[Data Quality](/categories/data-quality) September 8, 2023 # Bulletproof Your Digital Analytics with Data Validation Let's delve into data validation methods for your digital analytics to help you leverage your data collection efforts while preserving your data quality. ![](/images/64994225b80181b90166ae3e_unnamed-modified.avif) **[Mariona Martí](/author/mariona-marti)** Digital Marketing Specialist 5 min read · 1158 words ## Data Validation: The Foundations of Data Quality To identify and correct errors, inconsistencies, and inaccuracies in the data your apps and websites are sending to third-party integrations (e.g.: Google Analytics, Segment, Mixpanel, etc.) and ensure all this data enters the system correctly with the desired quality standards, it is essential that proper **data checks** are implemented. This is where [** data validation techniques**](/docs/data-validation) come into play. **Cleaning data and validating it after it is already in the system costs more money and time.** Moreover, not only does it negatively affect the revenue of the company, but it also becomes a disruption to the regular workflow, as it forces people to waste time on unruly and inaccurate data before it can be used for strategic decision-making. That is why data validation techniques serve **as a proactive mechanism** designed to intercept and rectify issues before errors can easily slip through the cracks, compromising the integrity of your results. ## Data Validation & Trackingplan With Trackingplan, you can be automatically notified whenever your properties, events, and user acquisition data don’t conform to the values you have specified. ### Data Type Validation The [Data Type Validation](/blog/optimize-data-validation-within-your-actual-analytics-schema-with-event-types) check is useful to ensure the data entered into the system has the correct data type. Trackingplan automatically interprets which data type is being tracked, but you can make as many manual adjustments as necessary. You can choose between *boolean, number, string, array, object, regex, enum,* or keep it unconstrained with *any*. If Trackingplan detects that the events sent do not conform to these specifications, a warning will be generated. ![Data Type Validation Example: Example of data type validation warning](/images/67eb9ee43d5480618b195ab0_66fd1e5aa494cbc42d817dba_65f1777e8990f2eb1ca1fe17_Data-20Type-20Validation.avif) ### Enum Validation Enums allow you to specify in advance the values you expect for a property to be notified every time it receives a value that does not conform to your list of predefined constants you had already specified. ![Example of how can you create Enums using Trackingplan](/images/67eb9ee43d5480618b195ab6_66fd1e5aa494cbc42d817dc0_65f177a5c592a2a6b1a47413_Enums-20creation.avif) Moreover, Trackingplan allows you to **autocomplete your Enums with the values that have been observed in the last 30 days in that specific property.** Doing this will automatically show you all the values detected for this property, but you can also check that all the values are correct and, in case they are not, delete them. Trackingplan will be checking that all the values in this property match the specified Enum. If it detects a value that is not within this list of predefined constants, Trackingplan will automatically send you a warning. Moreover, to ensure seamless recognition by the server, Trackingplan also offers the option to **ignore cases and diacritics** to prevent potential issues where the server might identify them as implementation problems. ### RegEx (Regular expressions) Validation RegEx Validation is useful for implementing real-world data input validation, as it allows you to specify regular expression patterns such as phone numbers or email addresses. Trackingplan will automatically warn you whenever a property does not match with the regular expression pattern to which all the values seen for a property must conform. In general, this field property is used to perform validation checks (format, length, etc.) on the value that the user enters in a field. If the user enters a value that does not pass these checks, it will throw an error. The process of setting up Regex for a property is very similar to the one used for Enums. These are completely customizable to your needs and even allow you to insert test values to confirm that your regular expression patterns will work as you expect. Moreover, for Regexes you can also ignore cases, diacritics, or both to prevent in advance any situation where the server would recognize it as an implementation issue. ![Ignore case and diacritics example](/images/67eb9ee43d5480618b195ab3_66fd1e5aa494cbc42d817dbd_65f177cca11527cf20bc55e5_RegEx-20Validation.avif) From this point on, Trackingplan will be checking that all the values for these properties match the specified regular expression, and if the value does not conform with the pattern you have specified, our dashboard will automatically show you a warning. ### Function Validations Trackingplan also allows you to set up any complex validation at track level and will warn you every time any of your properties don’t conform to the function provided to validate an event. For example, you could add cross-condition validation to ensure that all products logged in a cart carry a valid *product\_sku* given the *page* section). Just let our [support team](mailto:support@trackingplan.com) know which validation rules you'd like to add, and consider it done! ### Campaign Validations Moreover, Trackingplan also allows you to set up User Acquisition specification warnings to validate your campaigns based on your own requirements. With it, Trackingplan will automatically inform you any time the attribution data collected in your campaigns doesn’t meet the custom rules you have defined so you can get it fixed before compromising the performance of your marketing investments. Let’s see some examples: - If the campaign contains the keyword “black Friday”, the medium attribute cannot be ‘press’. If this combination is detected, please send me a warning. But not only campaigns are supported. Indeed, you can also set up validations for any of your landings, referrals, pages, mediums, sources, and event attributions. Some examples can be: - All the landing pages should follow this specific format "/section/abc. - The event *AddToCart* should only originate on these 3 pages: *a*, *b,* and *c*. If this event is detected on a page that is not listed above, send me a warning. Just ask [support@trackingplan.com](mailto:support@trackingplan.com) which validation rules you would like to add and we will implement them for you. ## What to do with Validation errors? Trackingplan automatically alerts you about any error happening in your digital analytics, spotting issues for you so you can focus on what you do best. However, at Trackingplan we know sometimes, after receiving an alert, it can be a bit hard to know what to do next, especially when this has to do with a property or event with validation errors that do not conform to the values you have specified. Hence, if you usually struggle to find the **root cause** of those warnings related to properties missing or not conforming to the validation rules or constraints specified, our [** Warning Debug**](/docs/debug-warnings) feature is for you. [You can see it in action in this video](https://youtu.be/sxWW1nGlhVI). ## Conclusion With [**Trackingplan**](/), validation errors are not just detected, but also categorized and presented in a way that simplifies troubleshooting. Our [** Warning Debug**](/docs/debug-warnings) feature, for instance, provides an in-depth analysis of your warnings related to properties missing or not conforming to your validation rules. By identifying the root cause of these warnings, users can quickly address the issues and ensure [data integrity](/blog/what-is-data-integrity). Nonetheless, Trackingplan not only takes a step further by providing an early warning system, indicating data inconsistencies before they escalate to larger issues, but it also allows users to take preventive measures to avoid problems before these even reach production, affecting, therefore, the quality of their digital analytics by offering a fully automated data QA and observability solution. [***Get started today***](https://app.trackingplan.com/signup) *to experience the benefits of Trackingplan first-hand and automatically validate your Digital Analytics health.* *For more information, you can always* [***book a demo***](https://calendar.app.google/zVwy6x5zqiPpJ5ae7)*.* On this page 1. [*01*Data Validation: The Foundations of Data Quality](#data-validation-the-foundations-of-data-quality) 2. [*02*Data Validation & Trackingplan](#data-validation-trackingplan) 3. [*03*What to do with Validation errors?](#what-to-do-with-validation-errors) 4. [*04*Conclusion](#conclusion) **Stop babysitting tags** Trackingplan audits your real user data around the clock and flags issues before they cost you. [Start free trial →](https://app.trackingplan.com/signup) ![](/images/64994225b80181b90166ae3e_unnamed-modified.avif) **Mariona Martí** Digital Marketing Specialist At Trackingplan since 2022, Mariona turns complex analytics challenges — tags, consent, broken conversions — into relatable stories that connect with the analytics community. Share Copy link [LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fwww.trackingplan.com%2Fblog%2Fbulletproof-your-digital-analytics-with-data-validation) [X](https://twitter.com/intent/tweet?url=https%3A%2F%2Fwww.trackingplan.com%2Fblog%2Fbulletproof-your-digital-analytics-with-data-validation&text=Bulletproof%20Your%20Digital%20Analytics%20with%20Data%20Validation) Read next [All Blog →](/blog) - [ 15 minData QualityJuly 3, 2026 ### 5 approaches to tracking audits and monitoring, compared Browser extensions, site crawlers, API auditors, BigQuery, and real-user monitoring compared: what each tracking audit tool covers and where it falls short. by **David Pombar**](/blog/5-approaches-to-tracking-audits-and-monitoring-compared) - [ 7 minData QualityApril 25, 2026 ### Data Integrity for Web Analytics: How One Enterprise Solved Its Cross-Platform Data Quality Crisis with Automated Observability How one e-commerce company reduced analytics discrepancies by 94% with automated data observability: real-time monitoring, better attribution, faster teams. by **Alexandros Andre Chaaraoui**](/blog/data-integrity-for-web-analytics-how-one-enterprise-solved-its-cross-platform-data-quality-crisis-with-automated-observability) - [ 19 minData QualityJanuary 5, 2026 ### How Do You Ensure Data Integrity? A Practical Playbook How do you ensure data integrity? Discover a practical playbook on validation, monitoring, and governance to build analytics pipelines you can trust. by **David Pombar**](/blog/how-do-you-ensure-data-integrity) Trackingplan ## See everything. Miss nothing. Your implementations audited around the clock with real-time, real-user data. Real-time alerts about errors or changes in your data, campaigns, pixels, privacy and consent. Let AI flag issues before they cost you. [Start free trial →](https://app.trackingplan.com/signup) [Book a demo](/demo)