Data Collection,
Integrity &

Fuel your data-driven strategy

Get answers to business questions by collecting data you can trust. Only when your data is clean and reliable can you be well-informed and implement strategies that propel your business forward.



Data Collection Services

In order to design a data collection process that is perfectly tailored to your needs, we must first answer a series of important questions:


  • What data should be collected and what data is too much?
  • What are your data sources?
  • Are your app screens categorized?
  • Are your products categorized?
  • Do users’ carts expire?
  • How do you identify your marketing channels?


We’ll work with you to catalog your data, define a content hierarchy, architect data collection, and organize access to data within and across your organization.

A building would never be constructed without architetural plans. This same principle also applies to how you approach data collection.


Analytics teams must collect data from a wide array of sources, then combine that data for analysis in a structured way. Solidify the foundation of your analytics practice by building data collection into your code. This often proves to be an extremely demanding task for developers to tackle alone.


We will work with your development teams to evolve your practices to include data collection for the purpose of the overall system becoming more self-aware.

Today, the variety of devices and technologies used to browse a digital property make it so that one user can be misidentified as multiple unique users as they access your website from multiple devices.


We can help you accurately examine user behavior across devices so that you can build a holistic experience that spans devices.

Elevating your user’s experience is no longer a choice, but rather a competitive advantage that makes a significant difference to your bottom line.

We create a consistency of values across tools, and enable easy addition of tools for personalization, remarketing, and more.


If you consider implementing a Tag Management Solution for your website or app (and you should!), creating a data layer will provide the maximum flexibility and ease of implementation.


A data layer will surface metadata about the UI, the user, and their interactions so that your many marketing tools can all pull values from a single source.

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Data Quality

Gathering data is comforting, but it is not enough. For data to be truly valuable and actionable, it first needs to pass rigorous testing.


We validate your data with preproduction QA and then production validation. Our QA engineers don’t just spot-check that tracking is in place, they compare their tracking results to our list of expected values for each tracking call. This process is more rigorous than any other agency.


By ensuring data quality, you will mitigate risks associated with bad data and eliminate data doubts.

In situations when tests are run repeatedly over a long period of time, automated testing can reduce time spent on QA processes and give you the ability to schedule the regression tests.


Automated regression testing helps you make sure that the problems corrected by a fix have actually been solved, and that the fix did not break anything else on the site.


We can help you make sure that your launches work flawlessly, minimize the risk of errors, and perform the way they were intended by implementing automated regression testing.

Getting frustrated with the areas in your dashboard that stakeholders keep skipping because they feel something is off with that data, but they can’t put their finger on the issue?


We can help you validate data in reports with automated QA reportlets and anomaly detection.


This will save you both time and energy, and you won’t have to waste precious resources on the wrong reports, but rather focus on delivering the next actionable insight for your company.

How much do you trust your data now? Do you still trust it will be accurate in a week? How about in a month? Or a year?


Get alerts when production data spikes or dips unexpectedly, days or months after implementation.


With our help, you can notify responsible colleagues of potential data quality issues and also improve the visibility of your data quality trends, so that you can be prepared to tackle any business questions that may emerge.

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