8.1 Introduction
Understanding the traffic behind online content is a useful means of identifying key audiences.
One way to do this is to use web analytics, which this module will center around. The module will start by providing a basic understanding of what it is, while also identifying the difference between website statistics and analytics. It will then move on to outline the two categories of web analytics, before discussing the five types. Next, an examination of the processes behind web analytics will take place, as well as looking at how it can be beneficial to marketing strategies. A brief discussion of how web analytics relate to social media will also occur, and then we will conclude by listing a number of best practices.
8.2 What is Web Analytics?
Web analytics are most often thought of as the means of measuring the impact of a website, but this is not solely the case.
The fact is it's actually far more complex than that. Web analytics is the multi-function practice that collects online traffic information, which is used for reporting and analyzing website data. In doing so, a company can understand the behaviors related to its website while also applying the data derived from the system of analysis towards future projects or goals.
Web analytics works by providing the owner or manager detailed information about the site and its users. This includes the number of visits to the site in general in comparison to page views, as well as trends within user engagement. It is also used as a means of conducting research related to the company, its brands, and/or campaigns. When web analytics are used properly, a company can improve the user experience, which should lead to increased traffic. It is important to note that web analytics, although founded to strictly mean the collection of data related to a website and its users, has now been broadened to include a number of other online platforms, such as social media.
8.3 The difference between website stats and web analytics
One of the biggest misunderstandings about web analytics is that it is strictly about website statistics. Although there are some similarities between the two, web analytics go beyond the surface-level data collected through website statistics, or web stats.
Website statistics are about collecting information related to how a user interacts with a website. In other words, it looks at the number of visitors a page had on a particular day, month, or even year.
Web analytics include that information but also seek to provide information related to why a user may have visited the page, and even how. In other words, web stats look at the minimal information about a website and its users, while web analytics take this into account as a means of understanding all of the factors that lead to the basic data; or to put it even more simply, web stats are only one component of web analytics.
8.4 Off-site and on-site web analytics
The above definition indicates that web analytics look at the bigger picture of website activity. Part of this data generation is broken down into two categories of analysis: off-site and on-site analytics.
Off-site:
Off-site web analysis looks at aspects of user engagement that are unrelated to a specific website. Another way to look at this is the measurement of a potential audience while examining its visibility and discussion about a website in comparison to the rest of the online world. The measurement of off-site web analytics can be conducted without owning or maintaining the website itself.
On-site:
On-site web analytics measure the behavior of the audience that has accessed a particular website; or what they do once they are on it. This measurement of behavior can include how many pages within the website a user has accessed, as well as how long they spent once there. This data is broken down into a number of measurable categories, which will be discussed in the next section.
FACT
Less than 30% of small businesses use web analytics, while another 18% do not use any sort of data tracking at all.
Source: Media Post
8.5 Types of web analytics
Data collected about a website's traffic and engagement is a crucial means of understanding the impact of the site, as well as user experience.
There are several types of analytics that can be used - all of which serve a different purpose.
These include:
-Click analytics
-Customer lifecycle analytics
-Geolocation of visitors
-Page tagging
-Web server log file analysis
An outline of each of these methods of web analytics will now take place in the following sections.
8.6 Click Analysis
Click analysis is an on-site form of web analytics that looks at the number of 'clicks' made by a user once they have entered a website.
The term click refers to the decisions made by a user, usually in terms of the links they select within a website. By analyzing this click activity, it can lead a website manager to better understand where traffic is directed once a user has accessed their site. In other words, of all the content found within a website, click analysis shows the information most accessed, while also providing a visual of how many pages the user engages with before leaving.
Click analysis can be accessed in real-time or through a snapshot, such as a given date or time. This is determined by the analyst and relates to the most relevant time capture for the specific project or campaign.
8.7 Customer Lifecycle Analysis
Similar to click analysis is the customer lifecycle analysis.
This is also a metric for analyzing data pertaining to user activity within a particular website. It involves page views and clicks, as well as third-party services, such as advertisements found within a site that lead to another.
The data collected through customer lifecycle analysis is used to provide valuable information or insights into visitor behavior. This can help to improve website optimization as well as user experience.
8.8 Geolocation of visitors
Geolocation is a form of website analytics that tracks a user's location.
It works by identifying the Internet Protocol (IP), which can provide information about the user's whereabouts, such as city or country.
The information collected using geolocation is used to better target specific geographic audiences. In other words, by identifying the exact locations of its audience, the website can be tailored to the area's preferences or behaviors. This would include ADA compliance, fraud detection, and overall content distribution. Geolocation can lead to the improvement in user experience since it allows the site manager to use methods of personalization.
Activity 1
Estimated Time: 20 minutes
Data collection through knowledge retention.
To demonstrate the process of data collection, start by identifying a number of people to interview. It is suggested that you speak with at least 3-5 people, preferably individuals who do not have any knowledge on the topic. Begin by explaining the concepts covered in this module - namely, what web analytics is and how it is used. You don't have to include every detail of the module, so there's no need to recite everything. The point is to test your understanding by explaining the wider concepts to those who are unfamiliar with the topic. After you have finished, have them relay back to you what they learned. As you go through this exercise, make note of reactions, responses, and any other behaviors. Following the reflection questions, tally the responses, as you will need them for the next activity as well. Note: these conversations can take place as one larger group or a series of one-on-one discussions.
After completing the above task, reflect on the responses using the questions below:
How did each person react to your knowledge-sharing sessions? Were there any verbal or non-verbal behaviors/reactions from the participants?
When they tried to explain everything back to you, how many got it right versus how many just did not grasp what you were teaching them? Were there any trends that occurred, such as similar information missing, or a failure to understand a particular topic? Did any of them seek prompts or other indications that they were looking for help?
What were the most difficult aspects of the explanation for you to deliver? Did you change this as you went along, or did you continue explaining it the same way each time? This exercise aims to test your retention of the concepts within this module by getting you to teach the material to others. This is also designed to provide a basic understanding of web analytics, and more specifically the data collection phase.
8.9 Page tagging
Created out of concerns related to the accuracy of the final type of web analytics (web server log file analysis, which will be discussed next) is page tagging.
Page tagging is also referred to as web bugs.
When a user accesses a website, the page is then tagged using a unique identifier that is attached to a particular user or computer. During subsequent visits to the same website or web pages, the user's information isn't extracted and counted against the data for that particular day's information. To put it another way, page tagging works by collecting the user's data on the first visit while also giving them a unique identity code. When the user returns to the site, that identification code is read by the website's data collection program and does not get recounted. This provides an accurate count of how many people have accessed a specific website, rather than the number of times a site has been opened.
8.10 Web server log file analysis
Web server log file analysis is considered to be the first means of web analysis. It is a means of collecting data using the server, rather than the site (such as page tagging).
Web server log file analysis works by identifying two units of measurement in relation to activity on the internet. The first is through the number of page views, which is counted as one request via the web server to view a certain page. The second is visits, which is counted as the number of requests via the web server to access the same page, by the same user, within a defined period of time. When the designated time - which was usually 30 minutes or so - had passed, the user's information would be deleted from the server log file, or the data of who had already viewed or visited a page. This led to double-counting, which provided inaccurate information.
Although the use of web server log files is still used today, they are not viewed as the most reliable. These log files are able to provide basic information on website statistics but are usually not analyzed without the consideration of other methods.
8.11 The process web analytics
Understanding the basics of web analytics and the various methods of obtaining data related to web activity is only the beginning. Knowing how it can be used to develop marketing strategies is equally important. This section will look at the processes related to how web analytics works. This section will be broken down into four sub-topics, including data collection, data processing, measurability, and strategy development.
Collecting data:
The process of collecting data is the basis of web analytics. Data can be collected using any other previously noted method but is dependent on how long the website has been in operation, and what the purpose of the data is. If the data collected is to be used to target a specific locale, rather than something more wide-reaching, then it doesn't make sense to look at the geolocation of the user's profile. Essentially, this first step is about collecting baseline data that will be used to set the measurability of the campaign, which will be discussed further below. However, it is important to remember that the data collected, at any stage, can be useful towards understanding the activity of the website, as well as how to enhance it in the future in terms of user experience.
Data processing:
Once the data has been collected, it is necessary to process it into tangible information that can be readily understood. This is the first stage of designing metrics. It works by taking the data and turning it into ratios and/or statistics.
Measurability:
The third phase of web analytics as a means of developing a marketing strategy is in the creation of measurable indicators, which are commonly referred to as KPIs, or Key Performance Indicators.
This is the process by which the translated data (the ratios and statistics derived from the collected data) are brought into the marketing strategy by applying a business approach. What this means exactly is that tangible objectives can be set using the baseline data collected from website activity. These objectives could be as simple as wanting to meet a specific number of page views or visits in another predetermined amount of time, but it can also be about overall activity or attracting a targeted demographic. The KPIs developed from this data are used to measure the success or failure of the campaign or strategy. If the KPIs are met, the chances are the website has boasted a positive user experience and is becoming more visible, which should lead to increased business.
Strategy:
Finally, after the data has been analyzed and the KPIs have been set, it's time to set the strategy. Generally speaking, the underlying goal of web analytics is to provide an optimal user experience while building the business. This could mean increasing market share or reaching a specific search engine ranking, for example. It should eliminate as many barriers as possible that could negatively impact the desired outcomes.
In other words, formulating the strategy is no more complicated than developing the path to achieving the KPIs. After the process has been completed the first time, it will eventually start over again, only this time using the data from the previous campaigns to build towards improved outcomes. As such, the previous data would be collected, and then analyzed. The themes and other insights extracted from the data would be used to develop a new strategy, which would require testing. Once this has been completed, the newly developed KPIs would be implemented, and the campaign would go live, looping back to the beginning upon its conclusion.
8.12 The importance of web analytics as a marketing Strategy
Web analytics are used to provide accurate data on a particular website or collection of web pages.
The data provided through these insights can help a business in the development of its marketing strategies. This section aims to consider a few of those rationales. First and foremost, web analytics are used to determine the rate of success for a specific website.
The data that is provided is the driving force of any online activity, as it clearly articulates a variety of patterns and trends pertaining to the company's website. It is also the simplest way to understand whether or not the content or tools to draw traffic to the website are working, or if these efforts have been wasted. In other words, it is difficult to ignore what the data is saying.
But aside from that, web analytics can have a number of other important functions in terms of business development and online marketing strategies. Many of the insights provided with the data identify additional information, such as which keywords were used to find the site or what the reference site was. It will provide very definite information about the users that access the website, as well as how marketing efforts are performing, by monitoring things such as traffic and user flow. It can also be used to determine when a goal within a marketing strategy has been met or how far off it is from being achieved. All of this information can directly be applied to a business, which in turn will help to direct future strategies and campaigns.
Activity 2
Estimated Time: 15 minutes
Analyzing the data.
To show how data is analyzed, using the responses from the previous activity:
Using the data you collected in the previous activity, begin to look at what you wrote. Pay special attention to the trends you highlighted, including the areas that were repeated back correctly, and those that were given inaccurately. Think about how the incorrect responses could have been remedied.
Once you have finished, try to answer the questions below:
-How frequently were responses relayed correctly, as opposed to incorrectly? Why do you think your participants were unable to relay the information back properly? What does this say about the participant? About your ability to pass on the information initially?
-When thinking back on the verbal and non-verbal cues - especially prompts from you to help, what were the most common behaviors? Why do you think this was the case? What assumptions can be made about these behaviors?
-Going back to the incorrect information, how could this be fixed? What do you think was the cause of this misinterpretation? Can it be corrected? If so, what do you think the impact would be on the overall exercise?
-In general, how does this exercise demonstrate the methods used to collect and analyze data, as indicated within the module?
This activity was designed to have you analyze the data you'd collected in the previous exercise, as a means of showing you how this process takes place, although in a simplified manner. It was also aimed to show how various factors can influence the data, and what different behaviors can mean to the overall results. Of course, the data collected through web analytics would not be influenced by human interpretation. However, this should demonstrate the process. Note: a bonus activity, to truly test these exercises, and the value of the collected data, would be to conduct retests to see if the same results appear, even when applying the recommendations you outlined.
8.13 A note on social media
As noted earlier in this module, web analytics started by solely tracking data pertaining to websites. But today, these methods of analysis are a key component of corporate social media profiles. These built-in features function in the exact same way that traditional web analytics does, by tracking information such as a user's location, what they viewed, and even the type of browser the site was accessed from.
Social media analytics also track information that is specific to the platform, such as the number of likes, shares, or other interactions within the site. This adds an extra measure that can be used to determine marketing goals and other outcomes. Like traditional web analytics, the insights provided through social media platforms are also beneficial to those responsible for the development of future marketing campaigns and strategies.
8.13. Best Practices
These include:
-Providing more than just traffic reports as a means of measuring a website's activity or success.
-When it comes to reporting, ensuring that the insights have been provided alongside the data.
-Avoiding snapshot reporting, as it usually doesn't tell the whole picture (unless of course, the report is on a very specific time slot).
-Allowing the data to speak for itself when it comes to decision making - people can make judgments based on personal biases, while the data cannot.
-Always communicate with the stakeholders as clearly and openly as possible; otherwise, the data will tell the truth.
The above-noted best practices are only some of the more common suggestions and it is not an inclusive list. Each of the listed points indicates the need to really look at what the data is saying, despite what the desired outcomes may be. Data can easily be left to the interpretation of an individual, but it is also the best way to provide an honest, accurate account of a specific measure.
These best practices emphasize the importance of thorough analysis and interpretation of data in web analytics. Providing comprehensive insights alongside raw data ensures a deeper understanding of website performance. Additionally, avoiding snapshot reporting and allowing the data to guide decision-making fosters objectivity and transparency. Clear communication with stakeholders is vital to ensure that interpretations align with the truth revealed by the data, facilitating informed decision-making and effective strategies.
Module Summary
The material disclosed in Module 8 surrounded web analytics. It covered a variety of topics related to the core subject, beginning with a brief background of web analytics. Following this introduction, it went on to show the differences between website statistics and analytics. This led to a description of the two categories of web analytics: off-site and on-site analytics. Once this was covered, the module went on to examine the five types of web analytics. These were identified as click analytics, customer lifecycle analytics, the geolocation of visitors, page tagging, and web server log file analytics. The processes involved in web analytics were later outlined in detail before a discussion on the importance of its use in terms of employing sound marketing strategies.
Next, a quick note on social media took place, which aimed to show how similar processes were found within these platforms. The module then finished by identifying several best practices. The purpose of this module was to provide a broad understanding of web analytics while providing detailed information on a number of related topics. This knowledge can then be applied to other aspects of digital marketing, including the development of future strategies and campaigns.
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