Are you trying to solve any of these challenges?

  • Manage structured data for campaigns, content, product catalogs or other marketing data
  • Enrich your digital platforms (e.g. analytics, CMS) for better personalization and insights
  • Improve tracking code/Adobe CID classifications globally
  • Build an improved and standardized process in your digital advertising/media operations
  • Unify disparate internal and external teams/agencies around creating clean and uniform data
  • Trying to get a taxonomy implementation buy-in, including standardizing naming conventions across content and campaigns
  • Going through a digital transformation and not sure where to begin

If any of these issues are important to you, Claravine can help. Schedule a demo today.

Learn how the best brands master campaign tracking

Marketing success begins with good data. This guide shares the steps any organization can take to implement campaign tracking best practices and optimize spend based on richer insights.

This guide will cover important topics including:

  • How to align campaign measurement with strategic marketing objectives
  • How to enforce a consistent classification taxonomy across teams and channels
  • How to optimize digital marketing based on reported performance metrics

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Learn how we can help you instantly standardize your tracking and improve your data quality in ways that drive better decisions.

Talking 'bout a (clean data) Revolution

By now, you’ve probably seen some version of this alarming news: Bad Data Costs US companies three trillion dollars a year. That’s three trillions.
And what, dear reader, can be done about this? It turns out much can be done. To make that case, let’s start by considering campaign marketing data — often considered the weak link within the larger sphere of web analytics data. As compared to your onsite web traffic data, which can be neatly tagged and precisely graphed to reconstruct a typical customer journey, your campaign data is generated by a slew of sites that you don’t control: media pages, blogs, search engines, just for starters. If you’re using programmatic ad buys you may truly have no idea of where your site traffic is coming from, unless you have a rigorous process for ensuring the uniformity and consistent inclusion of tracking code data for every referring URL.
Alas, tracking code data is notoriously easy to corrupt. The more marketing teams your organization utilizes, whether they are in-house or agency teams, the greater the likelihood that some marketer — out of ignorance or haste — is going to launch a campaign that includes a mistake in its tracking data. It might be a lower case letter where a capital is called for, or an errant hyphen. Any error, however small, can prevent that portion of the campaign data from flowing correctly through the analytics tool. Your analytics are going to give you data, sure, but how much can you really rely on that data if you suspect that some (or all) of your campaign data has gone missing? If it’s not all there, you’re getting only a partial picture.
If you will, imagine a world where the potential for human error and the correct application of tracking code data no longer intersect. What would that world be like?  To begin with, every marketer would feel empowered. If Marketer A plans to launch a campaign that will run across Facebook and Adroll and the company’s own email communications, he can be sure from the outset that the data from each of these platforms will be consistently generated, recognized by the analytics tool, and used to create a coherent, holistic picture of which messages and platforms are driving revenue.
And every analyst would feel empowered. Instead of printing off rows of hundreds of tracking codes, and going line by line to find any error that has crept into the data, she can focus on real-time customer response. Is one particular campaign asset or message driving a disproportionate response? That would be useful to know! Even better would be to ascertain if the increase in response is correlated with an increase in sales, or just with an increase in shares and likes. Both are valuable metrics, but each may lead to a different business response. Imagine a world where analysts provide analysis, instead of having to act as spreadsheet jockeys or, in the worst cases, toiling as data janitors cleaning up everyone’s collective mess.
And finally, in this new world, executives will feel empowered. Gone are the uncertainties about whether the incoming campaign data is clean enough to rely on for crucial business decisions. Instead of feeling compelled to buy every new, shiny marketing automation tool that crops up (in a sincere effort to finally shore up their data), they can re-invest in people and processes, and be deliberate in considering whether a new tool is necessary and/or will complement their existing workflow.  In recent years, executives have made significant investments in tools that allow for real-time customer response and highly customized buyer journeys. There are some amazing products in the market space; but no matter what remarkable capabilities they offer, they are still reliant on the quality of the data coming in. Imagine if, instead of having to chase a newer product suite, you could turn around and focus on getting full value from the martech investments you’ve already made.
What a world, eh? Not only do we think it’s possible, we know it’s possible, and we’re already doing it for 30 of your fellow Fortune 500 companies. Come talk to us about a free tracking code audit for your team. We’ll help you assess how close you are to this bright new future.

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