Analytics tools are like fitness equipment.  They are a means to an end.  Simply implementing a tool won’t get you anywhere.  That’s like buying a treadmill and never getting on it.

The purpose of the tool is to gain valuable insights to improve your online presence.  I hear clients and analysts constantly talking about why they can’t justify spending money on a Digital Analytics tool.  That point is almost always followed up with, “but we need to do something.”

If you’re not willing to invest, you don’t need anything… you will automatically have a negative ROI.  Skip to the end of this post then come back later once you’ve fallen even farther behind.

I’ve listed some of the arguments I’ve heard against implementing a Digital Analytics program.  What I’ve found, with near 100% consistency, is that people do not know what they’re missing when it comes to analytical insights and have a presumption that costs will outweigh benefits because it will be too difficult to act on any insights gained.  The real issue is that they are simply unwilling to put their organizations on a “Data Fitness Program” and train to become analytically-driven.

Here are the main excuses I hear and steps to become Data Fit:

Excuse #1:  We don’t have the budget for tools.

Investing doesn’t necessarily mean going out and getting a tool like Omniture SiteCatalyst (though I’d recommend it) or WebTrends.  You may do just fine with Google Analytics for free… the true investment needs to be in time and willingness to rely on the data more than your emotions.  Truth can be found in numbers and increased return in truth.

I see the wheels turning… yes, you need to have a person to do it.  Maybe you’re that person, maybe not, but at some point this person or team of people will become your biggest investment.  Focus on getting a return from their analysis vs. recouping the cost of the tool.

Data Fitness Step One — Warm up your brain.  Do some research and try to understand what data you need to influence your online performance.  From there, you can worry about how to actually get the data.

Excuse #2:  We can’t do much with old data.

Naysayers may argue that online data is historical and past performance doesn’t mean blah, blah, blah… BS.  Anyone that’s ever built a predictive model or pretends to understand one will surely agree that historical data is essential to predict future performance.  If you don’t know where you came from, how will you know where you’ve gone?  Further, this data is coming to you in near real-time and is an unbiased look over the shoulder of what people are doing on your site.

The real issue tends to be is that the organization may not be set up to move quick enough (or believe they are quick enough) to make changes that site analytics show you need to make.  This is a fitness issue, not a data issue.

Data Fitness Step Two — You need to train yourself to start small and work up to an analytically-driven organization.  Don’t look at every KPI… don’t try to triple your conversion rates, just get a clear picture of what’s happening and then plan your strategy, with analytically supported tactics, to meet those other goals.  Problems with other departments?  You need a project sponsor to serve as a “coach” and get everyone into shape.

Excuse #3:  ROI is impossible to quantify on Digital Analytics.

First, this isn’t true.  ROI is easy to quantify through testing and implementing improvements based on the data.  This is where the value of Digital Analytics data is unlocked.  Getting the data and reporting it vs. doing something with it is like buying a treadmill and using it to hang clothes.

Sure, you may be net-negative on the entire implementation at first go, but this is a long-term thing.  One workout doesn’t make you fit.

To that point, ROI for Digital Analytics is continuous.  Because the data continuously feeds into the decision process, it is expected that returns increase while holding Digital Analytics costs relatively constant or decreasing over time.  Just like regular exercise, you need to get into a routine.

Data Fitness Step Three — Think beyond the fiscal quarter.  You’re running a marathon.  Keep up the workouts and using the data will become much easier.

Excuse #4:  Data value can’t be determined.

Really?  Let’s say you’re running an AdWords campaign and you know what keywords drove people to your site.  The campaign costs money, right?  You received knowledge of what brought people to your site.  Therefore, you can indeed assign a value to a key piece of data.  That value is the actions taken less the cost of the traffic.  Maybe you paid too much for the traffic because keywords aren’t optimized.  Maybe you didn’t get enough conversion on your site because it needs improvement.  Regardless, the data will tell you what you need and you’ll be able to optimize your spend and increase conversion to yield positive ROI.

Take the example a step further.  Through Digital Analytics, you now know what people did once arriving to your site from the campaign vs. general site traffic.  You know what content they viewed, what they purchased, and other behavioral data.  Each of these learnings adds value and they’re quantifiable via a variety of KPIs.

The challenge is figuring out how to assign value.  You need to ask yourself what you learned from the data and what that information would a) cost to obtain elsewhere (BTW… people lie in focus groups, surveys, etc. but don’t lie in their click paths.  Think about that for a little while).  You also need to factor back in the data you obtained as part of your continuous ROI measurement since you’ll be building your future testing and fine-tuning on the data… right?  In this case, think of ROI as not just Return on Investment but as Return on Information.

Data Fitness Step Four — Information is like a set of stairs.  You have to keep climbing one step after the next to get to the top.  On the way up look out and gain some perspective over your site and audience.

So to sum up, the biggest investment needs to be in your willingness to learn to use the data available and to spend time training yourself for a marathon and not a run around the block.  Justifying the investment may be difficult since people invariably consider hard costs as more “real” than what is left on the table by doing nothing.  However, doing nothing is doing it all wrong.