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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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How to Govern Tracking Code Creation

Suppose your team has received a mandate from above: your company is about to amp up its digital marketing in a major way. If you’re a marketer, you may be thinking, “Hallelujah!”

Your colleagues on the analytics side might have a different initial reaction. It could feel like dread. At most large companies, it’s the analysts who are closest to the problems their company has with consistent campaign tracking: lots of different demand generation tactics, different tracking code systems being used by various tribes in the company, not a lot of consistency or standards in naming taxonomies… In addition, the systems that exist are usually not well-documented or may have mutated unrecognizably over time. Marketing analysts often accept this unhappy reality as the nature of the business. They aren’t necessarily looking for a solution, because they’re told that the current reality is just the way things are. But wait, they may say: now you want me to double our campaign output, and the confusion that goes with it?

There is a solution to this quandary, one that will allow campaign analytics teams of any size to scale up their efforts. To get started, look for the extreme pain points, and begin to work your way out. As is so often the case, you’ll want to focus on some combination of upgrades to the people, process and technology involved in the work.

One of the first challenges out of the gate will be people: dealing with existing tribes in your marketing organization, also known as channel silos. It’s likely things have gotten…tangled.

Suppose email is its own group, with their own specific method for building patterns in their tracking codes. We’ll add a second email group called Operational Email, who once saw the Email group creating codes a certain way and riffed off of that. As the two groups’ needs changed, their creation paths diverged. You’ll see a faint genetic blueprint if you squint, but each now uses a mutated version of something that was already flawed. Evolution in the wrong direction.

Channels like paid search will be doing their own thing based on guidance from their agency partners. The same for Paid Display, going their own way with a different agency partner. Ditto Social Media, with yet a third agency. Each group has their own way of doing things with distinct agency partners and channels. Oh, and each uses their own method of reporting.

If this describes your organization, your analytics group is fully stuck in a reactive mode. They adapt (to the extent possible) to what each group is doing, but their activity is driven by the tribes, leaving them unable to create a coherent data picture.

Marketing organizations in this state typically lose all the granularity in their tracking. You’ll see a pattern and you may know it’s an Operational Email, but there’s unlikely to be any lower level granularity beyond which group created the tracking code — and no consistent taxonomy to build meaningful metadata from.

Which brings us to the process problem. If you work with each group to tell them, “your tracking codes should contain this pattern, and consistently use these delimiters, and then we can build an auto-classification for it in Adobe Analytics,” they will start off doing it right. Inevitably though, the goals of the group will change and expediency will cause them to launch campaigns without consulting you (not their fault). Their code structure will deviate and you will end up with the same old data issues because they no longer follow the pattern.

And this brings us to the technology problem. In 2019, can’t we do better than spreadsheets? Shouldn’t there be a platform that allows the marketing tribes to create codes with the data bits they need to keep their workflow smooth, in a safe environment designed by the analysts? Shouldn’t the analysts be able to put parameters in place — think guardrails on a roller coaster — to facilitate both speed and safety?

Yes. Yes to all those questions. In fact, we provide just such a solution, one that can help your team get its hands around the three keys to governing tracking code creation:

-Setting up patterns the right way.

-Governance (ensuring that patterns are applied in a consistent way over time.

-Link validation (ensuring that URLs are live and working before a campaign launches)

The right technology solution will address the people problem by using a custom view for code parameter fields. It will present each group of users with only the fields they need, ensuring that the tribes (and their agencies) are building their tracking codes the right way, as prescribed by the data goals.

The right technology solution will address the process problem by offering analytics teams a full view of the data they need in their analytics platform. The analytics for media often relies on data coming from agencies, and agencies don’t usually use your company’s analytics platform. They use the data that comes from an ad server like Doubleclick, or onsite pixels that feed into their conversion metrics. But across the board, we see increasing demand for personalized customer journey data that goes beyond last touch, and customized messages and landing pages. The right tech solution will allow your team to use data not just as part of reporting, but as part of personalization.

Remember, a lot of customer conversion happens offline. Imagine trying to stitch cross-channel, cross-device and in-person data without applying this kind of tracking consistency.

It’s 2019 — there’s a better way. Your team deserves a coherent data picture of how various marketing efforts interact. Moreover, if you want to personalize the customer experience you’re going to need that data served up consistently every time. Let us help!

Author: Joseph Riddle
June 27, 2019

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