Inaccurate Data: All Too Common

Every digital marketer who has used web analytics has probably lived this nightmare at least once:

The campaign launched. At first review, the analytics reports seemed somehow “off”. A brief review of why they were “off” revealed that the  tags were not placed properly. Or not placed at all. And the data that came back therefore was wildly incorrect. And therefore useless.

The trouble is that many digital marketers have probably lived this more than once.

Why does this happen?

It happens because while analytics is widely acknowledged as “very important”, it often gets implemented a little late in the development process. Worse, it’s often implemented by a team that really has too many other things to do than to focus on getting the analytics correct.

But in today’s digital marketplace, analytics itself (in other words, the ability to measure success) is as important as the content or campaign. And there’s not much in the way of good excuses why analytics is ever left to anyone but a thorough expert.

Many marketers are victimized by an organizational lack of awareness that there even is a problem with the analytics they have: no one is auditing the technology.

Then, one day, a senior marketer wants to know “why” something measured the way it did. And based on that, analytics goes under the microscope. Especially common is an audit of the underlying data collection technique–usually represented by javascript known colloquially as “page tags”.

The audit reveals the poorly placed tags; or non-placed tags. And even if it gets fixed, serious damage has been done: trust has been broken.

When news that “analytics is innacurate” bubbles up to management, they may seem to not care so much that it was something that might have been easy to fix. They may not even know it was fixable. The only thing that gets remembered is that the analytics was useless.

When analytics is deemed useless (or even suspect), people start to avoid it. They may blame the vendor (usually unfairly), they may blame the agency, they may even blame the category of analytics itself for being “not that helpful”.

When key marketers avoid analytics, it’s a bad day for ROI.

The key is to align expertise with business requirements. In other words, make sure that the page-tagging (especially custom tags) and tool configuration are done by experts who depend on your analytics success for their livelihood. Hint: most likely this is not your content agency.

Proper tagging and configuration are keys to supportable, verifiable data. Supportable data–accurate data–is the key to adoption. Adoption is the key to ROI.

Make sure you don’t sacrifice ROI because of inaccuracy.

Inaccuracy is very avoidable: by verifying the expertise of whomever is claiming they can make analytics work for you.