So, you are interested in learning how digital marketing channels such as Display and YouTube contributed to a conversion (or multiple conversions). In other words, this is what Avinash Kaushik calls MCA-ADC: Multi-Channel Attribution Across Digital Channels. You’ve already seen this other Last-Click blog article and as a result you enabled your Google Analytics account to tie display impressions to your conversions.
You’re happy with the new insights and especially when you’re responsible for Display campaigns, very happy with the new impact you’re seeing in the multi-channel attribrution funnel. Now you’ve seen that Display makes an impact on your conversions, you want to integrate this in your attribution model – but how to actually click your way through Analytics? Here’s how.
In the same blog by Avinash mentioned above, he mentions that the core premise of the time decay model is that the media touch point closest to conversion gets most of the credit, and the touch point prior to that will get less credit based on a smart and simple algorithm. It passes the common sense test, as overall it does seem to make sense that the further back in time a media touch point is, the less credit it should get. After all, if the touch points were so incredibly magnificent, why did they not convert? So, in this example we will switch the attribution model from Last-Click to Time Decay, and we will adjust credit for impressions.
First, let’s go into Analytics and scroll way down to Conversions:
Then, click Model Comparison, and then click the little blue links under Custom Models that says Create New Custom Model:
You will see this lovely screen pop up:
Second, you can adjust days prior to conversion on top of the Time Decay tool based on your Time Lag report in the Multi-Channel Funnels folder. This means that an interaction that happens more than 7 days before the conversion will get half the credit of an interaction within the last 7 days before the conversion.
You can apply custom credit rules, which are custom rules that apply uniquely to your company. Here, you can start to value your campaigns based on the interaction they deliver. Here we adjust credit for impressions. If there is an impression (people only see the ad), you can start to value that too, in addition to clicks that are the default interaction that gets credit.
Step 3, see the cryptic line “credit all impressions 1 times other interactions in the conversion path.”. Huh, what’s that? Well, maybe you value an impressions a bit less than ads that get people to click on them. This setting at 1 times means that you equally value an impression to another interaction, most commonly a click. So, if you leave this setting, that means that when a prospect sees an impression and then goes to Search and clicks one of your ads, and then converts, both the display impression and the search campaign get 0.5 conversions ascribed to it.
Last, you can go nuts with the setting to adjust credit for impressions based on how much hours or days before a visit to your website:
You’ve done it! Now your attribution model is Time Decay adjusted by also giving credit to display impressions. Well done, now realize that this is not the end but just the beginning; remember that this switch does not mean you’re right, it just means you’re getting less wrong with your attribution.
Looking at the blogs, articles, and conferences, attribution is a hot topic for today’s marketers. A quick search for the topic on your favorite search engine delivers lots of content and technologies devoted to the subject. But is attribution actually a problem for you? Is it something that currently keeps you from your goals and should you be investing your analytics dollars in understanding?
The key to understanding if you might have an attribution problem is understanding the way that customers buy your products and services. Are the customer journeys simple, short and does your conversion event happen in that single visit? Or are they typically quite complex? If you look at the paths to purchase and you see that the journeys are quite short en “one touch” paths to purchase, i.e. customers either bought on their first visit or they didn’t, then you might not have an attribution problem at all. When the majority of conversions happen on a single visit then it doesn’t matter which model you use, their output will be the same!
However, be careful in looking at your current data set only, because it might be that you have data problems because you’re not tracking journeys across different devices and touch points, meaning that you are not getting a complete picture. In case you are currently using paid search and looking to deploy video campaigns, then this medium will probably not deliver the same results on the basis of the attribution model that worked well in the past for your paid search campaigns. From the data you might quickly conclude that ‘video does not work’, where in face your attribution model ‘is not longer appropriate’. In other words, you might develop an attribution model.
This is not to say that you need to cherry-pick attribution models based on the medium – it means that you select the attribution model that best fits the path to purchase and maximizes business results. Your attribution model is not ‘fixed’, and it should not be, as the path to purchase and the channel mix changes over time to drive more business.
When was the last time when you optimized your attribution model? We look forward to your comment!
Posted in Attribution in Online Advertising, Attribution Model, Conversion Tracking, Last Click Attribution, Marketing Attribution Tagged with: attribution model, attribution modeling, attribution problem, last click attribution