Placing ads online is a lot like investing. As a digital advertiser, you invest a sum of money in order to convert new or existing customers and hopefully make a return on your initial investment. For the e-commerce advertiser, this return comes in the form of direct online sales. For the mobile app developer, this return comes in the form of users or in-app purchases. For the publisher, this return comes in the form of page views.
What each of these advertisers has in common is an utter lack of clarity when it comes to understanding what is truly working and what is wasteful. Over the last five years, I've personally worked with hundreds of advertisers from around the world to help them manage and scale tens of millions of dollars in ad spend. I've seen many throw money at the wall in hopes of driving conversions with no set strategy in place to track, measure and attribute their conversion funnel.
Most paid media tracking and automation tools are also out-of-reach for small and mid-market advertisers, giving them no option to effectively track and measure attribution. These powerful systems are typically reserved for the enterprise elite who can afford to shell out a few thousand dollars a month to use them, or an even larger investment to build a version of their own.
The Attribution "Gray Area"
If you advertise online, then chances are you already understand the complexity that comes with measuring a return on ad spend. This return on investment can come in many shapes and sizes, but for most brands the best measure of success is sales. The issue is understanding where those sales come from. Imagine this scenario: a customer clicks on one of your Google Adwords campaigns, visits your website, leaves, and two days later comes back to your site due to a retargeting ad in their Facebook Newsfeed, then leaves again and returns in a few days organically to finally buy something. Who gets credit for the conversion? Is it Google, Facebook, direct traffic or a mix of each? This is the gray area in digital advertising that leaves many scratching their heads. Last-click attribution models, a model that gives conversion credit to the channel that drove the "last click," aren't enough when advertisers are managing dozens of campaigns across dozens of different ad channels.
Google Adwords, Facebook, Twitter, Pinterest, Snapchat, LinkedIn, display networks, native advertising, video advertising and thousands of blogs and other paid channels are just some of the many options available to advertisers. The more advertising opportunities that arise, the more complex tracking, managing and optimizing cross-channel ad spend becomes. As the famous early marketing pioneer, John Wanamaker said, "Half the money I spend on advertising is wasted; the trouble is I don't know which half."
Advertisers' Problem With Digital Media Giants
Companies like Facebook, Google and Twitter have been racing to tackle this problem head on. All three have their own versions of tracking pixels, which can be installed on an advertiser's website or in their mobile app to track events, conversions and users who can later be retargeted with more ads.
Advertisers have no access to any information about the user data that is collected and also have little to no insight into what moves these users make before they actually convert. The pixels that Facebook, Google, Twitter and others provide don't offer advertisers the ability to fully visualize, understand and optimize their post-click conversion funnel, or the process by which you engage with and drive users to convert after they first click on one of your ads.
There is very little sense as to how users who end up converting navigate down the post-click conversion funnel. All of this user and event-based data is extremely valuable to help advertisers learn more about their audience, spot bottlenecks in their conversion funnel, and improve the overall performance of paid media campaigns, but right now it's out of reach.
Most advertisers are driving cross-device traffic from multiple ad channels, as well as from other various marketing efforts outside of paid media. When they compare data points from these multiple sources and drill down to actual conversions, it becomes very difficult to understand the true value of return; and more importantly: where it came from.
A Workable Solution
Advertisers have a variety of different third-party tracking options that can help them track users and on-site or in-app events, but the impetus is still on the advertiser to put that third-party tracking data to work. On top of that, advertisers already have a slew of different tools and tabs open to access and analyze all of their data.
Here is an example of a few tabs in an advertiser's browser at any point in time: Facebook's Ads Manager or Power Editor, a Google Adwords dashboard, a Google Analytics dashboard, a third-party tracking system dashboard, a third-party retargeting dashboard, a sales dashboard from a payment processor, a CRM to track users and leads and more. What follows is the manual process of exporting all of this data from different sources and trying to make sense of it.
For now, advertisers have very little choice when it comes to effectively measuring true cross-channel ad spend attribution. It's an incredibly manual, confusing, and time-consuming process. While those with big budgets can afford pricey attribution software or build their own, others choose to outsource paid media management entirely or hire an in-house specialist to work on management and attribution full time. The common thread for both of these groups is that attribution remains the biggest problem in digital advertising.