In today’s business climate, running your business without web analytics is like captaining a ship without a compass. Occasionally you may find yourself traveling in the right direction, but more often than not, you will be blown off course.
In order to navigate effectively, you need accurate web analytics. And to obtain accurate web analytics, you need an analytics implementation.
A robust analytics implementation is a must if you want to track more than simple vanity metrics (such as page visits or bounce rates) with a basic analytics solution installation. If you want to move your business forward and deliver amazing online customer experiences, an analytics implementation will be necessary.
Creating, deploying, and governing a fully functional analytics implementation will allow you to collect accurate data for effective web analytics. Analyzing this accurate data will enable you to more fully understand your customers and deliver amazing customer experiences. Some benefits of delivering amazing experiences to your customers include:
- Increased customer loyalty
- The ability to maintain a competitive edge in your niche
- An increased bottom line
These benefits all sounds great, but to obtain these benefits you need to get your foundation right. Your foundation is your analytics implementation.
So, what is an analytics implementation?
What Is an Analytics Implementation?
An analytics implementation consists of the following:
- Tags, which represent different vendors’ data collection scripts you deploy on your site.
- Triggers, which determine when and how your tags fire.
- Variables, which determine what data you collect and share with vendors.
Let’s take a look at each of these component parts.
Tags (also called Extensions if you’re using Adobe Launch) are bits of analytics tracking code deployed on your web pages that transmit network request data to your vendor of choice. Alternatively, you can think of tags as the individual network requests, especially since a single piece of vendor code can potentially fire multiple requests. From a functionality standpoint, tags are digital tools used to gain insights into customer behavior, allowing you to monitor and improve customer experiences through data analysis.
You want to deploy tags on each page of your site and throughout critical user journeys, as these tags will allow you to effectively collect and analyze crucial user data on your site. By analyzing this data, you can optimize user experiences and create a better digital world for your customers.
For example, you might want to track user behavior on a site form to ensure proper functionality, count submissions, and improve overall user experiences. In this case, a tag can be configured to fire when someone submits your form, recording the action for analysis. If you wanted to get really granular, you could place tags to track when users focused on different form fields, allowing you to further analyze user behavior like form attrition.
Each tag deployed on your site needs a trigger (also called a Rule if you’re using Adobe Launch), as triggers observe the activity on your website and then fire the appropriate tags when certain tracking events take place. An event that triggers a particular tag to fire can be any type of click, page view, or any other user interaction you want to track.
Without a trigger, a tag is just a dead bit of code existing on your site.
Variables (also called Data Elements in Adobe Launch) are set data values. These values can help determine where a tag management system fires specific tags, and they can store and communicate analytics information with your vendors and tag management system.
For example, if you track product data for an eCommerce store, one of the variables you might track in your analytics solution could be a product ID. Product ID variables would allow you to segment your analysis at the product level, so you can see which products are the most profitable or bring in the most revenue.
One way to ensure consistent variables across an entire site is by implementing a data layer, which serves as a repository for consistent analytics variables.
The data layer sits as an intermediate data repository that connects your website’s data to your your tag manager and your other marketing solutions. When a customer interacts with your website, the data layer gathers that data into a centralized, organized manner for easy data sharing.
In order to accurately send information, your data layer must be set up with clearly defined variables that match specific conventions. As a result, you will need to validate your data layer to ensure accurate data formatting and capture.
For a more full understanding of how the aforementioned elements of an analytics implementation work together, you should also know about tag management systems. Here’s a quick run-down.
Tag Management Systems
Tag management systems (TMSs) are software solutions that allow you to continually manage and maintain your analytics implementation. By using a TMS, you equip yourself with the proper tools to engage in tag management, which is the practice of deploying, sunsetting, and regulating tags on a website via a container code deployed on every page of your site.
These container codes serve as intermediaries between your TMS and the individual tags that fire on your site. In other words, the container codes are what communicate with your TMS and actually deploy your analytics tags in their proper place.
As you work to create synergy between your analytics implementation and your tag management system, you need to understand what can threaten the integrity of your data collection efforts.
The Greatest Threat to An Accurate Implementation
As your website continues to grow over time, your analytics implementation will get larger and increasingly complex. This complexity is exacerbated by the fact that large websites require multiple teams and individuals to deploy analytics technology.
When these individuals and teams aren’t completely on the same page—a regular and inevitable occurrence in the majority of companies—they tend to deploy conflicting technology. Conflicting technology on your site can cause everything from site malfunctions to broken analytics tags, resulting in inaccurate and unusable analytics data.
So, how can you remedy this tendency for technology conflict? The answer is automated testing.
Maintain Your Analytics Implementation with Test Automation
Test automation for analytics data entails the use of automated tests to run against your analytics implementation following a change to check for tracking errors such as missing tags, missing variable data, incorrect formatting of variable data, and other errors.
These tests help you ensure the integrity of your implementation by locating tagging errors and validating your data to ensure accurate data collection.
The benefits of applying test automation to your analytics implementation include:
- A more efficient way to ensure quality data
- Increased accuracy of data
- Greater confidence in analytics data for decision-making
ObservePoint’s automated testing solution gives you complete freedom to cater your analytics tests to the specific needs of your business and website.
With the help of an automated testing solution, you can efficiently monitor and maintain your analytics implementation while you move your business forward. Regularly testing your implementation will result in more accurate data now and into the future and will enable you to confidently make data-based decisions that positively impact your customers and your bottom line.
To be competitive in today’s business climate, you need to be an insights-driven business, and here at ObservePoint, we’re here to help you do just that. Learn more about how ObservePoint can help you with your analytics testing by scheduling a demo today.
About the AuthorLinkedIn More Content by Andrew Geddes