Let’s face it, web analytics tools have been around for a while. Google Analytics was created in 2006, after a 2005 purchase of Urchin. Omniture was founded in 1996 and purchased by Adobe in 2009. While these are just a few examples of the more popular tools, it’s safe to assume companies have been using these tools for the better part of the past decade.
Now think about your company. Let’s take a quick assessment:
- What web analytics tool(s) do you currently use?
- How long has your company had it in place?
- Who owns the web analytics platform within your company?
- Do you know who originally set up the architecture and tracking for your web analytics tool?
- Is there documentation outlining what the tool is tracking and why?
Did you know the answer to each question? If so, pat yourself on the back. Color me impressed (I think that’s a saying, right?).
If not, chances are your company might have some web analytics issues.
Common Web Analytics Issues
- Outdated or insufficient tracking
- Confusion around tracking nomenclature in the tool
- If using multiple tools, confusion as to which one is the “official” tool for reporting purposes
- Untrustworthy data or data that doesn’t make sense
- Not understanding the tool due to no training or documentation available
- No support for questions or issues with the tool
- And the list goes on…
Many times, companies don’t know how they got to this point. Somebody will unearth an issue, emails are passed around the office about said issue, and more questions come up, rather than answers.
Let Me Tell You a Quick Story
This is one of the funnier, but sad, moments I’ve been a part of while working in the digital marketing industry.
I previously worked for a B2B agency, which specialized in print and digital media, web development, strategy and PR. A “full-services” agency as they all like to call themselves. I enjoyed working for this agency.
In my small amount of spare time, I was looking into the analytics behind our agency’s website. The website was built 2 or 3 years earlier, was outdated, and nobody paid attention to it. Hell, nobody owned it. And certainly nobody owned the analytics for the site.
I began digging into the top social sites that were driving leads for us, how certain elements of the site were performing and so on. Your standard analytics site audit.
I noticed some issues with improperly-tagged banners across the site that were muddying the data. So I start reaching out to people within my office about making the updates to the site. “Hey so and so, I noticed a few issues with our website. Who should I contact to get this updated?”
After a few emails, I’m led to a project manager (let’s call him Bill) that actually sits right across from me. Cool, easy enough.
So I approach Bill. “Bill, can you get these issues fixed on the site?”
Bill actually tells me he has no idea who does that or how to do it – but I should reach out to the CMO in the NYC office. He would know. I email him, again explaining the situation and politely asking who I should get in contact with to get the changes made on the site.
He replies that he’s excited someone is looking into the data. Very cool he says. And he then tells me that I should reach out to Bill, the PM, because he would know. So after about 10 emails, I’ve gone full circle, from Cincinnati, to NYC, back to Cincinnati, and nobody can tell me who to contact to make changes on the site to improve the analytics.
Hit ’em with the #smh gif, Larry Bird:
So, to summarize, all I wanted was to make a few minor updates to the site for better tracking and cleaner data. All I got was confusion about who could do it.
Why did I tell you this story? Well, one, it’s sort of funny because of the absurdity of the whole thing. NOBODY KNEW WHO HANDLED UPDATES TO OUR OWN SITE. Let that sink in for a second…
But I also told you this story as an example of some of the issues you might be running into at your company. Let’s break down a few of the top reasons why companies have web analytics issues, shall we?
Common Reasons Why Companies Have Web Analytics Issues
There really can be hundreds of different reasons why your company (or others) have issues with a web analytics platform. However, in the interest of my time and yours, I’ll list a few of the most common ones I see:
1. No One Owns Web Analytics
This is a much more common issue than you would expect. Companies have their standard siloed departments, like IT or development, marketing, finance, and so on. But, when it comes to web analytics, it can stretch across multiple departments. Most of the time, marketing isn’t technical enough to implement a complex tool like a web analytics platform or tag managment system. But, marketing is the end user and knows what data they want or need.
The IT/development team isn’t typically concerned with what the most popular stories or pages are on the site. Or what three products have the highest conversion rate. They want the site to operate correctly, load quickly, and have a great user experience. But, they have the technical knowledge and already own site development.
The finance department most likely doesn’t care about any of those above things. They’re interested in knowing how much the tool costs and what return they can expect from the investment.
Because of the cross-functional nature of web analytics, it can become a gray area within companies. IT handles implementation. Marketing handles reporting. But when it comes to re-evaulating the current setup, providing ongoing training and documentation, or ensuring it’s adoption throughout the organization, who handles that?
At InfoTrust, we recommend creating a cross-functional team that owns web analytics within the organization. An example would be an IT/dev lead, a manager or director of marketing, and a few others sprinkled in for good measure. This way, all the teams that will be utilized for the implementation are represented and there is a clear ownership group.
2. Multiple Analytics Tools are Being Used
This is an interesting issue. I’ve noticed it plenty of times – and even in doing some research using Tag Inspector. Plenty of organizations and websites use multiple web analytics tools. For instance, The New York Post uses Chartbeat and Google Analytics. The LA Times uses Google Analytics and Adobe SiteCatalyst (or Omniture or Adobe Analytics or whatever its called today).
I’ve seen a good amount of companies use a paid tool like Adobe SiteCatalyst and a free tool like Google Analytics. The reasons why usually differ – but it can lead to confusion. Typically, the data between two systems, even though they’re measuring the same thing, can be a bit different. Comparing the data between tools can be a nightmare.
Think about it this way. Organizations aren’t setting up both of these tools at the same time. This means different people were probably involved, interested in tracking different things, and one implementation is going to be older than the other. Therefore, comparing these two tools can acually become counterproductive.
Another issue with the two-tool method is that people don’t know which tool to use or which one to believe.
“Tool A says we had 500,000 pageviews on this story while Tool B says 390,000. Which is true?” Unfortunately, it can be a combination of both. Tool A might be tracking a pageview for each page refresh (to load new ads), while Tool B might not. Which is more accurate? I guess it would depend on your company’s definition of “pageviews”.
Our recommendation is to always choose one tool you’re confident in. Launch a pilot if you need to test a tool to ensure accuracy. With the right teams involved, a standardized architecture and tracking methodology can be agreed upon. This ensures the accuracy you’re looking for, but also allows for the understanding behind the metrics for your organization.
3. No One Understands the Current Setup and Architecture
You won’t believe how many times I’ve asked a client (or my own company) why something was set up a certain way and received an “I have no idea” answer. Employee turnover is usually one reason this happens. “Billy Bob actually set everything up, but he’s no longer with the company.”
Another reason is outsourcing this type of work to other companies, who either don’t set it up correctly or your company no longer has a relationship with them. “Actually, ‘It’s All About the Analytics’ set everything up a few years ago and the person we worked with isn’t there anymore.”
Whatever the reason, it’s essential to understand the current setup and architecture before you can make improvements. Hell, before you can even trust the data. I’ve ran into a few clients that were tracking things completely wrong, making a mess of their data.
How can you expect to make informed marketing decisions if you don’t know what is currently being tracked and if it’s accurate? Hint: You can’t…at least in good conscience.
Our recommendation is to always document everything. Document the initial architecture. Document what is being tracked and why. Document who to contact with issues or for support. Document how to document things (this last one I’m kidding – partially).
Which leads us into the last reason…
4. There is No Training, Support or Documentation Available
That last reason ties into #1 and #3. Without an owner, there most likely won’t be any training, support or documentation available on the current setup. If there is no training, support or documentation, nobody will understand your current setup and architecture. It’s a vicious circle, really.
Think about it this way. If somebody starts at your company today, how will you get them up to speed and using your web analytics tool?
We have two solutions:
1) You can choose people within your organization (or hire someone new) that have the necessary knowledge to own this space. This includes owning the training, support, and documentation.
2) You can partner with a company like InfoTrust to plan and execute your implementation according to your business objectives and goals, while also providing ONGOING training, support and documentation for the web analytics tool. We’ve found this to be highly successful with our clients, because this allows them to focus on making decisions with the data.
