those outcomes.
It’s important to have a clear measurement strategy to guide your implementation strategy and your data analysis.
In the online world, there are five common business objectives: ● First, for ecommerce sites, an obvious objective is selling products or services. 3
●
Second, for lead generation sites, the goal is to collect user information for sales teams to connect with potential leads.
● ●
Third, for content publishers, the goal is to encourage engagement and frequent visitation. Fourth, for online informational or support sites, helping users find the information they need at the right time is of primary importance.
●
And finally for branding, the main objective is to drive awareness, engagement and loyalty.
There are key actions on any website or mobile application that tie back to a business’ objectives. The actions can indicate an objective, like a purchase on an ecommerce site, has been fully met. We call these your “macro” conversions.
Some of the actions on a site might also be behavioral indicators that a customer hasn’t fully reached your main objectives but is coming closer, like, in the ecommerce example, signing up to receive an email coupon or a new product notification. We call these your “micro” conversions. It’s important to measure both micro and macro conversions so that you are equipped with more behavioral data to understand what experiences help drive the right outcomes for your site.
The continual improvement process Finally, let’s talk about the idea of continual improvement.
Data can be the driver of a continual improvement process for your business. Let’s step through this process and talk about it in more detail.
●
The whole process starts with measurement. How many people are completing the customer journey? And where along that journey are you losing or retaining customers? In a nutshell, the measurement stage is all about collecting the data needed to answer your business questions.
●
Next, we need to do reporting to package the data in a readable format and then get information out to decisionmakers so that they can be empowered with the information they need to make business decisions. This often happens by developing and distributing premade reports or dashboards.
●
Then analysis has to happen. Analysis can be as simple as identifying larger trends, but it can also be complex, including deep segmentation of your data or competitive analysis comparing your performance to an industry benchmark. 4
Essentially, analysis is the process of developing a hypothesis that reflects your expectations, and then figuring out why the numbers do, or do not, match those expectations. When unexpected events happen in your data, analysis helps you figure out why.
●
Testing is the next phase of the process. This is where you try different solutions to the problems you identified during your analysis. Testing is critical because it takes opinions out of the decision making process for discovering improvement opportunities.
●
Finally, you repeat what you learn from this whole process and you improve.
Conclusion So let’s look at our definition of “digital analytics” once more to summarize what we’ve covered in this lesson.
First, we talked about how the rapid growth of the internet and increased accessibility to information and data has opened new opportunities for measurement, but also complicated how we measure a customer’s journey and their engagement with your business online.
These changes have made it important for practitioners of digital analytics to think about how their business infrastructure the tools, processes and people support the continual improvement process of measuring, reporting, analyzing, testing and improvement.
This continual improvement process should include both qualitative and quantitative data about how your customers engage with your business, and ultimately whether your digital assets are driving customers to your desired online and offline outcomes.
Complete the lesson activity >> Visit the activity for this lesson now
5
Digital Analytics Fundamentals The importance of digital analytics
Introduction In this lesson, we will talk about what the term “digital analytics” actually means. We’ll talk about how today’s changing customer behavior has dramatically altered the way businesses need to approach measurement.
The evolving customer journey But before we talk about measurement, let’s review a few major trends that are driving change for every business both big and small alike. ● First, the internet has made the world’s information and media available to nearly everyone at the click of a button. ● Second, mobile devices have helped connect nearly everyone around the world, 24 hours a day, 7 days a week. ● And finally, cloud computing has provided us with practically infinite computing power and for cheap.
Because of the first two trends, the consumer journey is forever changed. People are empowered with more information than ever: product reviews, recommendations from friends or experts, store inventory, and competitive pricing. All these things are now instantly available.
At the same time, cloud computing has empowered organizations to analyze more business data than ever before.
The importance of building your analytics infrastructure Unless you have a solid infrastructure to collect and distribute data, and the skills to analyze and interpret that data, making business decisions about what you should be doing online to understand and connect with your customers can be overwhelming.
1
You need the right people, processes and technology to uncover all the ways you engage with your customers, to measure the effectiveness of those engagements, and to make sure you’re taking actions based on your data to improve your business results.
This is where the field of digital analytics comes in!
Defining “digital analytics” So what do we mean when we say “digital analytics?” Let’s take a look at a definition from a wellrespected digital marketing evangelist, Avinash Kaushik. Here’s his definition:
Digital analytics is the analysis of qualitative and quantitative data from your business and the competition to drive a continual improvement of the online experience that your customers and potential customers have which translates to your desired outcomes (both online and offline).
Your customers’ purchase journey Let’s unpack this definition and talk about a few key elements of digital analytics, starting with the most important part first your customers.
For a long time, we’ve had the marketing concept of a purchase funnel with various stages of customer interaction. This funnel consists of the following stages: ● ● ● ● ● building awareness acquiring interest engaging with potential customers driving them towards a conversion online or offline retaining them as customers
With the consumer increasingly in control, the linear purchase funnel is no longer relevant. The customer is at the center of the universe.
With all of their choice and control, we now recognize that customers can start their purchase journey at any point along their decision path. A marketer’s job is to figure out how to tap into this new dynamic and anticipate where customers will appear and what messages they need to hear. This can only be achieved if you’re focused on analyzing the customer, not the individual channel your customer is coming from, or the device they’re using to find or engage with you. 2
With customers ever more in the driver’s seat and controlling the speed and timing of their engagement, businesses need accessible, reliable, holistic and near realtime customer analytics to understand how well they are performing.
Qualitative and quantitative data Next, let’s talk about the concepts of qualitative and quantitative data.
Traditional web analytics has given us access to massive amounts of quantitative data about your website. This data tells us many things, like the size of your online audience, where they’re located, the performance of your online marketing and what people do once they visit your website.
For many years, tools like Google Analytics were only capable of collecting quantitative data for websites. But now, with the development of new technology, Google Analytics can track mobile applications, cloudconnected pointofsale systems, CRM systems, video game consoles, and even home appliances, like your refrigerator. This allows you to remove the artificial data walls between your customer engagement points. You can have a more comprehensive view across all of the touchpoints consumers might have with your business, not just your website.
Qualitative data, on the other hand, explains the why. An example of qualitative data is data you collect through a survey. Asking users why they came to your site, if they were able to complete their intended task, and why they were or weren’t able to complete that task can give you valuable information about your user’s experience that you can’t get with quantitative measurement alone.
Measuring outcomes Next, let’s talk about measuring outcomes. One of the most important steps of digital analytics is determining what your ultimate business objectives or outcomes are and how you expect to measure those outcomes.
It’s important to have a clear measurement strategy to guide your implementation strategy and your data analysis.
In the online world, there are five common business objectives: ● First, for ecommerce sites, an obvious objective is selling products or services. 3
●
Second, for lead generation sites, the goal is to collect user information for sales teams to connect with potential leads.
● ●
Third, for content publishers, the goal is to encourage engagement and frequent visitation. Fourth, for online informational or support sites, helping users find the information they need at the right time is of primary importance.
●
And finally for branding, the main objective is to drive awareness, engagement and loyalty.
There are key actions on any website or mobile application that tie back to a business’ objectives. The actions can indicate an objective, like a purchase on an ecommerce site, has been fully met. We call these your “macro” conversions.
Some of the actions on a site might also be behavioral indicators that a customer hasn’t fully reached your main objectives but is coming closer, like, in the ecommerce example, signing up to receive an email coupon or a new product notification. We call these your “micro” conversions. It’s important to measure both micro and macro conversions so that you are equipped with more behavioral data to understand what experiences help drive the right outcomes for your site.
The continual improvement process Finally, let’s talk about the idea of continual improvement.
Data can be the driver of a continual improvement process for your business. Let’s step through this process and talk about it in more detail.
●
The whole process starts with measurement. How many people are completing the customer journey? And where along that journey are you losing or retaining customers? In a nutshell, the measurement stage is all about collecting the data needed to answer your business questions.
●
Next, we need to do reporting to package the data in a readable format and then get information out to decisionmakers so that they can be empowered with the information they need to make business decisions. This often happens by developing and distributing premade reports or dashboards.
●
Then analysis has to happen. Analysis can be as simple as identifying larger trends, but it can also be complex, including deep segmentation of your data or competitive analysis comparing your performance to an industry benchmark. 4
Essentially, analysis is the process of developing a hypothesis that reflects your expectations, and then figuring out why the numbers do, or do not, match those expectations. When unexpected events happen in your data, analysis helps you figure out why.
●
Testing is the next phase of the process. This is where you try different solutions to the problems you identified during your analysis. Testing is critical because it takes opinions out of the decision making process for discovering improvement opportunities.
●
Finally, you repeat what you learn from this whole process and you improve.
Conclusion So let’s look at our definition of “digital analytics” once more to summarize what we’ve covered in this lesson.
First, we talked about how the rapid growth of the internet and increased accessibility to information and data has opened new opportunities for measurement, but also complicated how we measure a customer’s journey and their engagement with your business online.
These changes have made it important for practitioners of digital analytics to think about how their business infrastructure the tools, processes and people support the continual improvement process of measuring, reporting, analyzing, testing and improvement.
This continual improvement process should include both qualitative and quantitative data about how your customers engage with your business, and ultimately whether your digital assets are driving customers to your desired online and offline outcomes.
Complete the lesson activity >> Visit the activity for this lesson now
5
