Conversions are the lifeblood of digital advertising. They are often also referred to as leads, sales, goals, purchases, visits or subscriptions. With the digitisation of advertising, advertisers and their agencies have been submerged with data and performance measurement. And this is great news. Today more than ever we can link media investment to performance.
But it appears that this ever constant stream of data is not always making decision making any easier. Some would say that it is actually more complex than ever to plan, optimise and report on campaigns. Why is that? Shouldn’t conversion data make decision making an easy, seamless exercice?
The answer lies both in the nature of the data that is being measured, and in the method by which the data is being measured. In this post we will assume that your conversion data is being measured properly, and focus on the meaning of your conversion data.
A common complexity in conversion measurement is the attribution exercise, and here is why. When advertisers started being able to measure their campaigns’ performance, attribution models were simple or non-existent. Measuring conversions often meant attributing a sale or lead to the last measurable traffic source. This is often still the case today. The issue with that, while valuable information, this rarely represents the complexity of the customer journey, causing inaccurate conclusions.
Complexity you say?
Conversion paths variety
First of all, the user behavior to conversion is much more complex that originally portrayed. Those who track conversion paths on their website will know that there can be several thousands of unique conversion paths leading to conversions.
Example of a unique conversion path:
Complexification
User behavior has complexified intensely in the last few years. More than ever, daily tasks are conducted online. More than ever, people use multiple devices to access and browse the web. Beyond the cross-channel complexity illustrated above, online marketers have to deal with a cross-device complexity.
Tracking & measurement
The complexification is not only caused by changing user behavior. As tracking and measurement technology evolve, we get closer to understanding the complexity previously hidden by technical limitations. View-through conversions (VTC) have been measured for a few years now, and impression data has been linked to online conversions, adding another level of complexity. Cross-device tracking (covered below) also clearly illustrates this evolution.
View-through conversions
Ok, so why should I care about view through conversions? This set of data can help you understand the impact of upper funnel & branding campaigns. A view-through conversion occurs when conversion value is attributed to an online impression. This means that you can evaluate the impact of branding and remarketing campaigns that did not generate direct clicks to your website.
View-through conversions should evidently not be used as an attribution tool. This would not be accurate as an other traffic source should be credited as well. It is however interesting to use VTC performance to benchmark one campaign versus another. VTCs can also be used to optimise campaigns by identifying networks & audiences that perform better.
Cross Device
In Belgium, 69% of people use 2 or more connected devices, and 48% of people use 3 or more connected devices (Source: Consumer Barometer). Why is this complicating things? Because most of your online measurement is cookie based, and therefore device dependent. This is slightly changing as global technology providers such as Google and Facebook can manage to detect logged-in users across the web, and to link the dots. Google launched a new metric recently, estimated cross-device conversions. Actually, since September 2016, cross-device conversions are automatically integrated in your AdWords conversion reports (official communication here). Should you freak out? Definitely not. When you think about it, this is no stranger than the widely accepted industry standard of ‘30 days cookie window’ for post-click conversions. Simply make sure that you are aware of the change, as it may impact data in your reports as of September 2016. Be careful when looking at evolution over time as you may be comparing apples with, well..., slightly larger apples.
Conclusions
Our main tip is to always measure, analyse, adapt and repeat. Note the ‘adapt’ step in this process. We have seen that both user behavior and technology evolve over time, so should your measurement.
Understand the complexity and don’t jump to conclusions. Remember that there are many impression and click touch points before most conversion. Remember also that each platform measures performance differently, and that cross platform comparisons will often duplicate conversions, and thus complicate interpretation (for example, a conversion might be attributed to an affiliate impression in the affiliate’s platform, while the same conversion will be attributed to an AdWords click in Google AdWords).
There are several ways to limit the risk of duplication. The safest is to do your attribution exercise with site centric data (as opposed to ad platform centric data). Simply said, attribution should be done with web analytics tools that include the entire diversity of traffic source, from paid media to organic and email (Google Analytics, Adobe Analytics, …) rather than directly within advertising platforms.
After you’ve identified the complexity for your own performance, match it with an appropriate and flexible media mix (user trends don’t wait the next fiscal year in order to change). Conversion measurement can help valuing one channel versus another in a media mix and in a digital strategy. It should not, however, be understood as an ultimate measurement/attribution metric.
Happy measurement !
Author: Julien Cornet
