In marketing, we measure success in conversions and that means we need the best data possible to attain the greatest ROI. So what happens if your analytics program is misrepresenting your data? Unfortunately, if you’re using Google Analytics to measure lengthy conversions, that may be exactly what’s happening. One of the top programs among marketing experts, Google Analytics, just isn’t designed to take-on the complex processes that lead up to the sale.
How Long Conversions Take
The length of time from first contact to conversion depends on a number of factors, but one of the leading issues is cost. For low cost products, conversions are typically fairly quick, from a few minutes to a few days; micro conversions like newsletter sign-ups are almost immediate. In order to get a clear read on your average conversion rate, though, you’ll need to make sure you’re getting the complete attribution data.
Attribution data helps you assess the path customers take from contact to sale, but it also allows you to measure the length of time it takes to make a sale. For high-cost products, such as televisions or cars, that conversion window may be more than 90 days. The problem: Google Analytics only measures a maximum of 90 days. After that, the count starts over, meaning that a 120-day conversion might look like it took 30 days. You can’t function with that kind of distorted data.
It’s no surprise that Google Analytics falls short on big-picture reads. The fact is, you can do something well or you can do it for free. Google Analytics does its job remarkably for a free service, but it can’t offer everything a paid service might. That’s par for the course, but if you think you’re getting the whole story using free software, you’re mistaken.
Device Diversification Problems
Not all conversion data challenges are caused by the programs. For example, how do you know when the first contact was if two people share a device? Or, the opposite problem – how do you track the path of one person using multiple devices? Both multiple devices and multiple users on a single device can dramatically skew conversion data, either turning a frequent visitor into a new sale or merging multiple people into one data trail.
Ideally, analytics programs will find a way to attribute conversion activities more accurately, but the fact is without a sign-in or user-based cookie system, we’re not at a point where we have that level of insight. It’s confusing, but by encouraging all users to create sign-ins, not just those who have already made a sale, companies can improve what data they do have.
More Micro Conversion Paths
If you want to increase conversion rates and improve the accuracy of your data, one option is to increase the number of micro conversion opportunities. Micro conversions can help link data to the appropriate users when they enter information, differentiating between multiple users on the same device or connecting actions by the same user across devices.
When tracking conversion pathways, businesses often perceive them as dragging out because we don’t value micro conversions as highly as completed sales, but that doesn’t mean they aren’t important. Our failure as businesses to elevate the landmarks along the way is a structural one, but when we highlight those key moments, we become aware of just how active and engaged potential customers really are.
Macro conversions are exciting, but they only happen once; after that, it’s about maintaining the relationship. Focusing on that singular shift, the moment of the first sale is a recipe for frustration and distortion.
There are no perfect data measurement solutions, but we can be smarter about how we trace conversion paths and determine sales attributions. Somewhere in all that data is the truth about the road from contact to conversion.