Have you ever collected weeks—or even months—of web data only to find that a tracking error made all your collected data inaccurate and inactionable? When these errors happen (and they do happen), we feel frustration associated with wasting time and effort, and we likely have to endure an uncomfortable conversation with our boss.
Analytics tracking mistakes are a pain. But good news, there is a solution to help you eliminate these tracking mistakes before they ever become a pain.
That solution is frequent, automated analytics testing.
To learn more about why frequent analytics testing is important and how ObservePoint can help, read on.
What Is Analytics Testing?
Analytics testing is the practice of ensuring your marketing analytics implementation is effectively collecting accurate data, which involves a systematic, comprehensive evaluation of the current analytics configuration on a website. Ensuring the functionality of your analytics implementation must be completed through manual or automated testing.
Testing your analytics implementation manually requires human effort to scan through the code found on your website, inspecting and testing the functionality of analytics tracking code by hand. The process of manual testing is extremely time extensive and easily susceptible to human error.
When analytics testing is performed with automation, a cloud-based software crawls your website and renders the code on every page to test for functionality. More specifically, analytics testing software scans for network requests coming from the pages on a site, recognizing requests coming from analytics tracking code and then recording where those pieces of tracking code are present and what data each piece of code is collecting.
Why Test and Why Test Frequently with Automation?
The importance of frequent analytics testing resides in the fact that websites change, sometimes rapidly, and in order to maintain data integrity throughout time, your analytics implementation must change along with your website.
As I mentioned above, without an automated testing solution, you must manually assess whether or not your website is collecting accurate data, which is time-consuming and prone to human error. Attempting to test your analytics implementation manually often leads to missed analytics tracking mistakes that negatively impact your customer’s experience, and by extension, your bottom line. Due to the cumbersome and error-prone nature of manual analytics tracking, you are much better off utilizing an automated testing solution, like ObservePoint.
ObservePoint offers solutions like Web Audits and Web Journeys that allow you to automatically identify and test the analytics tracking code present on your site, so you can efficiently ensure data accuracy as your website changes over time. Maintaining this data accuracy across time with ObservePoint will allow you to more fully understand your customers and confidently make actionable decisions to improve your customer experiences.
What Are Web Audits?
Companies like NBCUniversal, RS Components, Hewlett Packard Enterprise, and Datalicious use Web Audits to regularly scan their site and discover what technologies are gathering data. Each audit scans a given number of pages, cataloging the discovered technologies and aggregating those into an easy-to-read report.
What Are Web Journeys?
The Web Journeys feature makes it possible for companies like Suncorp and Lima Consulting to test their most important web experiences. Web Journeys replicate your site’s user journeys, such as shopping carts or user logins, from start to finish, and tell you if anything prevents the path from completing or if the analytics are not tracking the activity.
Using automation will free up time and resources, so you can put even more energy into analyzing accurate data and providing amazing customer experiences. These amazing customer experiences are what will separate you from your competition and increase company revenue.
Continually validating your analytics implementation as an ongoing practice will allow you to confidently make decisions that improve customer experiences and drive revenue growth.
In addition to helping you eliminate analytics tracking mistakes and improve your customer experiences, continuous analytics testing will also enable you to ensure your analytics implementation is working properly as your website and MarTech solutions periodically go through new releases—a process known as release validation.
Your website will undoubtedly go through changes and updates. Depending on how frequently you make these website changes, you may find yourself implementing a release schedule to periodically make batches of changes go live all at once. In the case of periodic releases, you will want an analytics testing schedule that corresponds with each new release of your website to ensure accuracy.
RS Components Tackles Release Validation with ObservePoint
For example, RS Components, a top distributor of electronics and maintenance products in the UK, releases batches of updates and changes to their website every three weeks. In order to maintain data integrity and make sure they haven’t broken anything on their site, they run ObservePoint Web Journeys and Web Audits tests in a pre-production environment before each release and then again in a production environment after their release.
This automated pre- and post-release testing with ObservePoint allows RS Components to discover errors early before a release, save 7 hours of manual testing time for each new release, use accurate data to make more confident decisions, and continually deliver improved experiences to their customers.
Stay on Top of Updates with Regular Testing
Regular testing helps remedy website release mistakes caused by the communication gap that can occur between development and analytics teams, as it’s common for tracking errors to occur as a result of critical information simply not getting from one team to another during releases. Frequent testing can help both analytics and development professionals stay on the same page throughout new releases by clearly identifying the presence and functionality of a website’s marketing technology before and after each release.
In addition to helping ensure accurate data through new website releases, using an automated testing solution like ObserverPoint can also help you test your marketing implementation with each new release of your tag management system, as well as through any updates to your marketing analytics stack.
This ability to continually test and check your analytics implementation over time is critical to maintaining accurate data, because any change to your marketing technology creates opportunity for error. Utilizing an automated testing solution like ObservePoint will allow you to maintain accurate data and peace of mind throughout each subsequent change to any of your marketing or analytics technology.
Another way using an automated analytics testing solution like ObserverPoint is beneficial is through tag monitoring.
I want to clarify the role tags play in your analytics implementation and why you should be monitoring those tags in your production environment.
Sometimes tags break, causing valuable data to go uncollected.
Uncollected data from broken tags creates inaccuracies in your overall data set, which makes good decision-making nearly impossible.
Additionally, a broken tag will not alert you of the fact that the tag is currently broken, which is why tags must be monitored. Monitoring tags can be done manually, but manually checking tags one-by-one is incredibly time-consuming and prone to human error.
A much better solution is utilizing an automated tag monitoring tool (like ObserverPoint) to monitor all your tags. An automated tag monitoring tool will rapidly scan the pages of your live website on a set schedule and indicate which tags are present and functional. If any of your tags are not functioning properly during a scheduled scan, the monitoring tool will immediately alert you of the error.
Additionally, a tag monitoring tool will allow you to test the critical customer journey paths on your site to make sure every step of those journeys is performing as planned.
Due to the ever-changing nature of live websites, tag monitoring is something that needs to be done on a regular basis to ensure your web data is continually accurate. When you regularly monitor and fix your tags, you ensure accurate, actionable data and make better business decisions as a result.
Ensure Accurate Data, Make Better Decisions, and Create Amazing Customer Experiences
Maintaining accurate data requires much more than a one-time audit. Maintaining accurate data requires ongoing validation, testing, and monitoring. Using automation through ObservePoint is a great way to ensure accurate data into the future.
When you use ObservePoint as an ongoing practice, you put yourself in a powerful position. You are able to make business decisions with confidence, because you know you have accurate data. You are able to continually provide your customers with amazing experiences that build loyalty into the future, because you more fully understand customer behavior.
This ability to confidently make business decisions and continually deliver amazing experiences to customers is what will drive overall company growth as well as your company’s bottom line.
To see firsthand how ObservePoint can help you and your business, schedule a demo.
This article is part of our Tag Auditing & Governance Guide:
Tag Governance Strategy
- The Tag Governance Framework: How to Govern Your Analytics and Marketing Tags
- The Total Ecobomic Impact of ObservePoint
- Top 3 Challenges of Data Governance & Performance Measurement
- 2020 Digital Analytics and Governance Report
Tag Auditing Training
- Tag Auditing for Beginners
- 3 Ways to Optimize Your Website with Test Automation [Webinar]
- Migrating from Adobe DTM to Launch: A 4-Phased Approach [Webinar]
- Migrating from Adobe DTM to Adobe Launch [Infographic]
- How to Conduct a Google Analytics Audit
- 21 Point Google Analytics Audit
- How to Conduct Cross-Device Analytics Testing with LiveConnect
- Analytics Testing with ObservePoint Is an Ongoing Practice
About the AuthorLinkedIn More Content by Brandon Watson