Data Tagging Best Practices to Build an Analytics Strategy

Web analytics and digital marketing tracking are essential for any business looking to grow their online presence; however, many businesses struggle to understand and make sense of the data they collect. A common problem is not having a clear analytics tagging strategy which makes it difficult to track user behavior and the effectiveness of marketing campaigns. By having such a tagging strategy for analytics implementation, it is possible to design and architect for execution a concrete measurement plan, to enable businesses can make data-driven decisions to optimize the user experience, increase conversions, and drive more sales.

Did you already implement your analytics tagging, and you need to improve it further? You might be interested in reading this article as well on successful tactics to improve your analytics implementation strategy

The importance of using tagging best practices for optimal data collection in a measurement plan

The use of best tagging practices is essential for achieving accurate and actionable insights from web analytics and digital marketing data. Proper tagging can help ensure that data is collected in a consistent and accurate manner, and that the data is of high quality. Before going into a deep dive to the fundamental aspects behind any analytics implementation strategy, there are few correlated critical aspects to keep in mind to mitigate risks and ensure a successful approach. Here are the main considerations to keep in mind while going through the projection and implementation of a comprehensive analytics strategy:

• Website page load performance is one important aspect to consider when implementing tagging. A tagging strategy that includes too many tags or tags that are not optimized can slow down the website, which can negatively impact user experience and lead to a high bounce rate or even search engine penalties.
• Privacy compliance is another important aspect to consider. Tagging should be done in accordance with the privacy laws and regulations of the country and region where the website operates. This includes ensuring that any data collected is done so with the consent of the user, and that the data is protected from unauthorized access.
• Comprehensive tracking is an important aspect of tagging, as it ensures that all relevant data is collected, including data from all website pages, important user interactions, soft conversions, transactional conversions, and marketing campaigns. This allows businesses to gain a holistic view of user behavior and website performance. Data quality and efficiency are also important aspects to consider.

Analytics Tagging Strategy

Website tagging is an essential aspect of web analytics and digital marketing at a scale especially for enterprises with huge or multiple websites and having a clear and effective tagging strategy in place can greatly improve the accuracy and insights of the data collected. Best practices for tagging include having a well-defined and consistent tagged process, as well as using web tagging tools to automate and streamline the data collection process. Below are the wen-win steps to follow for an efficient and successful strategy:

1. Listing Key Performance Indicators

Creating an effective analytics tagging strategy involves identifying the key performance indicators (KPIs) that are essential to your business, so you can determine which elements of your website you need to tag. KPIs represent all soft conversions such as important page views, product impressions, product clicks, adding items to carts, subscribing to newsletters etc.. or transactional conversions that contribute to business success such as submitting lead generation forms, requesting services, or purchasing products. Whether they are soft conversions or transactional conversions, KPIs will turn out to be the tracked metrics in analytics reporting on business performance. The output of this step is a document that states the metrics to measure the KPIs defining them concisely and clearly.

2. Defining the conversion funnel in the customer journey

It is important to identify all the elements that represent the user journey through all the marketing and conversion funnel steps. This will allow you to track and analyze the data that is most important to your business. To define such conversion paths and evaluate the user experience through the available interface, it is necessary to analyze the website design or mockups in case of a prelaunch activity, categories structure, contents, services, products and features to come out with a tagging plan to track specific interactions and clicks in a structured manner that allows reporting on the different dimensions that report on such features, website sections, and usability in a granular way.

The output should be a documentation that states what are the content elements, components, and interaction events that need to be tracked and what are the detailed necessary information schema to be associated with such elements.

For example, if you are tracking the interactions with an internal search bar, it might be a good idea to track the start of an interaction of the search bar and the submission event of a search event alongside the search query to understand how users interact with the search bar and what are the most relevant search queries that might reveal interesting insights. Another description of a some of the user interactions while examining and purchasing a product by tracking a product impression event, a product click through event, a product add to cart event, and a product purchase event while assigning the different parameters to the various events such as the product name, product variant, product price, applicable promotions etc.. to be able to analyze the entire process and measure accurately the entire process of product sales performances.

3. Writing a Business Requirement Document (BRD) for Analytics Tagging Solution Design

Now that you have a holistic view of all the important KPIs, as well as all possible contents and user interactions it is time to create a documentation that needs to be analyzed and executed by developers. It might be useful to discuss with your technical stakeholders first to understand what are the best implementation choices and limits that might impact the way a BRD is written, such as relying on a data layer and a Tag Management System (TMS) or if the analytics triggers will be manually hardcoded into the website.

Second, you need to start to assign all KPIs to metrics or events and different parameters or attributes that describe the contents and interactions into dimensions or variables that will reflect in the analytics tools. Then it will be necessary to start to elaborate all the data layer values and specific triggers that might be in the form of code snippets that the developers need to integrate on the website, that will eventually be mapped to the dimensions and metrics in the analytics tool defining all naming conventions of products or interaction steps for example. Consult the relevant developer documentation of your analytics tool. Another good practice is to create a data dictionary to standardize naming values and formatting so that you avoid collecting fragmented data that would eventually require manual elaboration and cleaning.

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   Analytics Tagging Implementation Execution

Now that BRD or tagging plan is ready for execution there are three important aspects to handle separately and potentially by different stake holders in the organization:

• Onsite implementation: Development and execution of the tagging plan into the website code or template should be carried out by the development team. This includes adding the tracking code to the website and implementing any custom events or triggers as outlined in the BRD. The developer should also ensure that the data layer has been properly declared and that the values match those specified in the BRD.
• Tag Manager Configuration: Deploying tag codes, defining variables, and injecting other scripts should be carried out if the implementing choice involved the usage of a TMS. This includes setting up the container for the website and adding different types of necessary tags and triggers as outlined in the BRD.
• Analytics Console Configuration should be completed. This includes setting up properties, virtual, or real report suites, attribution models, internal traffic filters, reporting dashboards, goals and custom dimensions/metrics as outlined in the BRD.

5. Analytics Tagging Implementation Validation

Analytics Implementation Validation is an essential step before going live with tracking on a website. This step is important because it helps you to ensure that data quality is high, and that the data being collected is accurate and actionable. It also helps to identify and correct any issues or errors in the implementation before they can affect the data being collected. To run a comprehensive validation, conduct such an activity in a preproduction environment first by defining a testing playbook that verifies and confirms whether the BRD specifications now reflect on the website perfectly or not. This activity of quality control should be based on designing the test cases to validate all possible interactions and website pages, so it should be based on a micro governance validation rather than a sample check to unveil covered potential threats that impact the data integrity.

Read further on analytics implementation quality control.

6. Continuous Process

Finally, make sure to put a strong organizational process in place to be able to perceive all new website updates and releases of new features, products, pages etc… because most of businesses do not have simply static websites that never change. So once an overall analytics tagging strategy is executed, the website will probably continue to evolve through content enrichments that might need to be examined time to time as they start in the organizational production process pipeline. So make sure to set up regular checks with different marketing and product stakeholders and every time a new piece comes in, treat it through the previous explained five steps as a smaller project in the same context from KPI definition to analytics implementation validation.

Conclusion

Remember always that data collection is never retroactive, so whatever is not forecasted by the analytics data collection strategy cannot be recovered or reconstructed through the historical data, so it is important to be proactive enough to anticipate the business needs through a concrete methodological approach. By following such tagging best practices, businesses can ensure that data is collected in a consistent and accurate manner, allowing them to make data-driven decisions with confidence. This can also help to reduce the amount of time and resources required to analyze and interpret the data.

Did you already implement your analytics tagging, and you need to improve it further? You might be interested in reading this article as well on successful tactics to improve your analytics implementation strategy.

Frequently Asked Questions About Analytics Tagging Strategy

What is an analytics tagging strategy and why is it crucial for my business?

An analytics tagging strategy involves planning and implementing tracking codes on your website to collect data about user interactions, crucial for optimizing business operations and user experience.

How do I start developing an effective tagging strategy for my website?

Begin by defining your business KPIs and understanding the customer journey on your site. For comprehensive guidelines, refer to Tag Management Best Practices.

Can you explain how website performance is impacted by tagging, and how to mitigate any negative effects?

Improperly managed tags can slow down your site. Using a Tag Management System like Google Tag Manager helps manage tags efficiently and reduces their impact on site performance.

What should I consider regarding privacy compliance when implementing a tagging strategy?

Ensure your tagging strategy respects user privacy and complies with laws like GDPR by including user consent management. More on this at Data Layer Importance in Data Capture.

What are the best practices for maintaining data quality and efficiency in tagging?

Regularly audit your tags and keep your documentation up-to-date to ensure data accuracy and efficiency.

How do I ensure comprehensive tracking across all pages and user interactions?

Ensure all pages and user interactions are properly tagged and regularly validate your tracking setup to cover all site activities.